1
Journal Plant Physiology 1
Short title mGWAS reveals Gln-GLS link in Arabidopsis seeds 2
Corresponding author Ruthie Angelovici 3
E-mail angelovicirmissouriedu tel +1 573-882-3440 4
5
Article title mGWAS Uncovers Gln-Glucosinolate Seed-Specific Interaction and its 6
Role in Metabolic Homeostasis 7 8 Marianne L Slaten1 9 mleww8mailmissouriedu 10 11 Abou Yobi1 12 yobiamissouriedu 13 14 Clement Bagaza1dagger 15 cb36fmailumsledu 16 17 Yen On Chan1 18 chanyemailmissouriedu 19 20 Vivek Shrestha1 21 vs6d9mailmissouriedu 22 23 Samuel Holden
1 24
slhdmbmailmissouriedu 25 26 Ella Katz2 27 elkatzucdavisedu 28 29 Christa Kanstrup4 30
ckaplenkudk 31
32 Alexander E Lipka3 33 alipkaillinoisedu 34 35 Daniel J Kliebenstein2 36 kliebensteinucdavisedu 37 38 Hussam Hassan Nour-Eldin4 39 huhaplenkudk 40 41 Ruthie Angelovici1 42 angelovicirmissouriedu 43 44
1Division of Biological Sciences Interdisciplinary Plant Group Christopher S Bond Life Sciences 45 Center University of Missouri Columbia MO 65211 USA 46
Plant Physiology Preview Published on April 21 2020 as DOI101104pp2000039
Copyright 2020 by the American Society of Plant Biologists
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2
2Department of Plant Sciences UC Davis Davis CA 95616 USA 47 3Department of Crop Sciences University of Illinois Urbana IL 61801 USA 48 4DynaMo Center Copenhagen Plant Science Centre Department of Plant and Environmental 49
Sciences University of Copenhagen Frederiksberg Denmark 50 daggerCurrent address Department of Biology University of Missouri Saint Louis MO 63121 USA 51
52
53
Author contributions 54
MS performed the experiments wrote the manuscript and processed and analyzed data AY wrote the 55
manuscript and carried out metabolic analysis CB carried out genotyping experiments YC analyzed data 56
VS analyzed data SH carried out genotyping and metabolic analysis EK performed GLS measurements 57
CK peformed initial gtr12 experiment AL verified analytical methods and assisted with statistical aid H 58
N-E provided gtr12 mutants and initial analysis DK provided all the GLS mutants and GLS related 59
measurements from the population RA conceived the experimental design supervised the work provided 60
funding and wrote the manuscript All authors have reviewed the final version of the manuscript and 61
approved it and therefore are equally responsible for the integrity and accuracy of its content 62
63
Funding information 64 This work was funded by the NSF-IOS 1754201 to Ruthie Angelovici and by Danish National 65
Research Foundation grant DNRF99 to BAH and HHN-E 66
One-sentence summary mGWAS of Gln-related traits reveals an unexpected seed-specific 67
interaction between glutamine and glucosinolates and its potential role in shaping the metabolic 68
homeostasis in Arabidopsis seeds 69
70
71
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Abstract 72
Glutamine (Gln) is a key player in plant metabolism It is one of the major free amino acids that 73
is transported into the developing seed and is central for nitrogen metabolism However Gln 74
natural variation and its regulation and interaction with other metabolic processes in seeds 75
remain poorly understood To investigate the latter we performed a metabolic genome-wide 76
association study (mGWAS) of Gln-related traits measured from the dry seeds of the 77
Arabidopsis diversity panel using all potential ratios between Gln and the other members of the 78
glutamate (Glu) family as traits This semi-combinatorial approach yielded multiple candidate 79
genes that upon further analysis revealed an unexpected association between the aliphatic 80
glucosinolates (GLS) and the Gln-related traits This finding was confirmed by an independent 81
QTL mapping and statistical analysis of the relationships between the Gln-related traits and the 82
presence of specific GLS in seeds Moreover an analysis of Arabidopsis (Arabidopsis thaliana) 83
mutants lacking GLS showed an extensive seed-specific impact on Gln levels and composition 84
that manifested early in seed development The elimination of GLS in seeds was associated with 85
a large effect on seed nitrogen and sulfur homeostasis which conceivably led to the Gln 86
response This finding indicates that both Gln and GLS play key roles in shaping the seed 87
metabolic homeostasis It also implies that select secondary metabolites might have key 88
functions in primary seed metabolism Lastly our study shows that an mGWAS performed on 89
dry seeds can uncover key metabolic interactions that occur early in seed development 90
Key words glutamine aliphatic glucosinolates mGWAS amino acids QTL seeds 91
92
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Introduction 94
95
Glutamine (Gln) is a free amino acid (FAA) that belongs to the glutamate family which also 96
includes glutamate (Glu) gamma-aminobutyric acid (GABA) proline (Pro) and arginine (Arg) 97
(Skokut et al 1978 Majumdar et al 2016 Okumoto et al 2016) This amino acid family plays 98
a key role in plant cell core metabolism by providing an entry point for inorganic nitrogen 99
Briefly ammonium derived from nitrate or absorbed directly from the soil can be assimilated 100
into Gln via the glutamine synthase (GS)glutamine oxoglutarate aminotransferase (GOGAT) 101
cycle (Lea and Miflin 1974) GSGOGAT is the primary nitrogen assimilation pathway in plants 102
(Ireland 1999) and is involved in the remobilization of nitrogenous compounds and the 103
assimilation of large amounts of ammonium generated by photorespiration in C3 plants (Foyer et 104
al 2009) 105
Gln plays an important role in seed metabolism as one of the main nitrogen carriers it is 106
transported via the xylem and phloem to sink tissues including developing seeds (Zhang et al 107
2010 Zhang et al 2015 Besnard et al 2016) A study of maturing Brassica napus seeds 108
showed that embryos import nitrogen in the form of amino acids (mainly Gln and alanine) to 109
synthesize other amino acids via transaminationdeamination reactions and then incorporation 110
into seed storage proteins (SSP) (Schwender et al 2006) Consistently studies in Arabidopsis 111
have shown that Gln levels are highly elevated prior to the onset of SSP synthesis (Baud et al 112
2002 Fait et al 2006) and then drop substantially during seed maturation (Fait et al 2006) 113
Even though the majority of seed Gln comes from transport several glutamine synthase 114
isozymes are expressed during seed development in the micropillar chalaza embryo and seed 115
coat which suggests that Gln is also actively synthesized in seeds (Winter et al 2007) The 116
content of Gln in dry seeds therefore may be the result of a balance between its incorporation 117
into SSP active synthesis and degradation However its composition may also reflect the 118
environmental conditions encountered by the maternal plant High levels of Gln have been 119
reported in Arabidopsis plants facing sulfur deprivation (Nikiforova et al 2006) and in tobacco 120
plants grown under high nitrogen conditions (Geiger et al 1999) whereas low levels of Gln 121
have been reported in Arabidopsis seedlings grown under nitrate-deficit conditions (Scheible et 122
al 2004) Interestingly extensive variation in free Gln content in dry Arabidopsis seeds has 123
been reported across the various accessions belonging to the Arabidopsis diversity panel 124
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(Angelovici et al 2017) but the genetic architecture regulating this trait remains poorly 125
understood Knowledge regarding the genes that underlie Gln levels composition and seed 126
partitioning would shed light on its potential seed-specific functions its interaction with other 127
biological processes and its role in downstream metabolism 128
In recent years genome-wide association studies (GWAS) as well as quantitative trait 129
loci (QTL) mapping experiments have facilitated the identification of many loci for both primary 130
and secondary metabolites (Wentzell et al 2007 Chan et al 2011 Riedelsheimer et al 2012 131
Angelovici et al 2013 Gonzalez-Jorge et al 2013 Chen et al 2014 Verslues et al 2014 132
Angelovici et al 2017) In-depth analyses of these QTLs have facilitated the further discovery 133
of key structural and regulatory genes that underlie the natural variation of metabolic traits and 134
the identification of various cellular processes involved in metabolic homeostasis Although 135
GWAS and QTL mapping have been conducted on FAAs in both vegetative and seed tissues 136
across several species no major QTLs have been identified for Gln (Riedelsheimer et al 2012 137
Chen et al 2014 Wen et al 2014) The lack of any identifiable loci implies that Gln either has 138
a complex genetic architecture or that these studies possibly utilized ldquounderpoweredrdquo association 139
panels or both 140
The use of metabolic ratios as traits in GWAS has been useful for dealing with several 141
such calcitrant metabolites The approach which relies on biochemical pathways andor 142
represent relationships uncovered by a metabolic network correlation analysis has yielded 143
several significant associations even when the absolute levels of metabolites have not (Wentzell 144
et al 2007 Lipka 2013 Angelovici et al 2013 Gonzalez-Jorge et al 2013 Angelovici et al 145
2017) It has been postulated that metabolic ratios are less complex (since they only represent the 146
metabolite partitioning within biochemical pathways) and therefore are more tractable in 147
association mapping studies (Angelovici et al 2017) Still even this approach has failed to 148
identify QTLs for Gln in dry seeds (Angelovici et al 2017) 149
A different approach is clearly needed to uncover the genetic architecture of Gln 150
Notably the metabolic ratios used in previous studies do not represent all the potential ratios of 151
Gln-related traits since they were based principally on a priori pathway information which is 152
often incomplete 153
In theory performing a metabolic genome-wide association study (mGWAS) on all 154
possible Gln-related metabolic ratios would potentially resolve its genetic architecture In 155
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practice however such an endeavor would be challenging given the enormous number of 156
metabolic ratios that could be derived from the relationships between Gln and all 20 proteogenic 157
amino acids Therefore as a point of departure from previous studies we derived all possible 158
metabolic ratios of Gln only to its proteogenic amino acid family members thus theoretically 159
representing all potential biologically relevant partitioningrelationship of Gln within the Glu 160
family (Fig 1) By combining this approach with a Fixed and Random Model Circulating 161
Probability Unification (FarmCPU) which uses fixed and random effect models for powerful 162
and efficient GWAS studies (Liu et al 2016) we uncovered many significant QTLs for various 163
Gln-derived traits in dry seeds More importantly our analysis of the candidate genes revealed a 164
surprising enrichment for genes residing in the glucosinolate (GLS) biosynthesis pathway 165
suggesting a potential interplay between two metabolic pathways that are not known to be 166
directly linked (Fig 1) We validated this association by using an independent QTL mapping 167
approach as well as by characterizing Gln and other FAAs in mutant plants that have a disrupted 168
GLS composition and loading to the seeds Our data support an association between GLS natural 169
diversity and Gln levels and composition in seeds and also reveal that GLS loading to the seeds 170
has a profound effect on seed nitrogen and sulfur homeostasis as well as Gln levels and 171
composition Our results strongly suggest that an interaction between Gln and GLS plays a key 172
role in seed metabolic homeostasis 173
174
175
Results 176
177
The Four Glu Family Members Vary in Abundance Relative Composition and Broad-178
Sense Heritability Across the Arabidopsis Diversity Panel 179
In a previous study we quantified and described the natural variation of 18 out of the 20 180
proteogenic FAAs (excluding cysteine and asparagine) measured from dry seeds of three 181
biological repeats of a 313-accession Arabidopsis diversity panel (Angelovici et al 2013 182
Angelovici et al 2016) In the current study we used that data to assess the natural variation 183
among only the proteogenic FAAs in the Glu family ie Glu Pro Gln and Arg 184
Our analysis showed that the four Glu family members vary in abundance relative 185
composition and broad-sense heritability (Supplemental Table S1A) Glu was the most abundant 186
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amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
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Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
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38
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Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
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2
2Department of Plant Sciences UC Davis Davis CA 95616 USA 47 3Department of Crop Sciences University of Illinois Urbana IL 61801 USA 48 4DynaMo Center Copenhagen Plant Science Centre Department of Plant and Environmental 49
Sciences University of Copenhagen Frederiksberg Denmark 50 daggerCurrent address Department of Biology University of Missouri Saint Louis MO 63121 USA 51
52
53
Author contributions 54
MS performed the experiments wrote the manuscript and processed and analyzed data AY wrote the 55
manuscript and carried out metabolic analysis CB carried out genotyping experiments YC analyzed data 56
VS analyzed data SH carried out genotyping and metabolic analysis EK performed GLS measurements 57
CK peformed initial gtr12 experiment AL verified analytical methods and assisted with statistical aid H 58
N-E provided gtr12 mutants and initial analysis DK provided all the GLS mutants and GLS related 59
measurements from the population RA conceived the experimental design supervised the work provided 60
funding and wrote the manuscript All authors have reviewed the final version of the manuscript and 61
approved it and therefore are equally responsible for the integrity and accuracy of its content 62
63
Funding information 64 This work was funded by the NSF-IOS 1754201 to Ruthie Angelovici and by Danish National 65
Research Foundation grant DNRF99 to BAH and HHN-E 66
One-sentence summary mGWAS of Gln-related traits reveals an unexpected seed-specific 67
interaction between glutamine and glucosinolates and its potential role in shaping the metabolic 68
homeostasis in Arabidopsis seeds 69
70
71
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Abstract 72
Glutamine (Gln) is a key player in plant metabolism It is one of the major free amino acids that 73
is transported into the developing seed and is central for nitrogen metabolism However Gln 74
natural variation and its regulation and interaction with other metabolic processes in seeds 75
remain poorly understood To investigate the latter we performed a metabolic genome-wide 76
association study (mGWAS) of Gln-related traits measured from the dry seeds of the 77
Arabidopsis diversity panel using all potential ratios between Gln and the other members of the 78
glutamate (Glu) family as traits This semi-combinatorial approach yielded multiple candidate 79
genes that upon further analysis revealed an unexpected association between the aliphatic 80
glucosinolates (GLS) and the Gln-related traits This finding was confirmed by an independent 81
QTL mapping and statistical analysis of the relationships between the Gln-related traits and the 82
presence of specific GLS in seeds Moreover an analysis of Arabidopsis (Arabidopsis thaliana) 83
mutants lacking GLS showed an extensive seed-specific impact on Gln levels and composition 84
that manifested early in seed development The elimination of GLS in seeds was associated with 85
a large effect on seed nitrogen and sulfur homeostasis which conceivably led to the Gln 86
response This finding indicates that both Gln and GLS play key roles in shaping the seed 87
metabolic homeostasis It also implies that select secondary metabolites might have key 88
functions in primary seed metabolism Lastly our study shows that an mGWAS performed on 89
dry seeds can uncover key metabolic interactions that occur early in seed development 90
Key words glutamine aliphatic glucosinolates mGWAS amino acids QTL seeds 91
92
93
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Introduction 94
95
Glutamine (Gln) is a free amino acid (FAA) that belongs to the glutamate family which also 96
includes glutamate (Glu) gamma-aminobutyric acid (GABA) proline (Pro) and arginine (Arg) 97
(Skokut et al 1978 Majumdar et al 2016 Okumoto et al 2016) This amino acid family plays 98
a key role in plant cell core metabolism by providing an entry point for inorganic nitrogen 99
Briefly ammonium derived from nitrate or absorbed directly from the soil can be assimilated 100
into Gln via the glutamine synthase (GS)glutamine oxoglutarate aminotransferase (GOGAT) 101
cycle (Lea and Miflin 1974) GSGOGAT is the primary nitrogen assimilation pathway in plants 102
(Ireland 1999) and is involved in the remobilization of nitrogenous compounds and the 103
assimilation of large amounts of ammonium generated by photorespiration in C3 plants (Foyer et 104
al 2009) 105
Gln plays an important role in seed metabolism as one of the main nitrogen carriers it is 106
transported via the xylem and phloem to sink tissues including developing seeds (Zhang et al 107
2010 Zhang et al 2015 Besnard et al 2016) A study of maturing Brassica napus seeds 108
showed that embryos import nitrogen in the form of amino acids (mainly Gln and alanine) to 109
synthesize other amino acids via transaminationdeamination reactions and then incorporation 110
into seed storage proteins (SSP) (Schwender et al 2006) Consistently studies in Arabidopsis 111
have shown that Gln levels are highly elevated prior to the onset of SSP synthesis (Baud et al 112
2002 Fait et al 2006) and then drop substantially during seed maturation (Fait et al 2006) 113
Even though the majority of seed Gln comes from transport several glutamine synthase 114
isozymes are expressed during seed development in the micropillar chalaza embryo and seed 115
coat which suggests that Gln is also actively synthesized in seeds (Winter et al 2007) The 116
content of Gln in dry seeds therefore may be the result of a balance between its incorporation 117
into SSP active synthesis and degradation However its composition may also reflect the 118
environmental conditions encountered by the maternal plant High levels of Gln have been 119
reported in Arabidopsis plants facing sulfur deprivation (Nikiforova et al 2006) and in tobacco 120
plants grown under high nitrogen conditions (Geiger et al 1999) whereas low levels of Gln 121
have been reported in Arabidopsis seedlings grown under nitrate-deficit conditions (Scheible et 122
al 2004) Interestingly extensive variation in free Gln content in dry Arabidopsis seeds has 123
been reported across the various accessions belonging to the Arabidopsis diversity panel 124
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5
(Angelovici et al 2017) but the genetic architecture regulating this trait remains poorly 125
understood Knowledge regarding the genes that underlie Gln levels composition and seed 126
partitioning would shed light on its potential seed-specific functions its interaction with other 127
biological processes and its role in downstream metabolism 128
In recent years genome-wide association studies (GWAS) as well as quantitative trait 129
loci (QTL) mapping experiments have facilitated the identification of many loci for both primary 130
and secondary metabolites (Wentzell et al 2007 Chan et al 2011 Riedelsheimer et al 2012 131
Angelovici et al 2013 Gonzalez-Jorge et al 2013 Chen et al 2014 Verslues et al 2014 132
Angelovici et al 2017) In-depth analyses of these QTLs have facilitated the further discovery 133
of key structural and regulatory genes that underlie the natural variation of metabolic traits and 134
the identification of various cellular processes involved in metabolic homeostasis Although 135
GWAS and QTL mapping have been conducted on FAAs in both vegetative and seed tissues 136
across several species no major QTLs have been identified for Gln (Riedelsheimer et al 2012 137
Chen et al 2014 Wen et al 2014) The lack of any identifiable loci implies that Gln either has 138
a complex genetic architecture or that these studies possibly utilized ldquounderpoweredrdquo association 139
panels or both 140
The use of metabolic ratios as traits in GWAS has been useful for dealing with several 141
such calcitrant metabolites The approach which relies on biochemical pathways andor 142
represent relationships uncovered by a metabolic network correlation analysis has yielded 143
several significant associations even when the absolute levels of metabolites have not (Wentzell 144
et al 2007 Lipka 2013 Angelovici et al 2013 Gonzalez-Jorge et al 2013 Angelovici et al 145
2017) It has been postulated that metabolic ratios are less complex (since they only represent the 146
metabolite partitioning within biochemical pathways) and therefore are more tractable in 147
association mapping studies (Angelovici et al 2017) Still even this approach has failed to 148
identify QTLs for Gln in dry seeds (Angelovici et al 2017) 149
A different approach is clearly needed to uncover the genetic architecture of Gln 150
Notably the metabolic ratios used in previous studies do not represent all the potential ratios of 151
Gln-related traits since they were based principally on a priori pathway information which is 152
often incomplete 153
In theory performing a metabolic genome-wide association study (mGWAS) on all 154
possible Gln-related metabolic ratios would potentially resolve its genetic architecture In 155
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6
practice however such an endeavor would be challenging given the enormous number of 156
metabolic ratios that could be derived from the relationships between Gln and all 20 proteogenic 157
amino acids Therefore as a point of departure from previous studies we derived all possible 158
metabolic ratios of Gln only to its proteogenic amino acid family members thus theoretically 159
representing all potential biologically relevant partitioningrelationship of Gln within the Glu 160
family (Fig 1) By combining this approach with a Fixed and Random Model Circulating 161
Probability Unification (FarmCPU) which uses fixed and random effect models for powerful 162
and efficient GWAS studies (Liu et al 2016) we uncovered many significant QTLs for various 163
Gln-derived traits in dry seeds More importantly our analysis of the candidate genes revealed a 164
surprising enrichment for genes residing in the glucosinolate (GLS) biosynthesis pathway 165
suggesting a potential interplay between two metabolic pathways that are not known to be 166
directly linked (Fig 1) We validated this association by using an independent QTL mapping 167
approach as well as by characterizing Gln and other FAAs in mutant plants that have a disrupted 168
GLS composition and loading to the seeds Our data support an association between GLS natural 169
diversity and Gln levels and composition in seeds and also reveal that GLS loading to the seeds 170
has a profound effect on seed nitrogen and sulfur homeostasis as well as Gln levels and 171
composition Our results strongly suggest that an interaction between Gln and GLS plays a key 172
role in seed metabolic homeostasis 173
174
175
Results 176
177
The Four Glu Family Members Vary in Abundance Relative Composition and Broad-178
Sense Heritability Across the Arabidopsis Diversity Panel 179
In a previous study we quantified and described the natural variation of 18 out of the 20 180
proteogenic FAAs (excluding cysteine and asparagine) measured from dry seeds of three 181
biological repeats of a 313-accession Arabidopsis diversity panel (Angelovici et al 2013 182
Angelovici et al 2016) In the current study we used that data to assess the natural variation 183
among only the proteogenic FAAs in the Glu family ie Glu Pro Gln and Arg 184
Our analysis showed that the four Glu family members vary in abundance relative 185
composition and broad-sense heritability (Supplemental Table S1A) Glu was the most abundant 186
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7
amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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8
(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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10
SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
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Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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38
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Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
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Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
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Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
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Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
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Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
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3
Abstract 72
Glutamine (Gln) is a key player in plant metabolism It is one of the major free amino acids that 73
is transported into the developing seed and is central for nitrogen metabolism However Gln 74
natural variation and its regulation and interaction with other metabolic processes in seeds 75
remain poorly understood To investigate the latter we performed a metabolic genome-wide 76
association study (mGWAS) of Gln-related traits measured from the dry seeds of the 77
Arabidopsis diversity panel using all potential ratios between Gln and the other members of the 78
glutamate (Glu) family as traits This semi-combinatorial approach yielded multiple candidate 79
genes that upon further analysis revealed an unexpected association between the aliphatic 80
glucosinolates (GLS) and the Gln-related traits This finding was confirmed by an independent 81
QTL mapping and statistical analysis of the relationships between the Gln-related traits and the 82
presence of specific GLS in seeds Moreover an analysis of Arabidopsis (Arabidopsis thaliana) 83
mutants lacking GLS showed an extensive seed-specific impact on Gln levels and composition 84
that manifested early in seed development The elimination of GLS in seeds was associated with 85
a large effect on seed nitrogen and sulfur homeostasis which conceivably led to the Gln 86
response This finding indicates that both Gln and GLS play key roles in shaping the seed 87
metabolic homeostasis It also implies that select secondary metabolites might have key 88
functions in primary seed metabolism Lastly our study shows that an mGWAS performed on 89
dry seeds can uncover key metabolic interactions that occur early in seed development 90
Key words glutamine aliphatic glucosinolates mGWAS amino acids QTL seeds 91
92
93
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Introduction 94
95
Glutamine (Gln) is a free amino acid (FAA) that belongs to the glutamate family which also 96
includes glutamate (Glu) gamma-aminobutyric acid (GABA) proline (Pro) and arginine (Arg) 97
(Skokut et al 1978 Majumdar et al 2016 Okumoto et al 2016) This amino acid family plays 98
a key role in plant cell core metabolism by providing an entry point for inorganic nitrogen 99
Briefly ammonium derived from nitrate or absorbed directly from the soil can be assimilated 100
into Gln via the glutamine synthase (GS)glutamine oxoglutarate aminotransferase (GOGAT) 101
cycle (Lea and Miflin 1974) GSGOGAT is the primary nitrogen assimilation pathway in plants 102
(Ireland 1999) and is involved in the remobilization of nitrogenous compounds and the 103
assimilation of large amounts of ammonium generated by photorespiration in C3 plants (Foyer et 104
al 2009) 105
Gln plays an important role in seed metabolism as one of the main nitrogen carriers it is 106
transported via the xylem and phloem to sink tissues including developing seeds (Zhang et al 107
2010 Zhang et al 2015 Besnard et al 2016) A study of maturing Brassica napus seeds 108
showed that embryos import nitrogen in the form of amino acids (mainly Gln and alanine) to 109
synthesize other amino acids via transaminationdeamination reactions and then incorporation 110
into seed storage proteins (SSP) (Schwender et al 2006) Consistently studies in Arabidopsis 111
have shown that Gln levels are highly elevated prior to the onset of SSP synthesis (Baud et al 112
2002 Fait et al 2006) and then drop substantially during seed maturation (Fait et al 2006) 113
Even though the majority of seed Gln comes from transport several glutamine synthase 114
isozymes are expressed during seed development in the micropillar chalaza embryo and seed 115
coat which suggests that Gln is also actively synthesized in seeds (Winter et al 2007) The 116
content of Gln in dry seeds therefore may be the result of a balance between its incorporation 117
into SSP active synthesis and degradation However its composition may also reflect the 118
environmental conditions encountered by the maternal plant High levels of Gln have been 119
reported in Arabidopsis plants facing sulfur deprivation (Nikiforova et al 2006) and in tobacco 120
plants grown under high nitrogen conditions (Geiger et al 1999) whereas low levels of Gln 121
have been reported in Arabidopsis seedlings grown under nitrate-deficit conditions (Scheible et 122
al 2004) Interestingly extensive variation in free Gln content in dry Arabidopsis seeds has 123
been reported across the various accessions belonging to the Arabidopsis diversity panel 124
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(Angelovici et al 2017) but the genetic architecture regulating this trait remains poorly 125
understood Knowledge regarding the genes that underlie Gln levels composition and seed 126
partitioning would shed light on its potential seed-specific functions its interaction with other 127
biological processes and its role in downstream metabolism 128
In recent years genome-wide association studies (GWAS) as well as quantitative trait 129
loci (QTL) mapping experiments have facilitated the identification of many loci for both primary 130
and secondary metabolites (Wentzell et al 2007 Chan et al 2011 Riedelsheimer et al 2012 131
Angelovici et al 2013 Gonzalez-Jorge et al 2013 Chen et al 2014 Verslues et al 2014 132
Angelovici et al 2017) In-depth analyses of these QTLs have facilitated the further discovery 133
of key structural and regulatory genes that underlie the natural variation of metabolic traits and 134
the identification of various cellular processes involved in metabolic homeostasis Although 135
GWAS and QTL mapping have been conducted on FAAs in both vegetative and seed tissues 136
across several species no major QTLs have been identified for Gln (Riedelsheimer et al 2012 137
Chen et al 2014 Wen et al 2014) The lack of any identifiable loci implies that Gln either has 138
a complex genetic architecture or that these studies possibly utilized ldquounderpoweredrdquo association 139
panels or both 140
The use of metabolic ratios as traits in GWAS has been useful for dealing with several 141
such calcitrant metabolites The approach which relies on biochemical pathways andor 142
represent relationships uncovered by a metabolic network correlation analysis has yielded 143
several significant associations even when the absolute levels of metabolites have not (Wentzell 144
et al 2007 Lipka 2013 Angelovici et al 2013 Gonzalez-Jorge et al 2013 Angelovici et al 145
2017) It has been postulated that metabolic ratios are less complex (since they only represent the 146
metabolite partitioning within biochemical pathways) and therefore are more tractable in 147
association mapping studies (Angelovici et al 2017) Still even this approach has failed to 148
identify QTLs for Gln in dry seeds (Angelovici et al 2017) 149
A different approach is clearly needed to uncover the genetic architecture of Gln 150
Notably the metabolic ratios used in previous studies do not represent all the potential ratios of 151
Gln-related traits since they were based principally on a priori pathway information which is 152
often incomplete 153
In theory performing a metabolic genome-wide association study (mGWAS) on all 154
possible Gln-related metabolic ratios would potentially resolve its genetic architecture In 155
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6
practice however such an endeavor would be challenging given the enormous number of 156
metabolic ratios that could be derived from the relationships between Gln and all 20 proteogenic 157
amino acids Therefore as a point of departure from previous studies we derived all possible 158
metabolic ratios of Gln only to its proteogenic amino acid family members thus theoretically 159
representing all potential biologically relevant partitioningrelationship of Gln within the Glu 160
family (Fig 1) By combining this approach with a Fixed and Random Model Circulating 161
Probability Unification (FarmCPU) which uses fixed and random effect models for powerful 162
and efficient GWAS studies (Liu et al 2016) we uncovered many significant QTLs for various 163
Gln-derived traits in dry seeds More importantly our analysis of the candidate genes revealed a 164
surprising enrichment for genes residing in the glucosinolate (GLS) biosynthesis pathway 165
suggesting a potential interplay between two metabolic pathways that are not known to be 166
directly linked (Fig 1) We validated this association by using an independent QTL mapping 167
approach as well as by characterizing Gln and other FAAs in mutant plants that have a disrupted 168
GLS composition and loading to the seeds Our data support an association between GLS natural 169
diversity and Gln levels and composition in seeds and also reveal that GLS loading to the seeds 170
has a profound effect on seed nitrogen and sulfur homeostasis as well as Gln levels and 171
composition Our results strongly suggest that an interaction between Gln and GLS plays a key 172
role in seed metabolic homeostasis 173
174
175
Results 176
177
The Four Glu Family Members Vary in Abundance Relative Composition and Broad-178
Sense Heritability Across the Arabidopsis Diversity Panel 179
In a previous study we quantified and described the natural variation of 18 out of the 20 180
proteogenic FAAs (excluding cysteine and asparagine) measured from dry seeds of three 181
biological repeats of a 313-accession Arabidopsis diversity panel (Angelovici et al 2013 182
Angelovici et al 2016) In the current study we used that data to assess the natural variation 183
among only the proteogenic FAAs in the Glu family ie Glu Pro Gln and Arg 184
Our analysis showed that the four Glu family members vary in abundance relative 185
composition and broad-sense heritability (Supplemental Table S1A) Glu was the most abundant 186
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7
amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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8
(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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10
SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
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Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
4
Introduction 94
95
Glutamine (Gln) is a free amino acid (FAA) that belongs to the glutamate family which also 96
includes glutamate (Glu) gamma-aminobutyric acid (GABA) proline (Pro) and arginine (Arg) 97
(Skokut et al 1978 Majumdar et al 2016 Okumoto et al 2016) This amino acid family plays 98
a key role in plant cell core metabolism by providing an entry point for inorganic nitrogen 99
Briefly ammonium derived from nitrate or absorbed directly from the soil can be assimilated 100
into Gln via the glutamine synthase (GS)glutamine oxoglutarate aminotransferase (GOGAT) 101
cycle (Lea and Miflin 1974) GSGOGAT is the primary nitrogen assimilation pathway in plants 102
(Ireland 1999) and is involved in the remobilization of nitrogenous compounds and the 103
assimilation of large amounts of ammonium generated by photorespiration in C3 plants (Foyer et 104
al 2009) 105
Gln plays an important role in seed metabolism as one of the main nitrogen carriers it is 106
transported via the xylem and phloem to sink tissues including developing seeds (Zhang et al 107
2010 Zhang et al 2015 Besnard et al 2016) A study of maturing Brassica napus seeds 108
showed that embryos import nitrogen in the form of amino acids (mainly Gln and alanine) to 109
synthesize other amino acids via transaminationdeamination reactions and then incorporation 110
into seed storage proteins (SSP) (Schwender et al 2006) Consistently studies in Arabidopsis 111
have shown that Gln levels are highly elevated prior to the onset of SSP synthesis (Baud et al 112
2002 Fait et al 2006) and then drop substantially during seed maturation (Fait et al 2006) 113
Even though the majority of seed Gln comes from transport several glutamine synthase 114
isozymes are expressed during seed development in the micropillar chalaza embryo and seed 115
coat which suggests that Gln is also actively synthesized in seeds (Winter et al 2007) The 116
content of Gln in dry seeds therefore may be the result of a balance between its incorporation 117
into SSP active synthesis and degradation However its composition may also reflect the 118
environmental conditions encountered by the maternal plant High levels of Gln have been 119
reported in Arabidopsis plants facing sulfur deprivation (Nikiforova et al 2006) and in tobacco 120
plants grown under high nitrogen conditions (Geiger et al 1999) whereas low levels of Gln 121
have been reported in Arabidopsis seedlings grown under nitrate-deficit conditions (Scheible et 122
al 2004) Interestingly extensive variation in free Gln content in dry Arabidopsis seeds has 123
been reported across the various accessions belonging to the Arabidopsis diversity panel 124
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5
(Angelovici et al 2017) but the genetic architecture regulating this trait remains poorly 125
understood Knowledge regarding the genes that underlie Gln levels composition and seed 126
partitioning would shed light on its potential seed-specific functions its interaction with other 127
biological processes and its role in downstream metabolism 128
In recent years genome-wide association studies (GWAS) as well as quantitative trait 129
loci (QTL) mapping experiments have facilitated the identification of many loci for both primary 130
and secondary metabolites (Wentzell et al 2007 Chan et al 2011 Riedelsheimer et al 2012 131
Angelovici et al 2013 Gonzalez-Jorge et al 2013 Chen et al 2014 Verslues et al 2014 132
Angelovici et al 2017) In-depth analyses of these QTLs have facilitated the further discovery 133
of key structural and regulatory genes that underlie the natural variation of metabolic traits and 134
the identification of various cellular processes involved in metabolic homeostasis Although 135
GWAS and QTL mapping have been conducted on FAAs in both vegetative and seed tissues 136
across several species no major QTLs have been identified for Gln (Riedelsheimer et al 2012 137
Chen et al 2014 Wen et al 2014) The lack of any identifiable loci implies that Gln either has 138
a complex genetic architecture or that these studies possibly utilized ldquounderpoweredrdquo association 139
panels or both 140
The use of metabolic ratios as traits in GWAS has been useful for dealing with several 141
such calcitrant metabolites The approach which relies on biochemical pathways andor 142
represent relationships uncovered by a metabolic network correlation analysis has yielded 143
several significant associations even when the absolute levels of metabolites have not (Wentzell 144
et al 2007 Lipka 2013 Angelovici et al 2013 Gonzalez-Jorge et al 2013 Angelovici et al 145
2017) It has been postulated that metabolic ratios are less complex (since they only represent the 146
metabolite partitioning within biochemical pathways) and therefore are more tractable in 147
association mapping studies (Angelovici et al 2017) Still even this approach has failed to 148
identify QTLs for Gln in dry seeds (Angelovici et al 2017) 149
A different approach is clearly needed to uncover the genetic architecture of Gln 150
Notably the metabolic ratios used in previous studies do not represent all the potential ratios of 151
Gln-related traits since they were based principally on a priori pathway information which is 152
often incomplete 153
In theory performing a metabolic genome-wide association study (mGWAS) on all 154
possible Gln-related metabolic ratios would potentially resolve its genetic architecture In 155
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6
practice however such an endeavor would be challenging given the enormous number of 156
metabolic ratios that could be derived from the relationships between Gln and all 20 proteogenic 157
amino acids Therefore as a point of departure from previous studies we derived all possible 158
metabolic ratios of Gln only to its proteogenic amino acid family members thus theoretically 159
representing all potential biologically relevant partitioningrelationship of Gln within the Glu 160
family (Fig 1) By combining this approach with a Fixed and Random Model Circulating 161
Probability Unification (FarmCPU) which uses fixed and random effect models for powerful 162
and efficient GWAS studies (Liu et al 2016) we uncovered many significant QTLs for various 163
Gln-derived traits in dry seeds More importantly our analysis of the candidate genes revealed a 164
surprising enrichment for genes residing in the glucosinolate (GLS) biosynthesis pathway 165
suggesting a potential interplay between two metabolic pathways that are not known to be 166
directly linked (Fig 1) We validated this association by using an independent QTL mapping 167
approach as well as by characterizing Gln and other FAAs in mutant plants that have a disrupted 168
GLS composition and loading to the seeds Our data support an association between GLS natural 169
diversity and Gln levels and composition in seeds and also reveal that GLS loading to the seeds 170
has a profound effect on seed nitrogen and sulfur homeostasis as well as Gln levels and 171
composition Our results strongly suggest that an interaction between Gln and GLS plays a key 172
role in seed metabolic homeostasis 173
174
175
Results 176
177
The Four Glu Family Members Vary in Abundance Relative Composition and Broad-178
Sense Heritability Across the Arabidopsis Diversity Panel 179
In a previous study we quantified and described the natural variation of 18 out of the 20 180
proteogenic FAAs (excluding cysteine and asparagine) measured from dry seeds of three 181
biological repeats of a 313-accession Arabidopsis diversity panel (Angelovici et al 2013 182
Angelovici et al 2016) In the current study we used that data to assess the natural variation 183
among only the proteogenic FAAs in the Glu family ie Glu Pro Gln and Arg 184
Our analysis showed that the four Glu family members vary in abundance relative 185
composition and broad-sense heritability (Supplemental Table S1A) Glu was the most abundant 186
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7
amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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8
(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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10
SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
5
(Angelovici et al 2017) but the genetic architecture regulating this trait remains poorly 125
understood Knowledge regarding the genes that underlie Gln levels composition and seed 126
partitioning would shed light on its potential seed-specific functions its interaction with other 127
biological processes and its role in downstream metabolism 128
In recent years genome-wide association studies (GWAS) as well as quantitative trait 129
loci (QTL) mapping experiments have facilitated the identification of many loci for both primary 130
and secondary metabolites (Wentzell et al 2007 Chan et al 2011 Riedelsheimer et al 2012 131
Angelovici et al 2013 Gonzalez-Jorge et al 2013 Chen et al 2014 Verslues et al 2014 132
Angelovici et al 2017) In-depth analyses of these QTLs have facilitated the further discovery 133
of key structural and regulatory genes that underlie the natural variation of metabolic traits and 134
the identification of various cellular processes involved in metabolic homeostasis Although 135
GWAS and QTL mapping have been conducted on FAAs in both vegetative and seed tissues 136
across several species no major QTLs have been identified for Gln (Riedelsheimer et al 2012 137
Chen et al 2014 Wen et al 2014) The lack of any identifiable loci implies that Gln either has 138
a complex genetic architecture or that these studies possibly utilized ldquounderpoweredrdquo association 139
panels or both 140
The use of metabolic ratios as traits in GWAS has been useful for dealing with several 141
such calcitrant metabolites The approach which relies on biochemical pathways andor 142
represent relationships uncovered by a metabolic network correlation analysis has yielded 143
several significant associations even when the absolute levels of metabolites have not (Wentzell 144
et al 2007 Lipka 2013 Angelovici et al 2013 Gonzalez-Jorge et al 2013 Angelovici et al 145
2017) It has been postulated that metabolic ratios are less complex (since they only represent the 146
metabolite partitioning within biochemical pathways) and therefore are more tractable in 147
association mapping studies (Angelovici et al 2017) Still even this approach has failed to 148
identify QTLs for Gln in dry seeds (Angelovici et al 2017) 149
A different approach is clearly needed to uncover the genetic architecture of Gln 150
Notably the metabolic ratios used in previous studies do not represent all the potential ratios of 151
Gln-related traits since they were based principally on a priori pathway information which is 152
often incomplete 153
In theory performing a metabolic genome-wide association study (mGWAS) on all 154
possible Gln-related metabolic ratios would potentially resolve its genetic architecture In 155
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6
practice however such an endeavor would be challenging given the enormous number of 156
metabolic ratios that could be derived from the relationships between Gln and all 20 proteogenic 157
amino acids Therefore as a point of departure from previous studies we derived all possible 158
metabolic ratios of Gln only to its proteogenic amino acid family members thus theoretically 159
representing all potential biologically relevant partitioningrelationship of Gln within the Glu 160
family (Fig 1) By combining this approach with a Fixed and Random Model Circulating 161
Probability Unification (FarmCPU) which uses fixed and random effect models for powerful 162
and efficient GWAS studies (Liu et al 2016) we uncovered many significant QTLs for various 163
Gln-derived traits in dry seeds More importantly our analysis of the candidate genes revealed a 164
surprising enrichment for genes residing in the glucosinolate (GLS) biosynthesis pathway 165
suggesting a potential interplay between two metabolic pathways that are not known to be 166
directly linked (Fig 1) We validated this association by using an independent QTL mapping 167
approach as well as by characterizing Gln and other FAAs in mutant plants that have a disrupted 168
GLS composition and loading to the seeds Our data support an association between GLS natural 169
diversity and Gln levels and composition in seeds and also reveal that GLS loading to the seeds 170
has a profound effect on seed nitrogen and sulfur homeostasis as well as Gln levels and 171
composition Our results strongly suggest that an interaction between Gln and GLS plays a key 172
role in seed metabolic homeostasis 173
174
175
Results 176
177
The Four Glu Family Members Vary in Abundance Relative Composition and Broad-178
Sense Heritability Across the Arabidopsis Diversity Panel 179
In a previous study we quantified and described the natural variation of 18 out of the 20 180
proteogenic FAAs (excluding cysteine and asparagine) measured from dry seeds of three 181
biological repeats of a 313-accession Arabidopsis diversity panel (Angelovici et al 2013 182
Angelovici et al 2016) In the current study we used that data to assess the natural variation 183
among only the proteogenic FAAs in the Glu family ie Glu Pro Gln and Arg 184
Our analysis showed that the four Glu family members vary in abundance relative 185
composition and broad-sense heritability (Supplemental Table S1A) Glu was the most abundant 186
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7
amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
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34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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6
practice however such an endeavor would be challenging given the enormous number of 156
metabolic ratios that could be derived from the relationships between Gln and all 20 proteogenic 157
amino acids Therefore as a point of departure from previous studies we derived all possible 158
metabolic ratios of Gln only to its proteogenic amino acid family members thus theoretically 159
representing all potential biologically relevant partitioningrelationship of Gln within the Glu 160
family (Fig 1) By combining this approach with a Fixed and Random Model Circulating 161
Probability Unification (FarmCPU) which uses fixed and random effect models for powerful 162
and efficient GWAS studies (Liu et al 2016) we uncovered many significant QTLs for various 163
Gln-derived traits in dry seeds More importantly our analysis of the candidate genes revealed a 164
surprising enrichment for genes residing in the glucosinolate (GLS) biosynthesis pathway 165
suggesting a potential interplay between two metabolic pathways that are not known to be 166
directly linked (Fig 1) We validated this association by using an independent QTL mapping 167
approach as well as by characterizing Gln and other FAAs in mutant plants that have a disrupted 168
GLS composition and loading to the seeds Our data support an association between GLS natural 169
diversity and Gln levels and composition in seeds and also reveal that GLS loading to the seeds 170
has a profound effect on seed nitrogen and sulfur homeostasis as well as Gln levels and 171
composition Our results strongly suggest that an interaction between Gln and GLS plays a key 172
role in seed metabolic homeostasis 173
174
175
Results 176
177
The Four Glu Family Members Vary in Abundance Relative Composition and Broad-178
Sense Heritability Across the Arabidopsis Diversity Panel 179
In a previous study we quantified and described the natural variation of 18 out of the 20 180
proteogenic FAAs (excluding cysteine and asparagine) measured from dry seeds of three 181
biological repeats of a 313-accession Arabidopsis diversity panel (Angelovici et al 2013 182
Angelovici et al 2016) In the current study we used that data to assess the natural variation 183
among only the proteogenic FAAs in the Glu family ie Glu Pro Gln and Arg 184
Our analysis showed that the four Glu family members vary in abundance relative 185
composition and broad-sense heritability (Supplemental Table S1A) Glu was the most abundant 186
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7
amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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8
(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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10
SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
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Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
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7
amino acid with a relative composition mean of 035 whereas Gln was the least abundant with a 187
relative composition mean of 0015 We defined relative composition as the ratio of an individual 188
amino acid to the sum of the 18 measured amino acids (eg GlnTotal GluTotal) Arg and Pro 189
had a relative composition means (ArgTotal ProTotal) of 004 and 0017 respectively Gln 190
demonstrated moderate heritability (052) along with Pro and Glu (048 and 063 respectively) 191
whereas Arg had the highest heritability (074) Interestingly Gln had the largest relative 192
standard deviation whereas Glu had the smallest despite its high abundance (~61 and 23 193
RSD respectively) 194
To evaluate the relationship between Gln and the other Glu family members we 195
performed a correlation-based network analysis among the four FAAs and visualized the results 196
using Cytoscape version 361 (Supplemental Fig S1) All correlations (r) were significant at = 197
0001 and ranged from 012 to 054 Gln was moderately correlated with Arg and Glu and 198
weakly correlated with Pro which had a significant but weak correlation with all Glu family 199
members 200
201
mGWAS Identified Significant SNP-Trait Associations for Six Gln-related traits 202
In our previous study no significant associations were identified when seed Gln traits or any 203
Gln-related traits derived from a priori knowledge of the Glu metabolic pathway or correlation-204
based network analysis were used for the mGWAS (Angelovici et al 2017) Therefore we took 205
a slightly different approach in this study by using all possible Gln metabolic ratios that could be 206
derived from Gln relationships with the other members of the glutamate family The various 207
relationships were represented by calculating all the possible ratios in which Gln is the numerator 208
and is divided by a sum of every combination of the four Glu family members including Gln 209
itself ie Gln(Gln|Arg|Pro|Gu) | = (and or) We consider this a semi-combinatorial approach 210
since it relies on both a priori knowledge of the Glu family as well as all the possible 211
combinations of the Glu family FAAs in the denominator The traits and their corresponding 212
means ranges and broad-sense heritability scores are listed in Supplemental Table S1B For 213
simplicity we used a one letter code in our trait representations The sum of the FAA in the 214
denominator of each trait is represented by a string of one letter codes For example QEP is Gln 215
divided by the sum of Glu and Pro This approach yielded 16 Gln-related traits 14 ratio-based 216
traits (Supplemental Table S1B) one free Gln absolute level and the Gln relative composition 217
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(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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37
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Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
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Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
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Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
8
(GlnTotal) (Supplemental Table S1A) Of all these 16 traits QQP had the highest heritability 218
(053) and QRP had the lowest (035) In general the derived traits had low to moderate 219
heritability 220
We used the FarmCPU package in R (version 102) (Liu et al 2016) to perform an 221
mGWAS on the 16 Gln-related traits Since FarmCPU may be prone to a type I error we chose 222
to use the more conservative Bonferroni multiple testing correction procedure instead of the 223
Benjamini-Hochberg (1995) false discovery rate-controlling procedure We also considered 224
SNP-trait associations significant only at an = 001 Bonferroni correction level At this 225
significance threshold we identified 21 SNPndashtrait associations for six traits QP QR QQP 226
QRP QRQ and QRQP (Fig 2 Supplemental Dataset S1) only 16 SNPs were identified from 227
the 21 signals None of the six traits included Glu in their denominator but did include either Arg 228
or Pro or both The heritability of these six traits ranged from low to moderate (035ndash053) 229
(Supplemental Table S1B) No significant associations were observed on chromosome 1 One 230
was observed on chromosome 2 and three on chromosome 3 The majority of significant SNPs 231
were identified on either chromosome 4 or 5 (Fig 2 Supplemental Dataset S1) The five SNPs 232
with the lowest p-values were located on chromosomes 4 or 5 (Table 1) three of these SNPs fell 233
within a gene whereas the remaining two were located in a transposable element and an 234
intragenic region The three genes are annotated as encoding Brassinosteroid suppressor 1 235
(BSU1) a MATE efflux family protein and methylthioalkylmalate synthase 1 (MAM1) 236
237
Genes Within Haploblocks Spanning Significant SNPs Are Enriched for Glucosinolate 238
Biosynthetic Process 239
We compiled a candidate gene list based first on genes that contain a significant SNP We then 240
expanded the list to include those genes that are in strong linkage disequilibrium (LD defined as 241
regions with non-random associations calculated using a 95 confidence bounds on D prime) 242
with the significant SNPs identified by our mGWAS since significant SNPs identified by 243
GWAS may tag causal variants in neighboring genes that are in LD (Atwell et al 2010) To that 244
end we identified haploblocks that spanned the 16 SNPs using Haploview version 42 (See 245
Materials and Methods) (Barrett et al 2004) and considered all spanned genes as candidates If a 246
haploblock was not identified for a given SNP and did not fall within a gene then the gene 247
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9
directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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10
SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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directly upstream or downstream was recorded Overall we found 27 unique genes The entire 248
list of genes associated with all 16 SNPs is summarized in Supplemental Table S2A 249
Next we used agriGO (httpbioinfocaueducnagriGO) to perform a GO enrichment 250
analysis of the 27 genes We analyzed all genes identified across the six traits since collectively 251
they represent the potential genetic architecture of the Gln partition within the Glu family and its 252
relationships to the other members The analysis revealed a significant enrichment for the 253
following terms secondary metabolic process carbohydrate metabolic process sulfur metabolic 254
process S-glycoside biosynthetic process and glucosinolates biosynthetic process (Supplemental 255
Table S2B) 256
All the significant enrichment terms resulted from three genes MAM1 (AT5G23010) 257
AOP1 (AT4G03070) and AOP3 (AT4G03050) all of which are annotated as involved in the 258
biosynthesis of aliphatic GLS Notably one of our top five significant SNPs fell within MAM1 259
(QP) (Table 1) AOP1 was associated with traits QRQ and QRQP and AOP3 was associated 260
with trait QRQ (Fig 2 Supplemental Dataset S1) Although these genes are located in three 261
different haploblocks AOP1 and AOP3 are in very close proximity within the genome the end 262
of AOP3 and the beginning of AOP1 are 11831 base pairs apart (Fig 3) The three genes are 263
located in two well-characterized QTLs GS-ELONG and GS-AOP (Fig 3 and Fig 4) The GS-264
ELONG locus controls variation in the side-chain length of aliphatic GLS and is characterized by 265
three genes MAM1 MAM2 and MAM3 (previously MAM-L) (Kroymann et al 2001 Kroymann 266
et al 2003) GS-AOP is the collective name of two tightly linked loci GS-ALK and GS-OHP 267
and controls GLS side-chain modifications (Kliebenstein et al 2001) The GS-AOP locus 268
represents the branching point in the biosynthesis of aliphatic GLS that includes two 2-269
oxoglutarate dependent dioxygenases AOP2 localized in the GS-ALK locus and AOP3 270
localized in the GS-OHP locus The presenceabsence of genes in the GS-AOP and GS-ELONG 271
loci account for much of the natural variation in aliphatic GLS profiles in Arabidopsis (Fig 1) 272
Thus despite having significant SNPs directly associated with MAM1 AOP1 and AOP3 273
because of the high degree of LD in these regions MAM2 MAM3 and AOP2 are also putative 274
genes of interest 275
We next asked whether the three significant SNPs (ie S127050 S127076 S175365) 276
identified in the two GLS-related QTLs tagged the additional GLS genes in the GS-ELONG and 277
GS-AOP regions To that end we performed a pairwise LD analysis between the three identified 278
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SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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37
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38
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Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
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Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
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10
SNPs and the SNPs +-5 kb to either side of the first and last MAM or AOP genes in the GS-279
ELONG and GS-AOP regions (ie flanking the regions) respectively (Supplemental Fig S2 and 280
Supplemental Fig S3) SNP S127076 which resides within the BSU1 gene but is located within 281
the haploblock containing AOP1 is in high LD with AOP1 (S127071 and S127075 r2 = 0934 282
and 0934) as well as with the SNPs residing in both AOP2 (S127058 r2 = 0918) and AOP3 283
(S127048 S127050 and S127050 r2 = 0902 0918 and 0918 respectively) The high LD with 284
neighboring SNPs suggests that this SNP may tag a causal variation in one or both of these AOP 285
genes (Supplemental Fig S2A) Similarly SNP S127050 which resides in the same haploblock 286
as AOP3 is in perfect LD with a SNP from AOP2 (S127058 r2 = 1) and in high LD with SNPs 287
in AOP1 (S127071 S127075 and S127076 r2 = 0983 0983 and 0918 respectively) which 288
suggests that this SNP may tag the additional AOP genes in the region (Supplemental Fig S2B) 289
Finally SNP S175365 which resides in the same haploblock as MAM1 is in strong to moderate 290
LD with SNPs associated with MAM2 (S175355 r2 = 0908) and MAM3 (S175394 r
2 = 0649) 291
(Supplemental Fig S3) 292
Overall we found six genes involved in aliphatic GLS biosynthesis that are in moderate 293
(gt 05) to strong (gt 08) LD with three of significant SNPs in the region It is likely that either 294
one or an allelic combination of all six genes contributes to the natural variation of free Gln and 295
its related traits in dry seeds 296
297
QTL Analysis of the Bayreuth-0 and Shahdara Mapping Population Supports the GWAS 298
Finding 299
The finding of an association between Gln and GLS in dry seeds was surprising Glucosinolates 300
are not synthesized in seeds but rather are transported to the seed from the maternal plant 301
(Magrath and Mithen 1993) Therefore to independently confirm our results from the mGWAS 302
and to further support the association between Gln and the two GLS-related QTLs we performed 303
a biparental QTL mapping using the Bayreuth-0 (Bay) and Shahdara (Sha) recombinant inbred 304
population (Loudet et al 2002) Previous work has shown that Bay and Sha segregate at the GS-305
ELONG and GS-AOP loci and have an epistatic relationship (Kliebenstein et al 2001 306
Kroymann et al 2003 Textor et al 2004 Kliebenstein et al 2007 Wentzell et al 2007) We 307
hypothesized that if these GLS-related QTLs are indeed responsible for the natural variation of 308
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
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Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
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1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
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11
Gln in dry seeds then the Bay x Sha mapping population should recapitulate the QTL for the 309
Gln-related traits 310
To test this hypothesis we used the FAA quantifications from 158 recombinant inbred 311
lines of the Bay x Sha population as described previously (Angelovici et al 2013 Angelovici et 312
al 2017) and performed a QTL analysis of our 16 Gln-related traits using Multiple QTL 313
Mapping (MQM) in the Rqtl2 package in R (Arends et al 2010) This approach yielded a total 314
of 25 QTLs for eight traits (for the full list see Supplemental Dataset S2) Six traits had 315
significant LOD maxima on chromosome 5 at marker MSAT514 (position 7498509 bp) QRQ 316
QRQP QR QRP QQP and QP The supporting interval overlapped with the GS-ELONG 317
locus (Table 2) Both the highest percent of total phenotypic variation and the highest LOD were 318
observed for QQP and QP These two traits also had a LOD maxima on chromosome 4 at 319
marker MSAT443 with supporting intervals spanning the GS-AOP locus 320
Interaction between the two QTLs has been observed previously in GLS traits 321
(Kliebenstein Lambrix et al 2001 Kliebenstein et al 2007) Therefore we tested whether 322
interactions between the two loci existed for our Gln-related traits Visual inspection of the 323
interaction plots between markers MSAT443 and MSAT514 clearly indicated interaction 324
between these markers that seem to heavily influence the QQP and QP trait means 325
(Supplemental Fig S4) 326
327
The Presence or Absence of Specific GLS Has a Significant Effect on the Levels of the Gln-328
Related Traits in Dry Seeds 329
To further validate the association between GLS natural variation and the Gln-related traits we 330
grew 133 accessions from the Arabidopsis diversity panel and measured both FAA and GLS 331
levels in the dry seeds (Supplemental Dataset S3) Next we tested whether the presence or 332
absence of one of the four GLS which result from the different allelic combinations at the GS-333
ELONG and GS-AOP loci (Fig 1) were associated with high or low levels of our traits of 334
interest (ie the 16 Gln-related traits analyzed in our mGWAS) The four GLS analyzed for 335
presenceabscence were 3ohp (requiring the presence of MAM2 and AOP3) 2-propenyl 336
(requiring the presence of MAM2 and AOP2) 4ohb (requiring the presence of MAM1 and 337
AOP3) and 3butenylOH-3-butenyl (requiring the presence of MAM1 and AOP2) To evaluate 338
this association we performed t-tests on the levels of the Gln-related traits measured from 339
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accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
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Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
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Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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12
accessions that either had a specific GLS chemotype (ie 3ohp or 4ohb) or completely lacked it 340
(see Materials and Methods for more details regarding the statistical analysis) 341
Our results showed that Gln absolute levels were significantly less in the presence of 2-propenyl 342
(Supplemental Table S3) However the presenceabsence of both 3ohp and 4ohb had the most 343
significant effect on our traits The presence of 3ohp had a negative effect on most of the Gln-344
related ratios and had a positive effect on the absolute levels of Arg Glu and Pro By contrast 345
the presence of 4ohb had the opposite effect on most of the Gln-related traits in addition to the 346
absolute levels of Glu and Pro (Supplemental Table S3) Taken collectively these results both 347
confirm that GLS diversity can significantly affect the Gln-related traits and further supports the 348
association between these two pathways 349
350
FAA Characterization of Mutants in GLS Genes Present in the GS-ELONG and GS-AOP 351
Showed Only Small Effects on Gln-Related Traits in the Col-0 Background 352
We performed a transgenic approach to further confirm the association between aliphatic GLS 353
and Gln content in dry Arabidopsis seeds We obtained null and overexpression (OX) mutants of 354
the six relevant genes located in the GS-ELONG or GS-AOP locus and involved in aliphatic GLS 355
biosynthesis All plants were grown to maturity and their dry seeds harvested and analyzed for 356
FAA content and composition We also obtained and quantified the dry seed FAA content of a 357
bsu1 null mutant which lacks the BSU1 genes that contain the significant SNP (ie S127076) 358
identified for traits QRP and QRQP (Fig 4 Table 1) The T-DNA insertion lines were ordered 359
from the SALK and WISC T-DNA collections and included insertions in the AT4G03070 360
(aop1) AT4G03050 (aop3) AT5G23020 (mam3) and AT4G03080 (bsu1) genes The T-DNA 361
insertion locations are summarized in Supplemental Fig S5 Null homozygous mutants were 362
isolated and confirmed by the absence of the full transcript in a tissue of high expression 363
(Supplemental Fig S5 and Supplemental Fig S6) Based on the eFP browser expression data 364
(Schmid et al 2005 Winter et al 2007) AOP1 expression was evaluated in imbibed seeds 365
AOP3 was evaluated in young siliques MAM1 and MAM3 were evaluated in seedlings and 366
BSU1 was evaluated in leaves The RT-PCR primers used are listed in Supplemental Table S4 367
Interestingly all genes excluding AOP2 showed some transcript expression during seed 368
development despite a lack of GLS synthesis at the seed level MAM2 does not exist in the 369
Columbia-0 (Col-0) ecotype and does not have any publicly available expression profiles 370
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13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
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Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
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Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
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Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
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Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
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Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
13
In addition to null mutants we also obtained mutants with altered GLS composition in 371
the Col-0 background These mutants included gsm1 which accumulates C3 GLS and has large 372
reductions in 4-methyl sulfinylbutyl and 6-methylsulfinyl glucosinolates (Haughn et al 1991 373
Kroymann et al 2001) Since the Col-0 accession does not contain MAM2 and has a truncated 374
non-functional AOP2 protein (Kroymann et al 2001 Wentzell et al 2007 Jensen et al 2015) 375
we also analyzed a previously characterized AOP2 overexpression mutant in the Col-0 376
background that accumulates alkene GLS (Rohr et al 2009 Burow et al 2015) Collectively 377
these mutants represent some of the potential GLS composition alterations that can occur in the 378
Col-0 background The ability of any single gene mutant to capture the diversity of GLS is 379
limited since it arises from a complex allelic combination (Kliebenstein et al 2001) 380
We quantified the dry seed FAA for each of these single gene mutants and then assessed 381
the fold change (FC) as compared to its respective WT control (Col-0 or Col-3) for 16 Gln-382
related traits (Supplemental Dataset S4A) Gln absolute levels in the aop1 aop3 and AOP2-OX 383
mutants did not change significantly An elevated amount of Arg in the aop3 mutant led to 384
reductions in two Gln-related traits QR and QRQ (054 and 075 FC respectively Fig 5 385
Supplemental Table S5A Supplemental Dataset S4B) In addition Glu and Pro were reduced in 386
the AOP2-OX mutant but did not lead to any significant changes in the Gln-related ratios (Fig 387
5B Supplemental Table S5B) The bsu1 mutant had significantly high levels of Arg and Glu (a 388
162 and 143 FC respectively) but the levels of Gln and related ratios were unchanged (Fig 5 389
Supplemental Table S5B) The FAA quantifications of the AOP-related mutants showed that in 390
addition to minor alterations in the Glu family FAAs few other FAAs changed significantly 391
(Fig 5A Supplemental Table 5B) Our analysis of the MAM-related mutants showed that levels 392
of Gln Glu and Pro were slightly elevated (a 139 119 and 135 FC respectively) in the gsm1 393
mutant which led to slight increases in nine traits Gln related ratios (Fig 5B Supplemental 394
Table S5) In sum the single gene mutants showed only a small effect of the altered GLS 395
composition on the Gln-related traits 396
397
Elimination of Aliphatic GLS Triggers a Strong Seed-Specific Increase in Free Gln 398
To further characterize the association between aliphatic GLS and the Gln-related traits we 399
quantified the absolute levels of each FAA in the dry seeds of three null mutants (myb2829 400
myb3451 and grt12) with altered GLS compositions and the Col-0 ecotype The log2 of the 401
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
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Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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38
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Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
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Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
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Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
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Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
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Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
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Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
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14
average FC defined as the ratios between individual amino acid levels in the mutants and their 402
levels in their respective controls were calculated and used to create heat maps of the FAAs (Fig 403
6 Supplemental Dataset S4) The myb2829 double knockout mutant is a null mutant of two 404
transcription factors that regulate the aliphatic GLS in Arabidopsis MYB28 (AT5G61420) and 405
MYB29 (AT5G07690) This double knockout eliminates all aliphatic GLS from the entire plant 406
including the seed (Sonderby et al 2007) A double knockout of GTR1 (AT3G47960) and GTR2 407
(AT5G62680) resulting in the gtr12 mutant abolishes the transport of all GLS to the seeds 408
(Nour-Eldin et al 2012) Finally a double knockout of the two transcription factors MYB51 409
(AT1G18570) and MYB34 (AT5G60890) resulting in the myb3451 mutant eliminates the 410
indole GLS from the entire plant (Frerigmann and Gigolashvili 2014) 411
The FAA analysis revealed that Gln levels were significantly higher in the myb2829 and 412
gtr12 mutants but not in the myb3451 mutant as compared to Col-0 (Fig 6 Supplemental 413
Table S5A Supplemental Dataset S4A) In fact Gln showed the most pronounced FC among all 414
FAAs measured a 97 FC in the myb2829 mutant and a 598 FC in the gtr12 mutant (Fig 6 415
Supplemental Table S5A B) In addition to Gln three other Glu family members increased 416
significantly in the myb2829 and gtr12 mutants a 351 and 645 FC for Arg a 33 and 47 FC 417
for Glu and a 13 and 4 FC for Pro respectively (Supplemental Table S5A B) Alterations in 418
these Glu family FAAs led to significant FC increases in all Gln-related ratios ranging from a 419
15ndash19 FC in QRQ and a 763 and 1507 FC in QP in the myb2829 and gtr12 mutants 420
respectively (Fig 6B Supplemental Table S5A) In the myb2829 and gtr12 mutants we also 421
observed increases in Asn (1040 and 987 FC respectively) and His (878 and 4728 FC 422
respectively) Glu and Asp also showed a consistent elevation (~3ndash5 FC) in both mutants (Fig 423
6A Supplemental Table S5B) The total sum of the FAAs (TFAA) measured also increased 424
significantly in both myb2829 and gtr12 by 473 and 1258 respectively (Supplemental Table 425
S5B) 426
Since TFAA changed in both mutants we also calculated the percent of each FAA to the 427
sum of the TFAA measured in all genotypes including Col-0 (Supplemental Dataset S4C 428
Supplemental Table S5C) In both mutants the largest increase was in the relative composition 429
of Gln which increased from ~1 in Col-0 to 2282 in the myb2829 mutant and to 5310 in 430
the gtr12 mutant (Fig 6C Supplemental Table S5C) Arg and His were the only other FAAs 431
that consistently increased in both the myb2829 and gtr12 mutants from ~1 of the total FAA 432
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15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
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Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
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Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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38
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Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
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Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
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Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
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Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
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Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
15
in Col-0 to 882 and 610 respectively for Arg and to 244 and 495 respectively for 433
His The relative compositions of the remaining FAAs were consistently lower in both mutants 434
(excluding Asn which showed opposite trends in the two mutants) (Fig 6C Supplemental Table 435
S5C) The largest decreases were in the two most abundant FAAs in the Col-0 seeds Glu and 436
Gly which had relative abundances of 2881 and 1877 in Col-0 1994 and 1065 in 437
myb2829 and 666 and 283 in gtr12 respectively (Fig 6C Supplemental Table S5C) 438
Next we tested whether a reduction in GLS (rather than its complete elimination) would result in 439
significant alterations in Gln levels We quantified the dry seed FAA levels from the myb28 and 440
myb29 single mutants which have approximately half the seed GLS as the Col-0 ecotype 441
(Francisco et al 2016) The myb28 mutant had significant FCs only in Pro levels (a 123 FC 442
increase) (Supplemental Table S5A B) The myb29 mutant by contrast showed minor but 443
significant increases in both Gln absolute levels (155 FC) and relative composition (GlnTotal 444
126 FC) as well as FCs (17ndash147) in several Gln-related traits (ie QREP QE QP QRE 445
QQE QQP QEP QRQE QQEP QRQEP) in the myb29 mutant (Fig 6B Supplemental 446
Table S5A) Nevertheless levels of Asp Gly Leu and Phe were also elevated significantly in 447
this mutant with FCs of 123ndash142 (Fig 6A Supplemental Table S5B) Collectively this genetic 448
analysis indicated to us that Gln levels were extensively altered in response to a complete 449
absence of aliphatic GLS either in the plant or specifically in the seed 450
To evaluate if the response was seed specific we analyzed the FAA content in the rosette leaves 451
and stems of the myb2829 and gtr12 double mutants and the respective Col-0 control Tissues 452
were collected approximately 20 days after bolting in order to capture the metabolic steady state 453
of the FAA in these tissues during seed setting and filling Neither mutant had significant fold 454
changes in Gln levels in either its leaves or stems (Supplemental Dataset S5 Supplemental Table 455
S6) In contrast to the seeds we also found no elevation in TFAA (as explained above) in either 456
mutant The results support the genetic evidence that the elevated Gln levels in the mutant seeds 457
are occurring at the seed level rather than resulting from specific increases in the maternal tissue 458
459
460
461
462
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16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
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37
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38
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Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
16
463
Gln Levels Are Elevated During Early Seed Maturation in Both the myb2829 and the 464
gtr12 Mutants 465
During seed maturation FAAs (especially Gln) are incorporated into the SSPs especially during 466
seed fillingmaturation (Fait et al 2006) Hence we assessed whether Gln levels are elevated 467
during the early stages of seed development To do this we isolated developing seeds at 12 14 468
16 and 18 days after flowering (DAF) and at the dry seed stage from the myb2829 and gtr12 469
mutants and the Col-0 ecotype and analyzed the FC in FAA levels across these time points 470
(Supplemental Dataset S6) Our analysis indicated that as compared to the Col-0 control the 471
seeds from both mutants had substantial increases in Gln as early as 12 DAF (Fig 7 472
Supplemental Table S7) At 12 DAF there was a 24 FC increase of Gln in the myb2829 mutant 473
and a 37 FC increase in the gtr12 mutant (Supplemental Table S7) Gln levels were higher 474
across all the developmental time points in both mutants Although Gln levels in all genotypes 475
showed an overall reduction trend the FC observed in the mutants continued to increase as the 476
seed progressed to desiccation (Fig 7A B Supplemental Table S7) Gln absolute levels at all 477
time points exceeded the levels of any other amino acid (Supplemental Dataset S6) 478
Since the TFAA changed in both mutants we also evaluated the changes in FAA relative 479
composition as described above The relative composition of Gln dropped from 95 (12 DAF) 480
to ~111 (dry seed) in the Col-0 and dropped from ~541 (12 DAF) to 2282 (dry seed) in 481
the myb2829 mutant (Supplemental Table S7B) Surprisingly the Gln content in the gtr12 482
mutant remained between 5453 and 6140 throughout the entire seed maturation process 483
despite a drop in Gln absolute levels (Fig 7C Supplemental Table S7B) Hence Gln is only a 484
minor amino acid in Col-0 but the most abundant one in the mutants By contrast Glu is most 485
abundant in the seeds and its levels increased from 213 (12 DAF) to 288 (dry seed) in the 486
Col-0 remained constant at ~20 in the myb2829 mutant throughout development and 487
decreased from 139 (12 DAF) to 106 (dry seed) in the gtr12 mutant (Supplemental Table 488
S7B) Very pronounced changes were also recorded in the composition of Gly which had a 489
lower relative composition as compared to the Col-0 throughout seed development (Fig 7C 490
Supplemental Table S7) Notably at all seed developmental stages the FC never exceeded 2 for 491
Gly or 6 for Glu (Supplemental Table S7A) 492
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
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Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
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Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
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17
Collectively these results show that compositional alteration to FAAs in the 493
glucosinolate mutants occurs very early in seed maturation and persists in the dry seeds 494
495
Both Sulfur and Nitrogen Significantly Changed in Seeds that Lacked GLS 496
GLS are high in nitrogen and sulfur compounds A lack of GLS in seeds may cause a change in 497
their homeostasis which is known to have a substantial impact on Gln levels (Nikiforova et al 498
2005 Nikiforova et al 2006) To test this possibility we measured nitrogen carbon and sulfur 499
in the myb2829 and gtr12 mutants and in the Col-0 control (Table 3) 500
We found that as compared to Col-0 nitrogen was higher in both mutants (by 8 and 15 501
respectively) sulfur was significantly lower (by 79 and 90 respectively) and carbon was 502
unaltered (Table 3) Finally we assessed whether the elevated levels of Gln and other FAAs 503
reflected any changes in the levels or composition of proteins To do this we analyzed the 504
protein-bound amino acids (PBAA) in the dry seeds of the two mutants and in Col-0 The 505
analysis revealed no significant or consistent alterations in PBAA levels (Supplemental Dataset 506
S7 Supplemental Table S8) 507
508
Discussion 509
Genome-wide association studies have successfully uncovered many genes involved in the 510
natural variation and regulation of various metabolic traits including FAAs in seeds (Magrath 511
1994 Parkin et al 1994 Chan et al 2011 Angelovici et al 2013 Lipka et al 2013 512
Diepenbrock et al 2017) Yet none of these studies have identified any significant SNP 513
associations with free Gln in dry seeds The intractability of this trait would suggest that Gln has 514
a highly complex genetic architecture When faced with such complex metabolic traits some 515
researchers have enlisted metabolic ratios based on a priori knowledge or unbiased network 516
analysis an approach that has yielded additional QTLs that could not be retrieved using direct 517
measurements of the absolute traits (Angelovici et al 2013 Angelovici et al 2017 518
Diepenbrock et al 2017) Unfortunately for free Gln in seeds neither absolute measurements 519
nor specific metabolic ratios have resulted in significant associations 520
In this study we used a semi-combinatorial approach to formulate metabolic ratios as 521
traits in a mGWAS Unlike previous studies this approach yielded several novel SNP-trait 522
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18
associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
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34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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associations Interestingly we identified unique SNP-trait associations across the different Gln-523
related traits suggesting a slightly different genetic architecture for each metabolic ratio (Fig 2 524
Supplemental Dataset 1) Since all the traits represent the Gln partition or a relationship to the 525
other Glu family members we treated all the SNPs as contributing to one genetic architecture of 526
Gln metabolism This collective analysis enabled us to compile a comprehensive candidate gene 527
list that upon further analysis revealed a strong association between Gln and an unexpected 528
metabolic pathway the GLS biosynthesis We argue that this approach could help elucidate the 529
genetic basis of other complex metabolites and further reveal unexpected metabolic pathway 530
associations 531
532
Unexpected Association Between the Gln-Related Traits and the Aliphatic GLS Natural 533
Diversity is Supported by Multiple Independent Lines of Evidence 534
Our semi-combinatorial mGWAS analysis revealed that the natural variation of the Gln-related 535
traits measured from dry seeds is strongly associated with natural variation of aliphatic GLS Not 536
only did we identify an enrichment of GLS biosynthesis genes in our collective candidate gene 537
list but we also identified two aliphatic GLS biosynthetic genes in our top significant SNP-trait 538
associations analysis (Table 1 Supplemental Table 2B) This association is surprising because 539
GLS biosynthesis has three main steps (chain elongation of either methionine branched chain or 540
aromatic amino acids core structure formation secondary modifications Kliebenstein et al 541
2001) none of which involve Gln In general GLS are nitrogen- and sulfur-containing 542
compounds that likely evolved from cyanogen glucosides but are largely limited to the 543
Brassicales (Halkier and Gershenzon 2006) Their breakdown products display a variety of 544
biological activities explaining their defensive roles (Johnson et al 2009) Although GLS 545
accumulate to very high levels in seeds they are synthesized in the vegetative tissue and 546
transported from the maternal plant to the seed (Magrath and Mithen 1993) Nevertheless our 547
study provides multiple lines of evidence confirming an association between the natural variation 548
of Gln-related traits and the natural diversity of aliphatic GLS Firstly it is important to note that 549
the three significant SNPs associated with aliphatic GLS fell within two well characterized 550
QTLs the GS-ELONG and the GS-AOP (Magrath 1994) Previous studies have shown that the 551
presence and absence of five genes within these QTLs account for much of the diversity in the 552
aliphatic GLS profile in Arabidopsis These genes are MAM1ndash3 AOP2 and AOP3 (Halkier and 553
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
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Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
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Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
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Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
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Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
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19
Gershenzon 2006) Pairwise LD analysis of the three significant SNPs identified in these two 554
regions revealed that these SNPs are likely tagging all five genes within these two key QTLs 555
(Supplemental Fig S2 and Supplemental Fig S3) Secondly an independent QTL mapping of 556
the Gln-related traits measured from the BaySha mapping population (which segregates for 557
these two key QTLs (Wentzell et al 2007) also identified significant associations of both GS-558
ELONG and GS-AOP loci with several Gln-related traits (Table 2 Supplemental Dataset 2) 559
Lastly the presenceabsence of various chemotypes arising from different allelic combinations 560
of the MAM and AOP genes (Fig 1) resulted in significantly different levels in the Gln-related 561
traits (Supplemental Table S3) GLS 3ohp and 4ohb in particular showed strong associations 562
with the Gln-related traits and are among the most abundant class of GLS in seeds (Petersen et 563
al 2002 Velasco et al 2008) In addition the aliphatic GLS are the most abundant GLS in 564
Arabidopsis seeds (Kliebenstein et al 2001) Interestingly their precise function in this tissue is 565
unclear Taken together our results show that although unexpected the pathway level 566
association revealed by our mGWAS approach is strongly supported by multiple independent 567
approaches 568
569
The Nature of the Association Between the Gln-Related Traits and the GLS Natural Diversity 570
is Complex and Seed Specific 571
The precise nature of the association between GLS and the Gln-related traits is unclear Our data 572
indicate that the association is not simple Analysis of known single gene mutants of the genes 573
related to GLS in the GS-ELONG and GS-AOP regions in the Col-0 background (which lacks the 574
expression of AOP2 and MAM2) (Kroymann et al 2001) showed relatively small changes in the 575
Gln-related traits (Fig 5 Supplemental Table 5) This finding is perhaps not surprising since 576
GLS diversity relies on the presence of a complex epistatic interaction network of different GLS 577
QTLs (Burow et al 2010) and the ability of a single gene elimination in a set genotypic 578
background to capture all the potential allelic combinations is very limited In addition a 579
reduction of about half of the aliphatic GLS through single mutations in either the myb28 or 580
myb29 mutants (Francisco et al 2016) did not result in any large effects on the Gln-related traits 581
(Fig 6 Supplemental Table 5) However the elimination of all GLS transported to the seeds in 582
the gtr12 double mutant or removal of the aliphatic GLS in the myb2829 from the entire plant 583
had a profound effect on the composition of all FAAs and most prominently on Gln (Fig 6 584
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20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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37
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Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
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Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
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Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
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Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
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Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
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Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
20
Supplemental Table 5) These findings emphasize that the association between Gln and GLS 585
relies on a complete elimination of specific GLS in the seed This observation is further 586
supported by our statistical analysis of the association between levels of the Gln-related traits and 587
the presenceabsence of specific GLS in a natural population (Supplemental Table S3) More 588
importantly lack of FAA alteration in the stem and leaf measured from the double mutant clearly 589
showed that the association between GLS and Gln is seed specific and is not the cause of a 590
pleotropic effect that could arise from a lack of GLS in the mother plant or a direct interaction of 591
the MYB genes with any Gln-related pathway genes (Supplemental Table S6) In line with our 592
observation a study of the perturbation of aliphatic GLS biosynthesis in Arabidopsis showed 593
mild alteration in leaf FAA including free Gln in fact the study found that Gln levels in leaves 594
slightly decreased (Chen et al 2012) Interestingly our FAA analysis performed during early 595
seed maturation further indicated that the response of Gln to the lack of GLS especially 596
aliphatic occurs early (Fig 7 Supplemental Table 7) Overall this early seed-specific 597
interaction strongly suggests that both GLS and Gln have key functions in seed metabolic 598
homeostasis that are not manifested in the vegetative tissues Moreover it also demonstrates that 599
an mGWAS of FAA in dry seeds can reveal associations of biological processes taking place in 600
early development 601
602
The Association between Gln and GLS Is Likely Indirect and Induced by Alterations in the 603
Seed Metabolic Homeostasis 604
The molecular mechanism that underlies the interaction between GLS and Gln in the seeds is not 605
clear The Gln response appears to depend on the presenceabsence of aliphatic GLS that is 606
manifested in a specific tissue and is not dosage dependent This suggests that the interaction is 607
likely indirect and is potentially mediated through alteration of signalingsensing pathways or 608
other aspects of cell metabolism Consistently previous studies in Arabidopsis leaves have 609
shown that perturbation of the aliphatic GLS alter several proteins and metabolites involved in 610
various physiological processes including photosynthesis oxidative stress hormone 611
metabolism and specific amino acids (Chen et al 2012) It also has been shown in Arabidopsis 612
specific that indole GLS activation products can interact with the conserved TIR auxin receptor 613
to alter auxin sensitivity (Katz et al 2015) Furthermore exogenous application of a specific 614
aliphatic GLS (3ohp) causes an alteration in root meristem growth in an array of plant lineages 615
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
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1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
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Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
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21
even those that have never been reported to produce GLS (Malinovsky et al 2017) These 616
authors have established that this response is due to the interaction between GLS and the TOR 617
pathway which is a key primary metabolic sensor that controls growth and development and is 618
conserved back to the last common eukaryotic ancestor (Henriques et al 2014) These findings 619
highlight the potential interactions of aliphatic GLS with primary metabolism and a conserved 620
sensing mechanism Consistent with these observations our data show that the presence of 621
specific GLS compounds has a significant effect on the levels of the Gln-related ratios 3ohp had 622
a negative effect on most of the Gln-related ratios whereas 4ohb had the opposite effect 623
(Supplementary Table S3) These two GLS may possibly interact with distinct conserved 624
metabolic regulatory pathways that affect Gln metabolism 625
Our data also indicate that the strong seed-specific association between the Gln-related 626
traits and GLS in the seeds lacking aliphatic GLS (ie myb2829 and gtr12) may be induced 627
due to substantial alteration in the overall cell metabolic homeostasis Our analysis of the carbon 628
nitrogen and sulfur contents of the two double mutants lacking aliphatic GLS in seeds support 629
this hypothesis The results show that carbon remains relatively stable whereas both the nitrogen 630
and sulfur homeostasis is severely altered total sulfur is dramatically decreased and nitrogen is 631
increased (Table 3) GLS are compounds rich in both nitrogen and sulfur which are present in 632
high levels in seeds It was previously suggested that GLS may function as a sulfur storage due 633
to the large induction of the GLS breakdown pathway during broccoli (Brassica oleracea var 634
italic) seed germination (Gao et al 2014) Gln is also known to increase upon both high nitrogen 635
availability and sulfur deficiency (Nikiforova et al 2005 Nikiforova et al 2006) A study of 636
sulfur starvation in Arabidopsis seedlings showed that plants convert the accumulated excess 637
nitrogen into nitrogenous compounds including Gln (reviewed in (Nikiforova et al 2006)) 638
Hence it is possible that the lack of stored sulfur in the form of GLS in seeds may lead to sulfur 639
deficiency in turn leading to an elevation in FAAs especially Gln It is worth mentioning that no 640
coherent pattern of alteration of the PBAA composition was observed in the myb2829 and the 641
gtr12 mutants as compared to the Col-0 ecotype indicating that the elevation in Gln is not due 642
to a lack of incorporation of Gln into SSP (Supplemental Table 8) The latter finding further 643
supports the conclusions that sulfur reduction is due mainly to GLS reduction and that the 644
interaction between the pathways is mediated through signalingsensing cascades that are 645
induced in response to the alterations to seed metabolic homeostasis 646
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22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
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Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
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Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
22
647
Conclusions 648
In this study we demonstrated that free glutamine in Arabidopsis seeds is strongly affected by 649
glucosinolate diversity and presence in this organ This finding clearly highlights that the 650
presence of specific secondary metabolites can profoundly affect primary metabolism in seeds 651
and that selected specialized metabolites may play a larger role in the metabolic homeostasis of 652
this tissue than originally believed Evolutionary theory predicts that the diversity and 653
composition of plant defense compounds such as the glucosinolates in the different plant tissues 654
reflect past selection pressures imposed on plants by their environment (Jones and Firn 1991) 655
pressures that are believed to be key driving forces of compound diversity and composition 656
(Benderoth et al 2006) Our study supports this claim and further suggests that the GLS effect 657
on core metabolism may have played a role in shaping its diversity and composition further 658
studies are needed to reveal the extent of this phenomenon and its implication for seed fitness 659
Our study also aligns with previous work that has shown that although defense mechanisms 660
such as GLS although evolutionarily more recent and often species- and taxa-specific have 661
established connections with conserved regulatorysignaling pathways involved in core 662
metabolism and other essential cellular processes The latter was suggested to be evolutionarily 663
advantageous in helping plants coordinate both defense metabolism and growth (Malinovsky et 664
al 2017) Finally this study demonstrates that performing a semi-combinatorial ratio based 665
mGWAS using metabolites measured in dry seeds can capture events occurring early in seed 666
development This finding has practical implications for future metabolic analyses since it is 667
easier to perform an mGWAS on dry seeds than on developing seeds 668
669
Materials and Methods 670
671
Plant growth and seed collection 672
All Arabidopsis (Arabidopsis thaliana) genotypes were grown at 22degC24degC (daynight) under 673
long-day conditions (16 h of light8 h of dark) Growth of the Arabidopsis diversity panel 674
(Nordborg et al 2005 Platt et al 2010 Horton et al 2012) was as described (Angelovici et al 675
2013) 676
677
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23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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38
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
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Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
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Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
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Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
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Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
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Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
23
Seed and tissue collection 678
Developing siliques were marked to track their developmental stage Siliques were harvested at 679
12 14 16 or 18 days after flowering (DAF) as well as from dry seeds flash frozen in liquid 680
nitrogen upon collection and stored at -80C Siliques were lyophilized and the seeds were 681
isolated and ground for the metabolic analysis 682
Sample leaf and stem tissues were collected from the same plants at approximately 20 683
days after bolting Only green tissue was collected Tissues were flash frozen in liquid nitrogen 684
upon collection and stored at -80C Tissues were lyophilized and ground for the metabolic 685
analysis 686
687
Isolation of T-DNA insertion mutants and genotypic characterization 688
The mutant lines SAIL_181_F06 (aop1) SALK_001655C (aop3) SALK_004536C (mam3) and 689
WiscDsLoxHs043_06G (bsu1) were obtained from the Arabidopsis Biological Resource Center 690
(httpsabrcosuedu) The SALK and WiscDsLoxHs043_06G insertions are in the Col-0 691
background and the SAIL_181_F06 mutant is in the Col-3 background Homozygous mutant 692
lines were validated by genomic PCR using gene-specific primers in combination with the T-693
DNA left border primer Primers spanning the full-length transcript were used to confirm lack of 694
transcripts for respective genes The list of primers can be found in Supplemental Table S4 695
The AOP2 overexpression line (Burow et al 2015) the myb28 and myb29 single 696
mutants the myb2829 and myb3451 knockout mutants (Sonderby et al 2010 Frerigmann and 697
Gigolashvili 2014) and the GSM1 mutant (Haughn et al 1991) were provided by Dr Dan 698
Kliebenstein with the University of California Davis The GLS transporter mutant gtr12 (Nour-699
Eldin et al 2012) was provided by Dr Hussam Hassan Nour-Eldin with Copenhagen 700
University 701
702
Transcript analysis 703
Total RNA extracted from dry and developing seeds was isolated using a hot borate method 704
(Birtic and Kranner 2006) and purified using Direct-zol RNA Miniprep Plus filter columns 705
(Zymo Research) Total RNA from leaves was extracted using the Direct-zol RNA Miniprep 706
Plus Kit (Zymo Research) First-strand cDNA was synthesized from 1 microg of purified total RNA 707
using the iScript cDNA Synthesis Kit (Bio-rad) RT-PCR was used to determine transcript levels 708
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
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34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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24
using the Dream Taq Green Master Mix (Thermo Fisher Scientific) with ACTIN2 (AT3G18780) 709
as a control (For primers see Supplemental Table S4) 710
711
Data analysis and mGWAS 712
mGWAS was performed using the genotypic data from the 250K single nucleotide 713
polymorphism (SNP) chip that was performed on the Arabidopsis diversity panel (Horton et al 714
2012) SNPs with a minor allele frequency (MAF) lt005 were removed leaving 214052 SNPs 715
for our association mapping The 14 derived ratios and glutamine absolute value and relative 716
composition were used as trait inputs The association tests were conducted in R 332 (Team 717
2014) using the R package Fixed and Random Model Circulating Probability Unification 718
(FarmCPU) (Liu et al 2016) The Bonferroni correction was used to control the experiment 719
wise type I error rate at 120572 = 001 720
721
Statistical analysis of the Gln-related trait levels in accessions harboring specific GLS 722
A subset of 133 accessions from the 313-accession population were grown in single replicates 723
and analyzed for FAA and GLS contents Accessions were grouped based on the presence or 724
absence of four GLS chemotypes 3ohp 2-propenyl 4ohb and 3-butenylOH-3-butenyl A t-test 725
was used to test for the presenceabsence of the group based on levels of Gln-related traits 726
Because sample sizes of some groups were small a 1000 permutations procedure was conducted 727
to determine statistical significance at 120572 = 005 (Churchill and Doerge 1994) 728
GO enrichment 729
For the candidate genes associated with the SNPs a GO enrichment analysis was performed 730
using agriGO (Zhou et al 2010) with the following parameters a hypergeometric test with a = 731
005 FDR correction (n = 3) an agriGO suggested background Arabidopsis as the select 732
organism and a complete GO ontology 733
734
Correlation analysis 735
A Spearmanrsquos rank correlation was used to calculate an r correlation matrix between all raw 736
absolute levels of FAA in the glutamate family after one round of outlier removal was performed 737
in R A p-value was calculated to reflect the significance of each correlation Results were 738
filtered using a r2 = 01 threshold and a p-value = 0001 Results were visualized with 739
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25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
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26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
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Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
25
Cystoscope (Shannon et al 2003) using the method previously described in (Batushansky et al 740
2016) 741
742
Haplotype analysis and pairwise LD analysis 743
Since the average LD in Arabidopsis is 10 kb (Kim et al 2007) the haploblock analysis was 744
performed on a 10-kb window where the 5 kb to the left and right of each significant SNP were 745
used as inputs The haploblock analysis was completed using Haploview version 42 (Barrett et 746
al 2004) Pairwise LD values (r2) were calculated between the significant SNP of interest and 747
neighboring (upstream and downstream) SNPs in a +-5 kb window All SNPs were filtered at a 748
5 MAF Default Gabriel block parameters were used resulting in blocks that contained at least 749
95 of the SNPs in strong LD Any genes contained or partially contained in the haploblock 750
with a significant SNP were saved as putative genes of interest If no haploblock was identified 751
for a respective SNP then the genes immediately upstream and downstream of the SNP were 752
saved 753
754
QTL analysis 755
A QTL analysis was conducted on the 158 RILs from the Bay x Sha population (Loudet et al 756
2002) in R 332 (Team 2014) using the Rqtl2 package (Broman et al 2019) Data were 757
previously quantified and described in Angelovici et al (2013) Publicly available genotype 758
markers spanned the five chromosomes for a total of 69 markers The mqmaugment function in R 759
was used to calculate genotype probabilities using a step value and an assumed genotyping error 760
rate of 0001 Missing values were replaced with the most probable values using the fillgeno 761
function unsupervised cofactor selection was completed through backward elimination 762
Genome-wide LOD significance thresholds were determined using 1000 permutations for each 763
trait For each QTL confidence intervals were determined by a 15 LOD drop from peak marker 764
Percent variance explained (PVE) was calculated using the following formula PVE = 1 - 10^(-765
(2n)LOD) where n is the sample size Epistatic interactions were explored using the effectplot 766
function 767
768
Metabolic analyses 769
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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37
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38
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Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
26
Amino acid analysis Amino acids were analyzed from four biological replicates (n = 3ndash4) for 770
seed tissues and from five biological replicates (n = 5) for leaf and stem tissues The PBAAs 771
were extracted from ~3 mg of dry seed by performing acid hydrolysis (200 microl 6N HCl at 110degC 772
for 24 h) followed by the FAA extraction method described in (Yobi and Angelovici 2018) 773
FAAs were extracted with 1 mM of perfluoroheptanoic acid (PFHA) from ~6 mg tissue as 774
described previously (Yobi et al 2019) The analyses were performed using an ultra-775
performance liquid chromatography-tandem mass spectrometer (UPLC-MSMS) instrument 776
(Waters Corporation Milford MA) as detailed previously (Yobi and Angelovici 2018 Yobi et 777
al 2019) 778
GLS analysis GLS identification and quantification were completed using high-performance 779
liquid chromatography with diode-array detection (HPLCDAD) as previously described 780
previously (Kliebenstein et al 2001) 781
Nitrogen and carbon analyses Nitrogen and carbon levels were determined using an ECS 4010 782
CHNSO analyzer (Costech Analytical Technologies Inc) following the instructions in the 783
manufacturerrsquos manual Briefly ~2 mg tissue from five biological replicates (n = 5) were placed 784
in tin capsules (Costech Analytical Technologies Inc) and analyzed along with 2 mg of 25-bis-785
2-(5-tert-butylbenzoxazolyl)thiophene (BBOT Thermo Fisher Scientific) as an internal standard 786
Helium was used as a carrier gas and separation was performed on a GC column maintained at 787
110degC Detection was based on a TCD detector and quantification was carried out by plotting 788
against external standards for both molecules 789
Sulfur analysis Sulfur measurements were performed using the procedure described in Ziegler 790
et al (2013) Briefly ~50 mg of seed from six biological replicates (n = 6) were digested with a 791
concentrated HNO3 with an internal standard Seeds were soaked at room temperature overnight 792
and then incubated at 105degC for 2 h After cooling the samples were diluted and analyzed with 793
an Elan 6000 DRC (dynamic reaction cell)-e mass spectrometer (PerkinElmer SCIEX) connected 794
to a Perfluoroalkoxy (PFA) microflow nebulizer (Elemental Scientific) and Apex HF desolvator 795
(Elemental Scientific) as described in (Ziegler et al 2013) 796
797
Accession numbers 798
At4g03070 (AOP1) At4g03060 (AOP2) At4g03050 (AOP3) At5g23010 (MAM1) At5g23020 799
(MAM3) At4g03063 (BSU1) At5g61420 (MYB28) At5g07690 (MYB29) At3g47960 (GTR1) 800
At5g62680 (GTR2) AT1G18570 (MYB51) AT5G60890 (MYB34) 801
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27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
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37
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Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
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Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
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Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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38
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Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
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Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
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Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
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Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
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Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
27
802
803
Supplemental Data 804
805
Supplemental Figure S1 Correlation analysis of the four Glu family FAAs 806
Supplemental Figure S2 Pairwise LD estimates (r2) of S127076 with SNPs spanning all the 807
GLS-related genes in the region 808
Supplemental Figure S3 Pairwise LD estimates (r2) of S175365 with SNPs spanning all the 809
GLS-related genes in the region 810
Supplemental Figure S4 Interaction plots from QTL associated with the GS-AOP and GS-811
ELONG loci showing epistatic interactions between markers MSAT443 and MSAT514 for 812
traits QP and QQP respectively 813
Supplemental Figure S5 AOP1 AOP3 MAM3 and BSU1 genomic structures and transcript 814
levels in tissues of high expression from the respective knockout mutants 815
Supplemental Figure S6 Heatmap of expression data for AOP1 AOP2 AOP3 MAM1 MAM3 816
and BSU1 across various Arabidopsis tissues and seed developmental stages 817
Supplemental Table S1 Mean relative content standard deviation relative standard deviation 818
range and broad-sense heritability of the Glu family and the Gln-related traits 819
Supplemental Table S2 List of all unique genes that are included in the haploblocks spanning 820
all the identified significant SNPs 821
Supplemental Table S3 Statistical analysis summary of the Gln-related levels from the 133 822
accessions grouped by GLS chemotypes 823
Supplemental Table S4 A list of primers used to test for the expression of the full transcript of 824
relevant genes involved in GLS biosynthesis in Arabidopsis 825
Supplemental Table S5 Summary of the fold changes (FC) in the average FAA and Gln-related 826
traits measured from the dry mutant seeds as compared to the control (Col-0) 827
Supplemental Table S6 Summary of the fold changes (FC) in the stem and leaf FAA average 828
levels measured from the myb2829 and gtr12 mutants as compared to the Col-0 829
Supplemental Table S7 Summary of the FAA measured from seeds harvested at five time 830
points during seed maturation in the myb2829 and gtr12 mutants and Col-0 ecotype 831
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28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
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Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
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Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
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Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
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Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
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Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
28
Supplemental Table S8 Summary of the fold changes (FC) in the protein-bound amino acid 832
(PBAA) absolute level averages (nmolmg) in myb2829 and gtr12 mutant dry seeds 833
Supplemental Dataset S1 mGWAS results summarizing all significant SNP-trait associations 834
identified at a 1 Bonferroni level from the 16 Gln-related traits 835
Supplemental Dataset S2 The full QTL analysis of the 16 Gln-related traits from the Bay x Sha 836
mapping population 837
Supplemental Dataset S3 Summary of Gln-related traits and GLS measurements from the dry 838
seeds in the 133-accession Arabidopsis panel 839
Supplemental Dataset S4 Summary of the seed FAA quantification from mutants of relevant 840
genes involved in the natural variation of aliphatic GLS in the Col-0 background 841
Supplemental Dataset S5 Summary of the FAA absolute level measurements from the leaf and 842
stem tissues of Arabidopsis myb2829 and gtr12 mutants and the Col-0 ecotype 843
Supplemental Dataset S6 Summary of the FAA measured from seeds harvested at five time 844
points during seed maturation in the myb2829 and gtr12 mutants and the Col-0 ecotype 845
Supplemental Dataset S7 Summary of the protein-bound amino acid (PBAA) absolute levels 846
(nmolmg) measured from the dry seeds of the myb2829 and gtr12 mutants 847
848
849
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29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
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Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
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Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
29
Tables 850
Table 1 Top five SNP-trait associations with the lowest p-values Traits SNP chromosomal position p-value relevant haploblock 851
coordinates the genes that contain significant SNPs or are within a haploblock containing a significant SNP and their annotation are 852
summarized for each SNP An asterisk () designates a gene containing the SNP If a SNP is intergenic and falls within a haploblock 853
with additional genes the additional genes are listed If the SNP is intergenic and does not fall within a haploblock the genes directly 854
upstream (L) and downstream (R) are recorded 855
856
SNP Trait Chr Position p-value Haploblock range Genes within
haploblock Functional annotation
S204486 QP 5 21544586 618E-15 None AT5G53135 transposable element
AT5G53140 protein phosphatase 2C family protein
S127076 QRP 4 1360042 617E-14 1356197-1364333 AT4G03063 Pseudogene of AT4G03070 AOP1 (2-
oxoglutarate-dependent dioxygenase 11)
QRQP AT4G03070 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (AOP1)
AT4G03080 BRI1 suppressor 1 (BSU1)-like 1
S124151 QR 4 152626 532E-13 152604-152640 AT4G00350 MATE efflux family protein
QRQ
S190878 QRP 5 15830557 522E-11 15829858-15830557 AT5G39530 (L) hypothetical protein (DUF1997)
AT5G39532 (R) pseudogene of Bifunctional inhibitorlipid-transfer
proteinseed storage 2S albumin superfamily
protein (computational description)
S175365 QP 5 7704845 379E-10 7703584-7705070 AT5G23010 methylthioalkylmalate synthase 1 (MAM1)
857
858
859
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30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
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Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
30
Table 2 QTL analysis of the (Gln)-related traits from the Bay x Sha mapping population Only QTL that span the GS-ELONG andor 860
GS-AOP region are shown For full analysis see Supplemental Dataset S2 Genotypic and phenotypic data from 158 recombinant 861
inbred lines were analyzed using the Rqtl2 package to identify significant QTLs An asterisk () indicates traits with significant SNP-862
trait associations in our GWAS 863
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QRQ 5 MSAT514 266 7499 177-454 467-1396 349 967
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRQP 5 MSAT514 266 7499 177-418 467-1211 782 2038
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QR 5 MSAT514 266 7499 177-454 467-1396 280 784
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QRP 5 MSAT514 266 7499 177-418 467-1211 597 1597
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
864
865
866
867
868
869
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
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34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
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31
Continued 870
Trait Chr Marker
name
Marker
position
(cM)
Marker
position (Mbp)
Suporting
interval (cM)
Supporting
interval (Mbp)
Log of
the odds
Phenotypic
variance
GSL genes in supporting interval
Gene name Gene location
QQP
4 MSAT443 107 2576 2-242 041-755 397 1093
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
AT4G12030 7210807-7213376
5 MSAT514 266 7499 177-418 467-1211 1579 3689
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
QP
4 MSAT443 107 2576 2-158 041-563 588 1575
AT4G03050 (AOP3) 1343845-1346436
AT4G03060 (AOP2) 1351688-1354096
AT4G03063 (AOP1) 1355667-1356018
AT4G03070 (AOP1) 1358267-1359698
5 MSAT514 266 7499 177-418 467-1211 1210 2972
AT5G23010 (MAM1) 7703041-7706973
MAM2
AT5G23020 (MAM3) 7718118-7721866
AT5G26000 9079452-9082384
871
872
873
874
875
876
877
878
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
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37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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32
Table 3 Nitrogen carbon and sulfur absolute levels measured from the dry seeds of Arabidopsis myb2829 and gtr12 double 879
mutants and the Col-0 ecotype (n =5) The table lists the averages of the absolute levels the percentage of each absolute level in the 880
mutants relative to Col-0 the percentage of increase or decrease and the significance of the difference after using a Duncanrsquos Multiple 881
Range Test with different lower-case letters indicating significant differences at the = 005 level 882
883
Element Line Av Absolute levels (microgmg) of control Difference Duncan
Nitrogen
Col-0 3415 plusmn 032 100 0 b
myb2829 3694 plusmn 048 10817 817 a
gtr12 3918 plusmn 019 11473 1473 a
Carbon
Col-0 52514 plusmn 416 100 0 a
myb2829 5191 plusmn 518 9885 -115 a
gtr12 50876 plusmn 294 9688 -312 a
Sulfur
Col-0 537 plusmn 003 100 0 a
myb2829 115 plusmn 001 2143 -7857 b
gtr12 054 plusmn 002 996 -9004 c
884
885
886
887
888
889
890
891
892
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33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
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35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
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Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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38
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
33
Figure legends 893
Fig 1 Simplified metabolic pathways of the Glu amino acid family and the aliphatic GLS 894
Genes that are within the genomic region of GS-ELONG or GS-AOP loci are represented in red 895
and include MAM1 MAM2 and MAM3 as well as AOP2 and AOP3 These gene products are 896
responsible for most of the GLS natural diversity MAM1 is responsible for the production of C4 897
GLS 4-methylsulfinybutyl GLS (4msb) MAM2 (in the absence of MAM1) is required for the 898
production of C3 GLS 3-methylsulfinypropyl GLS (3msp) MAM3 is responsible for the 899
production of C8 GLS 8-methylsulfinyloctyl (8mso) C3 GLS 3msp can be further converted to 900
3-hydroxypropyl GLS (3ohp) by AOP3 or 2-propenyl by AOP2 C4 GLS 4msb can be converted 901
to 4-hydrozybutyl GLS (4ohb) by AOP3 or 3-butenyl and then OH-3-butenyl by AOP2 902
903
Fig 2 The chromosomal distribution of the 21 significant SNP-trait associations identified by 904
the mGWAS A total of 21 significant SNPs-trait associations were identified at an = 001 905
Bonferroni for six traits SNPs are represented by short lines that are color-coded based on their 906
P-value The histogram on top of the heatmap illustrates the number of occurrences of each SNP 907
identified across all traits Arrows indicate SNPs located within a gene or haploblock of interest 908
An asterisk () designates traits that have a significant association with a SNP in a GLS gene or 909
in high LD with GLS genes Q glutamine R arginine P proline 910
911
Fig 3 mGWAS of traits QRP and QRQ These two representative traits have significant 912
associations with SNPs in LD with genes AOP1 and AOP3 respectively A Scatterplots for 913
QRP (dark blue and black) and QRQ (light blue and grey) show significant associations among 914
multiple SNPs including S127076 and S127050 respectively (red) that reside in haploblocks 915
that contain GLS biosynthesis genes Negative log10-transformed p-values are plotted against 916
the genomic physical position The red line represents the 1 Bonferroni cutoff All SNPs above 917
the red line are significantly associated with other SNPs at that level B A graphical 918
representation of genes and haploblocks within the genomic region (Chr4 1340000ndash1375000 919
bp) spanning SNPs S127076 and S127050 (red arrows) This region also spans the GS-AOP 920
QTL S127050 falls within haploblock 2 which spans AOP3 S127076 falls within haploblock 5 921
which spans BSU1 and AOP1 Genes are represented by wide grey arrow unless they are 922
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34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
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Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
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Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
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Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
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Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
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Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
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Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
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Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
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Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
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Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
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Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
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Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
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Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
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34
associated with GLS biosynthesis and marked in red Haploblocks in the region are represented 923
by numbered boxes and shaded grey if they contain a SNP of interest 924
925
Fig 4 mGWAS of QP A A scatterplot for QP shows the significant associations among 926
several SNPs including S175365 (marked in red) Negative log10-transformed p-values are 927
plotted against the genomic physical position The red line represents the 1 Bonferroni cutoff 928
All SNPs above the red line are significantly associated with SNPs at that level B A graphical 929
representation of genes and haploblocks within the genomic region spanning SNP S175365 (red 930
arrow) and GLS genes in close proximity (Chr47695000ndash7725000 bp) This region spans the 931
GS-ELONG QTL Genes are represented by wide grey arrows unless they are associated with 932
GLS biosynthesis and marked in red Haploblocks in the region are represented by numbered 933
boxes and shaded grey if they contain a SNP of interest 934
935
Fig 5 Heatmap of the fold changes of FAA and Gln-related traits average in GLS null and OX 936
mutants and the Col-0 ecotype Measurements were obtained from dry seeds and used to 937
calculate the log2 Fold Change (FC) with respect to the Col-0 ecotype for each FAA (A) and 938
each Gln-related trait (B) Blue indicates that the FAA or Gln-related trait decreased relative to 939
Col-0 whereas red indicates that the FAA or Gln-related trait increased relative to Col-0 A t-test 940
was performed to determine the significance of the changes between each mutant and Col-0 (n = 941
3ndash4) Asterisks () represent significant difference between the mutant and the control at a = 942
005 level Q glutamine E glutamate R arginine P proline 943
944
945
Fig 6 Heatmap of the fold changes of FAA and Gln-related traits average in the GLS single and 946
double knockout mutants and the Col-0 ecotype A and B Measurements were obtained from 947
dry seeds and used to calculate the average log2 fold change (FC) with respect to the Col-0 948
ecotype for each FAA (A) and each Gln-related trait (B) Blue indicates that the FAA or Gln-949
related trait decreased relative to Col-0 whereas red indicates that the FAA or Gln-related trait 950
increased relative to Col-0 C A heatmap of the FAA composition of each amino acid ( 951
FAATotal AA) calculated per genotype using the FAA measurements from seeds Red indicates 952
that the amino acid represents a higher percentage of the total composition relative to Col-0 953
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
36
984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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38
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
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Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
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Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
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1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
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Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
35
whereas yellow indicates that the amino acid represents a lower percentage of the total 954
composition relative to Col-0 Asterisks () indicate a significant difference between the mutant 955
and the Col-0 as deduced by t-test at an = 005 level (n = 3ndash4) Q glutamine E glutamate R 956
arginine P proline 957
958
Fig 7 Gln levels and the relative composition of free amino acids across maturation in the GLS 959
double knockout mutants (myb2829 grt12) and the Col-0 ecotype Seeds were harvested at 12 960
14 16 and 18 days after flowering (DAF) and at full maturation (dry seed) and FAA levels and 961
composition were analyzed across these developmental time points A Gln levels (nmolmg) 962
across seed maturation in Col-0 B Gln levels in the double mutants C Composition analysis of 963
the 20 FAAs across the developmental time-points for the three genotypes Relative composition 964
is presented as of each FAA to TFAA in the seed TFAA represents a sum of the 20 FAA 965
measurements Red indicates that the amino acid represents a higher percentage of the total 966
composition relative to Col-0 whereas yellow indicates that the amino acid represents a lower 967
percentage of the total composition relative to Col-0 Asterisks () indicate a significant 968
difference between the mutant and Col-0 as deduced by t-test at an = 005 level (n = 4 except 969
for 18 DAF which is n = 2 for gtr12) 970
971
972
Acknowledgments 973
The authors wish to acknowledge Melody Kroll for assistance with editing the manuscript and 974
Ivan Baxter and Greg Ziegler for sulfur analysis 975
976
Disclosure 977
Authors have no conflict of interest to declare 978
979
980
981
982
983
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36
984
Literature cited 985
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Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
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Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
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Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
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Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
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Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
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Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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984
Literature cited 985
Angelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) 986 Network-guided GWAS improves identification of genes affecting free amino acids Plant 987 Physiology 173 872-886 988
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA 989 Dellapenna D (2013) Genome-wide analysis of branched-chain amino acid levels in Arabidopsis 990 seeds Plant Cell 25 4827-4843 991
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM 992 Hu TT (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred 993 lines Nature 465 994
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and 995 haplotype maps Bioinformatics 21 263-265 996
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and 997 analysis as a powerful tool in biological studies a case study in cancer cell metabolism Biomed 998 Res Int 2016 1-9 999
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed 1000 development in Arabidopsis thaliana ecotype WS Plant Physiology and Biochemistry 40 151-1001 160 1002
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive 1003 selection driving diversification in plant secondary metabolism Proceedings of the National 1004 Academy of Sciences of the United States of America 103 9118-9123 1005
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is 1006 an amino acid exporter involved in phloem unloading in Arabidopsis roots J Exp Bot 67 6385-1007 6397 1008
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) 1009 Rqtl2 Software for mapping quantitative trait loci with high-dimensional data and multiparent 1010 populations Genetics 211 495-502 1011
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate 1012 biosynthetic gene AOP2 mediates feed-back regulation of jasmonic acid signaling in Arabidopsis 1013 Molecular plant 8 1201-1212 1014
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The 1015 Glucosinolate Biosynthetic Gene AOP2 Mediates Feed-back Regulation of Jasmonic Acid 1016 Signaling in Arabidopsis Mol Plant 8 1201-1212 1017
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape 1018 Arabidopsis thaliana fitness Curr Opin Plant Biol 13 348-353 1019
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1020 association mapping and transcriptional networks to identify novel genes controlling 1021 glucosinolates in Arabidopsis thaliana PLoS Biol 9 1022
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide 1023 association mapping and transcriptional networks to identify novel genes controlling 1024 glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125 1025
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang 1026 L Yu S Wang G Lian X Luo J (2014) Genome-wide association analyses provide genetic and 1027 biochemical insights into natural variation in rice metabolism Nat Genet 46 714-721 1028
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and 1029 metabolomics of Arabidopsis responses to perturbation of glucosinolate biosynthesis Mol Plant 1030 5 1138-1150 1031
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical 1072 Transactions of the Royal Society of London Series B-Biological Sciences 333 273-280 1073
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
38
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
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39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
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Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
37
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-1032 Castillo E Wallace JG Cepela J Mesberg A Bradbury PJ Ilut DC Mateos-Hernandez M 1033 Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MA DellaPenna 1034 D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 1035 29 2374-2392 1036
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) 1037 Arabidopsis seed development and germination is associated with temporally distinct metabolic 1038 switches Plant Physiol 142 839-854 1039
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants 1040 energetics and redox signaling Annu Rev Plant Biol 60 455-484 1041
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein 1042 DJ (2016) The Defense Metabolite Allyl Glucosinolate Modulates Arabidopsis thaliana 1043 Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7 774 1044
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1045 glucosinolate biosynthesis in Arabidopsis thaliana Mol Plant 7 814-828 1046
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic 1047 glucosinolate biosynthesis in Arabidopsis thaliana Molecular Plant 7 814-828 1048
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in 1049 seeds and sprouts of broccoli (Brassica oleracea var italic) PLoS One 9 e88804 1050
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN 1051 Angelovici R Lin H Cepela J Little H Buell CR Gore MA Dellapenna D (2013) 1052 Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content in Arabidopsis 1053 seeds Plant Cell 25 4812-4826 1054
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 1055 303-333 1056
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary 1057 metabolites in Arabidopsis thaliana the glucosinolates Plant Physiology 97 217-226 1058
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary 1059 Metabolites in Arabidopsis thaliana The Glucosinolates Plant Physiol 97 217-226 1060
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment 1061 by the TOR signalling pathway J Exp Bot 65 2691-2701 1062
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A 1063 Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide 1064 Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212 1065
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate 1066 metabolism In SB K ed Plant Amino Acids Biochemistry and Biotechnology Marcel Dekker 1067 New York pp 49-109 1068
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands 1069 the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 1070 762 1071
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Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G 1074 Chamovitz DA (2015) The glucosinolate breakdown product indole-3-carbinol acts as an auxin 1075 antagonist in roots of Arabidopsis thaliana Plant J 82 547-555 1076
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M 1077 (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana Nat Genet 39 1078
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J 1079 Last RL Jander G (2007) Characterization of seed-specific benzoyloxyglucosinolate mutations 1080 in Arabidopsis thaliana Plant J 51 1062-1076 1081
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Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
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Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
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Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
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Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
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Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
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40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
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Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
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Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
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Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
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Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
38
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T 1082 (2001) Genetic control of natural variation in Arabidopsis glucosinolate accumulation Plant 1083 Physiol 126 811-825 1084
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an 1085 Arabidopsis insect resistance quantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 1086 14587-14592 1087
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A 1088 gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine 1089 chain elongation pathway Plant Physiol 127 1077-1088 1090
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-1091 616 1092
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR 1093 Buckler ES Rocheford T Dellapenna D (2013) Genome-wide association study and pathway-1094 level analysis of tocochromanol levels in maize grain G3 3 1287-1299 1095
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect 1096 Models for Powerful and Efficient Genome-Wide Association Studies PLoS Genet 12 e1005767 1097
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect 1098 models for powerful and efficient genome-wide association studies PLoS genetics 12 e1005767 1099
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant 1100 inbred line population a powerful tool for the genetic dissection of complex traits in Arabidopsis 1101 Theoretical and Applied Genetics 104 1173-1184 1102
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation 1103 in Brassica napus and Arabidopsis thaliana Heredity 72 290-299 1104
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates 1105 in Seeds and Seedlings of Brassica-Napus Plant Breeding 111 249-252 1106
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) 1107 Glutamate Ornithine Arginine Proline and Polyamine Metabolic Interactions The Pathway Is 1108 Regulated at the Post-Transcriptional Level Front Plant Sci 7 78 1109
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ 1110 (2017) An evolutionarily young defense metabolite influences the root growth of plants via the 1111 ancient TOR signaling pathway Elife 6 1112
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR 1113 Hesse H Hoefgen R (2006) Effect of sulfur availability on the integrity of amino acid 1114 biosynthesis in plants Amino Acids 30 173-183 1115
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R 1116 (2005) Systems rebalancing of metabolism in response to sulfur deprivation as revealed by 1117 metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318 1118
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich 1119 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1120 glucosinolate defence compounds to seeds Nature 488 531-534 1121
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich 1122 R Geiger D Halkier BA (2012) NRTPTR transporters are essential for translocation of 1123 glucosinolate defence compounds to seeds Nature 488 531 1124
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family 1125 Functions beyond Primary Metabolism Front Plant Sci 7 318 1126
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic 1127 Glucosinolates 2 Hydroxylation of Alkenyl Glucosinolates in Brassica-Napus Heredity 72 594-1128 598 1129
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of 1130 glucosinolates in developing Arabidopsis thaliana Planta 214 562-571 1131
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
39
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1136 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1137 profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877 1138
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - 1139 Impact on glucosinolate profile and insect resistance Journal of Applied Botany and Food 1140 Quality-Angewandte Botanik 82 131-135 1141
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D 1142 Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development Nat Genet 1143 37 501-506 1144
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos 1145 of Brassica napus J Biol Chem 281 34040-34047 1146
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker 1147 T (2003) Cytoscape a software environment for integrated models of biomolecular interaction 1148 networks Genome Res 13 2498-2504 1149
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of 1150 assimilation of [N]ammonium and [N]nitrate by tobacco cells cultured on different sources of 1151 nitrogen Plant Physiol 62 299-304 1152
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of 1153 Three R2R3 MYB Transcription Factors Determines the Profile of Aliphatic Glucosinolates in 1154 Arabidopsis1[C][W][OA] Plant Physiology 153 348-363 1155
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems 1156 biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions 1157 in regulation of aliphatic glucosinolates PLoS One 2 e1322 1158
Team R (2014) A language and environment for statistical computing R Foundation for Statistical 1159 Computing Vienna Austria2014 URL(httpswww R-project org) 1160
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis 1161 of methionine-derived glucosinolates in Arabidopsis thaliana recombinant expression and 1162 characterization of methylthioalkylmalate synthase the condensing enzyme of the chain-1163 elongation cycle Planta 218 1026-1035 1164
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in 1165 leaf and seed tissues of different Brassica napus crops Journal of the American Society for 1166 Horticultural Science 133 551-558 1167
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping 1168 combined with reverse genetics identifies new effectors of low water potential-induced proline 1169 accumulation in Arabidopsis Plant Physiol 164 144-159 1170
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-1171 based genome-wide association study of maize kernel leads to novel biochemical insights Nat 1172 Commun 5 3438 1173
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking 1174 metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways PLoS Genet 3 1175 1687-1701 1176
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent 1177 Pictograph browser for exploring and analyzing large-scale biological data sets PLoS One 2 1178 e718 1179
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M 1132 Willmitzer L Melchinger AE (2012) Genome-wide association mapping of leaf metabolic 1133 profiles for dissecting complex traits in maize Proceedings of the National Academy of Sciences 1134 109 8872-8877 1135
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Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino 1180 acids in seeds Curr Protoc Plant Biol e20084 1181
wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
40
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism 1182 to the combination of desiccation and low nitrogen availability in Sporobolus stapfianus Planta 1183 249 1535-1549 1184
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and 1185 seed productivity by simultaneous increase of phloem and embryo loading with amino acids 1186 Plant J 81 134-146 1187
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of 1188 amino acids affects metabolism and leads to increased seed yield and oil content in Arabidopsis 1189 Plant Cell 22 3603-3620 1190
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of 1191 Field-Grown Soybean Identifies Mutants with Altered Seed Elemental Composition Plant 1192 Genome 6 1193
1194
1195
1196
1197
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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wwwplantphysiolorgon June 18 2020 - Published by Downloaded from Copyright copy 2020 American Society of Plant Biologists All rights reserved
1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
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Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
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Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
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Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
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Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
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1
GlutamateGlutamine
Arginine Proline
Aspartate
Threonine
IsoleucineSO2
Methionine
Cysteine
Serine
MAM2
3msp
3ohp 2-propenyl
AOP2AOP3
4msb
4ohb 3-butenyl
AOP2AOP3
OH-3-butenyl
MAM1MAM3
8mso
Glutamate family
Aliphatic GLS
Fig 1
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
AOP1BSU-1
AOP3 MAM1
Trai
t
QP
QR
QQP
QRP
QRQ
QRQP
Chromosome Position
1 52 3 4
351E-03
176E-03
618E-10
P-value
SNP
Cou
nt
12
Fig 2
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
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Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
A
BAT4G03050AOP3
AT4G03100
AT4G03040 AT4G03060AOP2
AT4G03080BSU1
AT4G03070AOP1
AT4G03063pseudoAOP1
SNP127076SNP127050
1340K
1375K
1350K
1360K
21 4 5 6
3Chr 4
10
6
2
1 2 3 40
4
8
12
14
-log10(P-value)
Chromosome5
SNP127076
SNP127050
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
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Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
A
B
Chr 5
7695K
7705K
7725K
7715K
1 2 3 4 5 6 97 8
AM180571MAM2
AT5G23000
AT5G23020MAM3
AT5G23010MAM1 SNP175365
1 2 3 4 50
4
8
12
16
-log10(P-value)
Chromosome
SNP175365
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
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Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
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QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0
-1
1log2(FC)
Ratios FCA B
AlaAsnAspGly
Ser
His
Total
IleLeuLysMet
TyrThr
ValCys
Phe
Trp
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
2log2(FC)
0
-2
GlnArgGluPro
Absolute FC
aop1
AOP2
OXao
p3gsm1
mam
3bsu1
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
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Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
AlaAsn
Gly
PheSerTrp
HisIle
LeuLys
Met
Thr
Val
Asp
Tyr
Cys
Gln
GluPro
Arg
A B
myb28
29
gtr12
myb29
myb28
myb34
51
QRPQQEQQP
QR
QQEP
QEQP
QRQQRE
QRQEQEP
QRQPQREP
QTotalQQREP
0-2
8log2FC)
AA Ratios
4
myb28
29
gtr12
Col-0
60FAATotal AA
0
30
10
Absolute CompositionC
AlaAsn
Gly
PheSerTrp
His
Total
IleLeuLys
Met
Thr
Val
Asp
Tyr
Cys
myb28
29
gtr12
myb29
myb28
myb34
51
10log2(FC)
0-2
Gln
GluPro
Arg
6
2
Absolute AA
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
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Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
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Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
C12 14 16 18 Dry 12 14 16 18 Dry
Ala
AsnAsp
Gly
Phe
Ser
Trp
HisIle
LeuLys
Met
TyrThr
Val
Cys
12 14 16 18 Dry
65FAATFAA
0
30
Gln
Arg
GluPro
FAA Composition
myb2829 gtr12 Col-0
DAF
FAA
12 14 16 18 Dry
0
4Col-0
2100
150
50
myb 2829
gtr12
12 14 16 18 Dry
DAF
Gln
cont
ent (
nmol
mg)
A B
Parsed CitationsAngelovici R Batushansky A Deason N Gonzalez-Jorge S Gore MA Fait A DellaPenna D (2017) Network-guided GWAS improvesidentification of genes affecting free amino acids Plant Physiology 173 872-886
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Angelovici R Lipka AE Deason N Gonzalez-Jorge S Lin H Cepela J Buell R Gore MA Dellapenna D (2013) Genome-wide analysis ofbranched-chain amino acid levels in Arabidopsis seeds Plant Cell 25 4827-4843
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Atwell S Huang YS Vilhjalmsson BJ Willems G Horton M Li Y Meng D Platt A Tarone AM Hu TT (2010) Genome-wide associationstudy of 107 phenotypes in Arabidopsis thaliana inbred lines Nature 465
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Barrett JC Fry B Maller J Daly MJ (2004) Haploview analysis and visualization of LD and haplotype maps Bioinformatics 21 263-265Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Batushansky A Toubiana D Fait A (2016) Correlation-based network generation visualization and analysis as a powerful tool inbiological studies a case study in cancer cell metabolism Biomed Res Int 2016 1-9
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Baud S Boutin JP Miquel M Lepiniec L Rochat C (2002) An integrated overview of seed development in Arabidopsis thaliana ecotypeWS Plant Physiology and Biochemistry 40 151-160
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Benderoth M Textor S Windsor AJ Mitchell-Olds T Gershenzon J Kroymann J (2006) Positive selection driving diversification inplant secondary metabolism Proceedings of the National Academy of Sciences of the United States of America 103 9118-9123
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Besnard J Pratelli R Zhao C Sonawala U Collakova E Pilot G Okumoto S (2016) UMAMIT14 is an amino acid exporter involved inphloem unloading in Arabidopsis roots J Exp Bot 67 6385-6397
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Broman KW Gatti DM Simecek P Furlotte NA Prins P Sen Ś Yandell BS Churchill GA (2019) Rqtl2 Software for mappingquantitative trait loci with high-dimensional data and multiparent populations Genetics 211 495-502
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The glucosinolate biosynthetic gene AOP2 mediatesfeed-back regulation of jasmonic acid signaling in Arabidopsis Molecular plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
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Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
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Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
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Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
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Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
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Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
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Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
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Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
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Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
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Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
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Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
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Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
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Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
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Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
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Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
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Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
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Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
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Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Atwell S Francisco M Kerwin RE Halkier BA Kliebenstein DJ (2015) The Glucosinolate Biosynthetic Gene AOP2 MediatesFeed-back Regulation of Jasmonic Acid Signaling in Arabidopsis Mol Plant 8 1201-1212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Burow M Halkier BA Kliebenstein DJ (2010) Regulatory networks of glucosinolates shape Arabidopsis thaliana fitness Curr OpinPlant Biol 13 348-353
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9
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Chan EK Rowe HC Corwin JA Joseph B Kliebenstein DJ (2011) Combining genome-wide association mapping and transcriptionalnetworks to identify novel genes controlling glucosinolates in Arabidopsis thaliana PLoS Biol 9 e1001125
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Chen W Gao Y Xie W Gong L Lu K Wang W Li Y Liu X Zhang H Dong H Zhang W Zhang L Yu S Wang G Lian X Luo J (2014)Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism Nat Genet 46714-721
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Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Diepenbrock CH Kandianis CB Lipka AE Magallanes-Lundback M Vaillancourt B Gongora-Castillo E Wallace JG Cepela J MesbergA Bradbury PJ Ilut DC Mateos-Hernandez M Hamilton J Owens BF Tiede T Buckler ES Rocheford T Buell CR Gore MADellaPenna D (2017) Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain Plant Cell 29 2374-2392
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Fait A Angelovici R Less H Ohad I Urbanczyk-Wochniak E Fernie AR Galili G (2006) Arabidopsis seed development and germinationis associated with temporally distinct metabolic switches Plant Physiol 142 839-854
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Foyer CH Bloom AJ Queval G Noctor G (2009) Photorespiratory metabolism genes mutants energetics and redox signaling AnnuRev Plant Biol 60 455-484
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Francisco M Joseph B Caligagan H Li B Corwin JA Lin C Kerwin R Burow M Kliebenstein DJ (2016) The Defense Metabolite AllylGlucosinolate Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway Front Plant Sci 7774
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Gonzalez-Jorge S Ha SH Magallanes-Lundback M Gilliland LU Zhou A Lipka AE Nguyen YN Angelovici R Lin H Cepela J Little HBuell CR Gore MA Dellapenna D (2013) Carotenoid cleavage dioxygenase4 is a negative regulator of beta-carotene content inArabidopsis seeds Plant Cell 25 4812-4826
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Halkier BA Gershenzon J (2006) Biology and biochemistry of glucosinolates Annu Rev Plant Biol 57 303-333Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana theglucosinolates Plant Physiology 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Chen YZ Pang QY He Y Zhu N Branstrom I Yan XF Chen S (2012) Proteomics and metabolomics of Arabidopsis responses toperturbation of glucosinolate biosynthesis Mol Plant 5 1138-1150
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Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Mol Plant 7 814-828
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Frerigmann H Gigolashvili T (2014) MYB34 MYB51 and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsisthaliana Molecular Plant 7 814-828
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Gao J Yu X Ma F Li J (2014) RNA-seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli(Brassica oleracea var italic) PLoS One 9 e88804
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Haughn GW Davin L Giblin M Underhill EW (1991) Biochemical Genetics of Plant Secondary Metabolites in Arabidopsis thaliana TheGlucosinolates Plant Physiol 97 217-226
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Henriques R Bogre L Horvath B Magyar Z (2014) Balancing act matching growth with environment by the TOR signalling pathway JExp Bot 65 2691-2701
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Horton MW Hancock AM Huang YS Toomajian C Atwell S Auton A Muliyati NW Platt A Sperone FG Vilhjaacutelmsson BJ (2012) Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel Nature genetics 44 212
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ireland RJ Lea P J (1999) The enzymes of glutamine glutamate asparagine and aspartate metabolism In SB K ed Plant AminoAcids Biochemistry and Biotechnology Marcel Dekker New York pp 49-109
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jensen LM Kliebenstein DJ Burow M (2015) Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis Front Plant Sci 6 762
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Jones CG Firn RD (1991) On the Evolution of Plant Secondary Chemical Diversity Philosophical Transactions of the Royal Society ofLondon Series B-Biological Sciences 333 273-280
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Katz E Nisani S Yadav BS Woldemariam MG Shai B Obolski U Ehrlich M Shani E Jander G Chamovitz DA (2015) The glucosinolatebreakdown product indole-3-carbinol acts as an auxin antagonist in roots of Arabidopsis thaliana Plant J 82 547-555
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kim S Plagnol V Hu TT Toomajian C Clark RM Ossowski S Ecker JR Weigel D Nordborg M (2007) Recombination and linkagedisequilibrium in Arabidopsis thaliana Nat Genet 39
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ DAuria JC Behere AS Kim JH Gunderson KL Breen JN Lee G Gershenzon J Last RL Jander G (2007)Characterization of seed-specific benzoyloxyglucosinolate mutations in Arabidopsis thaliana Plant J 51 1062-1076
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kliebenstein DJ Kroymann J Brown P Figuth A Pedersen D Gershenzon J Mitchell-Olds T (2001) Genetic control of naturalvariation in Arabidopsis glucosinolate accumulation Plant Physiol 126 811-825
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Donnerhacke S Schnabelrauch D Mitchell-Olds T (2003) Evolutionary dynamics of an Arabidopsis insect resistancequantitative trait locus Proc Natl Acad Sci U S A 100 Suppl 2 14587-14592
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Kroymann J Textor S Tokuhisa JG Falk KL Bartram S Gershenzon J Mitchell-Olds T (2001) A gene controlling variation inArabidopsis glucosinolate composition is part of the methionine chain elongation pathway Plant Physiol 127 1077-1088
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lea PJ Miflin BJ (1974) Alternative route for nitrogen assimilation in higher plants Nature 251 614-616Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Lipka AE Gore MA Magallanes-Lundback M Mesberg A Lin H Tiede T Chen C Buell CR Buckler ES Rocheford T Dellapenna D(2013) Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain G3 3 1287-1299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative Usage of Fixed and Random Effect Models for Powerful and EfficientGenome-Wide Association Studies PLoS Genet 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Liu X Huang M Fan B Buckler ES Zhang Z (2016) Iterative usage of fixed and random effect models for powerful and efficientgenome-wide association studies PLoS genetics 12 e1005767
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Loudet O Chaillou S Camilleri C Bouchez D Daniel-Vedele F (2002) Bay-0times Shahdara recombinant inbred line population a powerfultool for the genetic dissection of complex traits in Arabidopsis Theoretical and Applied Genetics 104 1173-1184
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Bano F Morgner M (1994) Genetics of aliphatic glucosinolates I Side chain elongation in Brassica napus andArabidopsis thaliana Heredity 72 290-299
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Magrath R Mithen R (1993) Maternal Effects on the Expression of Individual Aliphatic Glucosinolates in Seeds and Seedlings of
Brassica-Napus Plant Breeding 111 249-252Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Majumdar R Barchi B Turlapati SA Gagne M Minocha R Long S Minocha SC (2016) Glutamate Ornithine Arginine Proline andPolyamine Metabolic Interactions The Pathway Is Regulated at the Post-Transcriptional Level Front Plant Sci 7 78
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Malinovsky FG Thomsen MF Nintemann SJ Jagd LM Bourgine B Burow M Kliebenstein DJ (2017) An evolutionarily young defensemetabolite influences the root growth of plants via the ancient TOR signaling pathway Elife 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Bielecka M Gakiere B Krueger S Rinder J Kempa S Morcuende R Scheible WR Hesse H Hoefgen R (2006) Effect ofsulfur availability on the integrity of amino acid biosynthesis in plants Amino Acids 30 173-183
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nikiforova VJ Kopka J Tolstikov V Fiehn O Hopkins L Hawkesford MJ Hesse H Hoefgen R (2005) Systems rebalancing ofmetabolism in response to sulfur deprivation as revealed by metabolome analysis of Arabidopsis plants Plant Physiol 138 304-318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Jorgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531-534
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Nour-Eldin HH Andersen TG Burow M Madsen SR Joslashrgensen ME Olsen CE Dreyer I Hedrich R Geiger D Halkier BA (2012)NRTPTR transporters are essential for translocation of glucosinolate defence compounds to seeds Nature 488 531
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Okumoto S Funck D Trovato M Forlani G (2016) Editorial Amino Acids of the Glutamate Family Functions beyond PrimaryMetabolism Front Plant Sci 7 318
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Parkin I Magrath R Keith D Sharpe A Mithen R Lydiate D (1994) Genetics of Aliphatic Glucosinolates 2 Hydroxylation of AlkenylGlucosinolates in Brassica-Napus Heredity 72 594-598
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
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Petersen BL Chen S Hansen CH Olsen CE Halkier BA (2002) Composition and content of glucosinolates in developing Arabidopsisthaliana Planta 214 562-571
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proceedings of the NationalAcademy of Sciences 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Riedelsheimer C Lisec J Czedik-Eysenberg A Sulpice R Flis A Grieder C Altmann T Stitt M Willmitzer L Melchinger AE (2012)Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize Proc Natl Acad Sci U S A 109 8872-8877
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Rohr F Ulrichs C Mewis I (2009) Variability of aliphatic glucosinolates in Arabidopsis thaliana (L) - Impact on glucosinolate profile andinsect resistance Journal of Applied Botany and Food Quality-Angewandte Botanik 82 131-135
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schmid M Davison TS Henz SR Pape UJ Demar M Vingron M Scholkopf B Weigel D Lohmann JU (2005) A gene expression map ofArabidopsis thaliana development Nat Genet 37 501-506
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Schwender J Shachar-Hill Y Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus J Biol Chem281 34040-34047
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Google Scholar Author Only Title Only Author and Title
Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Amin N Schwikowski B Ideker T (2003) Cytoscape a softwareenvironment for integrated models of biomolecular interaction networks Genome Res 13 2498-2504
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Skokut TA Wolk CP Thomas J Meeks JC Shaffer PW (1978) Initial organic products of assimilation of [N]ammonium and [N]nitrate bytobacco cells cultured on different sources of nitrogen Plant Physiol 62 299-304
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Burow M Rowe HC Kliebenstein DJ Halkier BA (2010) A Complex Interplay of Three R2R3 MYB Transcription FactorsDetermines the Profile of Aliphatic Glucosinolates in Arabidopsis1[C][W][OA] Plant Physiology 153 348-363
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Sonderby IE Hansen BG Bjarnholt N Ticconi C Halkier BA Kliebenstein DJ (2007) A systems biology approach identifies a R2R3 MYBgene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates PLoS One 2 e1322
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Team R (2014) A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria2014URL(httpswww R-project org)
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Textor S Bartram S Kroymann J Falk KL Hick A Pickett JA Gershenzon J (2004) Biosynthesis of methionine-derived glucosinolatesin Arabidopsis thaliana recombinant expression and characterization of methylthioalkylmalate synthase the condensing enzyme of thechain-elongation cycle Planta 218 1026-1035
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Velasco P Soengas P Vilar M Cartea ME del Rio M (2008) Comparison of glucosinolate profiles in leaf and seed tissues of differentBrassica napus crops Journal of the American Society for Horticultural Science 133 551-558
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Verslues PE Lasky JR Juenger TE Liu TW Kumar MN (2014) Genome-wide association mapping combined with reverse geneticsidentifies new effectors of low water potential-induced proline accumulation in Arabidopsis Plant Physiol 164 144-159
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wen W Li D Li X Gao Y Li W Li H Liu J Liu H Chen W Luo J Yan J (2014) Metabolome-based genome-wide association study ofmaize kernel leads to novel biochemical insights Nat Commun 5 3438
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ (2007) Linking metabolic QTLs with network and cis-eQTLscontrolling biosynthetic pathways PLoS Genet 3 1687-1701
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Winter D Vinegar B Nahal H Ammar R Wilson GV Provart NJ (2007) An Electronic Fluorescent Pictograph browser for exploringand analyzing large-scale biological data sets PLoS One 2 e718
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Angelovici R (2018) A High-throughput absolute-level quantification of protein-bound amino acids in seeds Curr Protoc PlantBiol e20084
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Yobi A Batushansky A Oliver MJ Angelovici R (2019) Adaptive responses of amino acid metabolism to the combination of desiccationand low nitrogen availability in Sporobolus stapfianus Planta 249 1535-1549
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Garneau MG Majumdar R Grant J Tegeder M (2015) Improvement of pea biomass and seed productivity by simultaneousincrease of phloem and embryo loading with amino acids Plant J 81 134-146
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Zhang L Tan Q Lee R Trethewy A Lee YH Tegeder M (2010) Altered xylem-phloem transfer of amino acids affects metabolism andleads to increased seed yield and oil content in Arabidopsis Plant Cell 22 3603-3620
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title
Ziegler G Terauchi A Becker A Armstrong P Hudson K Baxter I (2013) Ionomic Screening of Field-Grown Soybean Identifies Mutantswith Altered Seed Elemental Composition Plant Genome 6
Pubmed Author and TitleGoogle Scholar Author Only Title Only Author and Title