PART OF A SPECIAL ISSUE ON PLANT NUTRITION Genetic analysis of potassium use efficiency in Brassica oleracea P. J. White 1, *, J. P. Hammond 2 , G. J. King 3 , H. C. Bowen 2 , R. M. Hayden 2 , M. C. Meacham 2 , W. P. Spracklen 2 and M. R. Broadley 4 1 Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, UK, 2 Warwick HRI, University of Warwick, Wellesbourne, Warwick CV35 9EF, UK, 3 Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK and 4 Plant and Crop Sciences Division, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD, UK * For correspondence. E-mail [email protected]Received: 7 July 2009 Returned for revision: 18 August 2009 Accepted: 10 September 2009 Published electronically: 8 October 2009 † Background and Aims Potassium (K) fertilizers are used in intensive and extensive agricultural systems to maxi- mize production. However, there are both financial and environmental costs to K-fertilization. It is therefore important to optimize the efficiency with which K-fertilizers are used. Cultivating crops that acquire and/or utilize K more effectively can reduce the use of K-fertilizers. The aim of the present study was to determine the genetic factors affecting K utilization efficiency (KUtE), defined as the reciprocal of shoot K concentration (1/[K] shoot ), and K acquisition efficiency (KUpE), defined as shoot K content, in Brassica oleracea. † Methods Genetic variation in [K] shoot was estimated using a structured diversity foundation set (DFS) of 376 accessions and in 74 commercial genotypes grown in glasshouse and field experiments that included phosphorus (P) supply as a treatment factor. Chromosomal quantitative trait loci (QTL) associated with [K] shoot and KUpE were identified using a genetic mapping population grown in the glasshouse and field. Putative QTL were tested using recurrent backcross substitution lines in the glasshouse. † Key Results More than two-fold variation in [K] shoot was observed among DFS accessions grown in the glass- house, a significant proportion of which could be attributed to genetic factors. Several QTL associated with [K] shoot were identified, which, despite a significant correlation in [K] shoot among genotypes grown in the glass- house and field, differed between these two environments. A QTL associated with [K] shoot in glasshouse-grown plants (chromosome C7 at 62 . 2 cM) was confirmed using substitution lines. This QTL corresponds to a segment of arabidopsis chromosome 4 containing genes encoding the K þ transporters AtKUP9, AtAKT2, AtKAT2 and AtTPK3. † Conclusions There is sufficient genetic variation in B. oleracea to breed for both KUtE and KUpE. However, as QTL associated with these traits differ between glasshouse and field environments, marker-assisted breeding pro- grammes must consider carefully the conditions under which the crop will be grown. Key words: Arabidopsis, Brassica oleracea, genetics, potassium (K), potassium use efficiency (KUE), quantitative trait loci (QTL), shoot. INTRODUCTION Potassium (K) is an essential mineral element for plant growth, development and fecundity (White and Karley, 2009). It is required in large amounts by crop plants and, because many agricultural soils lack sufficient phytoavailable K for maximal crop production, it is generally supplied as K-fertilizers in both intensive and extensive agricultural systems (Lægreid et al., 1999; Pettigrew, 2008; Rengel and Damon, 2008; Fageria, 2009). However, there are both finan- cial and environmental costs, inherent in the energy required for their production, distribution and application, to the con- sumption of K-fertilizers (Lægreid et al., 1999). In the immediate future, a scarcity of K-fertilizers is unlikely, but unstable energy prices, which affect the mining, distribution and application of K-fertilizers, and the introduction of finan- cial instruments associated with meeting climate change and other environmental targets, will determine their cost, avail- ability and usage. For these reasons, K-fertilizers must be deployed efficiently. Breeding crops that acquire and/or utilize K more effectively is one strategy that could reduce the use of K-fertilizers (Baligar et al., 2001; Trehan, 2005; Pettigrew, 2008; Rengel and Damon, 2008; Fageria, 2009; Szczerba et al., 2009). Agronomic K use efficiency is defined as crop dry matter yield per unit K supplied (g DM g 21 K s ). This is numerically equal to the product of plant K content per unit K supplied (g K g 21 K s ), which is referred to as plant K uptake efficiency (KUpE), and crop yield per unit plant K content (g DM g 21 K), which is referred to as plant K utilization efficiency (KUtE). In general, plant K content can be estimated from shoot K content, and KUtE can then be expressed as the reci- procal of shoot K concentration ([K] shoot ) if the entire shoot is harvested (White et al., 2005). Potassium is the most abundant inorganic cation in plants, comprising up to 10 % of a plant’s dry weight (Watanabe et al., 2007), and [K] shoot is often higher in plants from the Brassicaceae than in those from many other angiosperm families when grown under comparable conditions (Broadley et al., 2004). Variation in [K] shoot has been observed among genotypes of several plant species grown in the same environment (Baligar et al., 2001; Pelletier et al., 2008; Pettigrew, 2008; Rengel and Damon, 2008; Fageria, 2009), # The Author 2009. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: [email protected]Annals of Botany 105: 1199–1210, 2010 doi:10.1093/aob/mcp253, available online at www.aob.oxfordjournals.org by guest on January 13, 2013 http://aob.oxfordjournals.org/ Downloaded from
Transcript
PART OF A SPECIAL ISSUE ON PLANT NUTRITION
Genetic analysis of potassium use efficiency in Brassica oleracea
P. J. White1,*, J. P. Hammond2, G. J. King3, H. C. Bowen2, R. M. Hayden2, M. C. Meacham2, W. P. Spracklen2
and M. R. Broadley4
1Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, UK, 2Warwick HRI, University of Warwick, Wellesbourne,Warwick CV35 9EF, UK, 3Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK and 4Plant and Crop Sciences
Division, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD, UK* For correspondence. E-mail [email protected]
Received: 7 July 2009 Returned for revision: 18 August 2009 Accepted: 10 September 2009 Published electronically: 8 October 2009
† Background and Aims Potassium (K) fertilizers are used in intensive and extensive agricultural systems to maxi-mize production. However, there are both financial and environmental costs to K-fertilization. It is thereforeimportant to optimize the efficiency with which K-fertilizers are used. Cultivating crops that acquire and/orutilize K more effectively can reduce the use of K-fertilizers. The aim of the present study was to determinethe genetic factors affecting K utilization efficiency (KUtE), defined as the reciprocal of shoot K concentration(1/[K]shoot), and K acquisition efficiency (KUpE), defined as shoot K content, in Brassica oleracea.† Methods Genetic variation in [K]shoot was estimated using a structured diversity foundation set (DFS) of 376accessions and in 74 commercial genotypes grown in glasshouse and field experiments that included phosphorus(P) supply as a treatment factor. Chromosomal quantitative trait loci (QTL) associated with [K]shoot and KUpEwere identified using a genetic mapping population grown in the glasshouse and field. Putative QTL were testedusing recurrent backcross substitution lines in the glasshouse.† Key Results More than two-fold variation in [K]shoot was observed among DFS accessions grown in the glass-house, a significant proportion of which could be attributed to genetic factors. Several QTL associated with[K]shoot were identified, which, despite a significant correlation in [K]shoot among genotypes grown in the glass-house and field, differed between these two environments. A QTL associated with [K]shoot in glasshouse-grownplants (chromosome C7 at 62.2 cM) was confirmed using substitution lines. This QTL corresponds to a segmentof arabidopsis chromosome 4 containing genes encoding the Kþ transporters AtKUP9, AtAKT2, AtKAT2 andAtTPK3.† Conclusions There is sufficient genetic variation in B. oleracea to breed for both KUtE and KUpE. However, asQTL associated with these traits differ between glasshouse and field environments, marker-assisted breeding pro-grammes must consider carefully the conditions under which the crop will be grown.
Key words: Arabidopsis, Brassica oleracea, genetics, potassium (K), potassium use efficiency (KUE),quantitative trait loci (QTL), shoot.
INTRODUCTION
Potassium (K) is an essential mineral element for plant growth,development and fecundity (White and Karley, 2009). It isrequired in large amounts by crop plants and, because manyagricultural soils lack sufficient phytoavailable K formaximal crop production, it is generally supplied asK-fertilizers in both intensive and extensive agriculturalsystems (Lægreid et al., 1999; Pettigrew, 2008; Rengel andDamon, 2008; Fageria, 2009). However, there are both finan-cial and environmental costs, inherent in the energy requiredfor their production, distribution and application, to the con-sumption of K-fertilizers (Lægreid et al., 1999). In theimmediate future, a scarcity of K-fertilizers is unlikely, butunstable energy prices, which affect the mining, distributionand application of K-fertilizers, and the introduction of finan-cial instruments associated with meeting climate change andother environmental targets, will determine their cost, avail-ability and usage. For these reasons, K-fertilizers must bedeployed efficiently.
Breeding crops that acquire and/or utilize K more effectivelyis one strategy that could reduce the use of K-fertilizers
(Baligar et al., 2001; Trehan, 2005; Pettigrew, 2008; Rengeland Damon, 2008; Fageria, 2009; Szczerba et al., 2009).Agronomic K use efficiency is defined as crop dry matteryield per unit K supplied (g DM g21 Ks). This is numericallyequal to the product of plant K content per unit K supplied(g K g21 Ks), which is referred to as plant K uptake efficiency(KUpE), and crop yield per unit plant K content (g DM g21
K), which is referred to as plant K utilization efficiency(KUtE). In general, plant K content can be estimated fromshoot K content, and KUtE can then be expressed as the reci-procal of shoot K concentration ([K]shoot) if the entire shoot isharvested (White et al., 2005).
Potassium is the most abundant inorganic cation in plants,comprising up to 10 % of a plant’s dry weight (Watanabeet al., 2007), and [K]shoot is often higher in plants from theBrassicaceae than in those from many other angiospermfamilies when grown under comparable conditions (Broadleyet al., 2004). Variation in [K]shoot has been observed amonggenotypes of several plant species grown in the sameenvironment (Baligar et al., 2001; Pelletier et al., 2008;Pettigrew, 2008; Rengel and Damon, 2008; Fageria, 2009),
# The Author 2009. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved.
including Brassica oleracea kales and collards (Kopsell et al.,2004; Vilar et al., 2008), Brassica rapa (Wu et al., 2008),Brassica napus (Brennan and Bolland, 2007; Damon et al.,2007; Rose et al., 2007; Bhardwaj and Mamama, 2009) andBrassica juncea (Shi et al., 2004).
This paper describes the genetic variation in, and chromoso-mal quantitative trait loci (QTL) associated with, [K]shoot andtherefore KUtE in Brassica oleracea, a major edible cropworldwide that includes several morphologically distinctsubtaxa, such as acephala (kale/collards), alboglabra (orientalkale), botrytis (cauliflower), capitata (cabbage), gemmifera(Brussels sprout), gongylodes (kohlrabi), italica (broccoli/calabrese), sabauda (Savoy cabbage) and sabellica (bore-cole/curly kale), in which the entire shoot is generally har-vested (Broadley et al., 2008). Brassica oleracea is a diploidplant species for which significant genetic resources are avail-able, including (1) a diversity foundation set (DFS) thought tocontain most of the common allelic variation within thisspecies (Broadley et al., 2008), (2) genetic mapping popu-lations suitable for the identification of chromosomal lociaffecting quantitative traits (Sebastian et al., 2000; Pinket al., 2008), (3) collections suitable for isolating mutants inspecific genes (Himelblau et al., 2009), (4) extensivegenome sequence (Schranz et al., 2007) and (5) routine tech-niques for genetic transformation (Cogan et al., 2004). Inaddition, the genus Brassica contains the closest crop relativesof the model plant Arabidopsis thaliana and genomic relation-ships between A. thaliana, B. oleracea (Brassica C genome)and other Brassica crops, such as B. rapa (A genome),B. napus (AC genome) and the B genome-containing mustards(B. nigra, B. juncea, B. carinata), are becoming increasinglywell characterized (Parkin et al., 2005; Schranz et al., 2006,2007). Ultimately, this knowledge of comparative genomicswill facilitate the identification of genes affecting KUpE andKUtE among the Brassicaceae and the breeding of Brassicacrops that utilize K-fertilizers more efficiently.
MATERIALS AND METHODS
Plant material
The plant material used in this study consisted of: (1) a DFS of376 Brassica oleracea L. accessions, selected from the .4300accessions held in the Warwick-HRI Genetic Resources Unitand thought to contain most of the common allelic variationwithin this species (Broadley et al., 2008); (2) a set of 74 com-mercial genotypes sampled to represent the distinct majorB. oleracea morphotypes in current or recent cultivation innorthern Europe (Broadley et al., 2008); (3) the 90 mostinformative lines from the ‘AGDH’ genetic mapping popu-lation, to enable the identification of QTL associated withshoot K concentration in B. oleracea. The AGDH populationwas generated through anther culture of the F1 of a crossbetween a DH rapid-cycling accession of B. oleracea var.alboglabra (A12DHd) and a DH accession derived from anF1 hybrid calabrese cultivar, ‘Green Duke’, B. oleracea var.italica (GDDH33). A linkage map of 906 cM for the AGDHmapping population has been developed, with a mean distancebetween marker loci of 1.92+ 3.49 cM, such that approx.90 % of the genome is within 5 cM of a marker (Sebastian
et al., 2000; Broadley et al., 2008; Pink et al., 2008). Therewere physical limitations on the number of AGDH lines thatcould be grown in these experiments. Hence, a subset ofAGDH lines was selected that maximized the range of recom-bination break points, as well as the marker scoring density.This subset has been shown to be adequate for the successfuldetection of QTL for shoot mineral concentrations (Broadleyet al., 2008; Hammond et al., 2009). (4) A set of 20 recurrentbackcross substitution lines (the ‘AGSL’ population), eachcontaining chromosomal segments of GDDH33 introgressedinto the A12DHd background, was used to validate thelocation of QTL in the AGDH population (Rae et al., 1999;Broadley et al., 2008). (5) A common reference set of geno-types consisting of A12DHd, GD33DH and eight commercialB. oleracea cultivars allowed comparisons between exper-iments (Greenwood et al., 2005, 2006; Broadley et al., 2008;Hammond et al., 2009).
Field and glasshouse experiments
Plants were grown in a series of field and glasshouse exper-iments at Wellesbourne, UK (5281203000N, 183603900W, 45 mabove sea level), each temporally arranged over severaloccasions, as described by Broadley et al. (2008). Eachoccasion represented an independent experimental run, con-taining a subset of the accessions being screened. Sets ofplants were grown with different applications of P-fertilizersto investigate the effect of plant growth rate on [K]shoot.Although most plants were grown successfully, not all of theaccessions sown in each experiment survived to harvest,especially in the field. The experiments were as follows. (1)A glasshouse experiment (GE1), in which three replicates ofthe 376 DFS accessions and nine replicates of the 74 commer-cial cultivars were sown over six occasions between June,2003 and July, 2004 in a 40-m2 ‘Cambridge’-type glasshousecompartment that was set to maintain temperatures of 24 8C byday and 15 8C at night using automatic vents and supplemen-tary heating. Daylight was supplemented by artificial lighting(Son-T 400-W Philips phi 0.85i, Groote, Noort, TheNetherlands) to maintain 16 h light per day above a photo-synthetically active radiation (PAR) of 300 W m22. Plantswere grown in compressed polystyrene pots (dimensions11 � 11 � 12 cm; Desch Plantpak Ltd, Mundon, Maldon,UK), filled to a depth of approx. 0.5 cm below the rim witha peat-based compost. The compost contained either5.25 mg L21 (low [P]ext) or 15.75 mg L21 (high [P]ext) ofadded P following the incorporation of 0.075 and 0.225 g ofsieved (500 mm) single superphosphate [SSP, CaSO4 þ
Ca(H2PO4)2, containing 7 % P] per litre of compost(Greenwood et al., 2005). Other nutrients were incorporatedin the potting-mix in sufficient amounts to prevent mineraldeficiencies. Analysis of compost samples gave Olsen’s extrac-table P values of 9.2 and 20.2 mg L21 for low and high [P]ext
composts, respectively. The average water-extractable K con-centration in these composts was 183+ 3 mg L21 (mean+s.e.m., n ¼ 34), resembling soils of high K-fertility. Plantshoots were sampled at similar developmental stages, 39, 47,49, 49, 42 and 37 d after sowing on the six occasions. (2) Afield experiment (FE1) conducted in Wharf Ground,Wellesbourne, between May, 2004 and May, 2005 in which
White et al. — Genetics of potassium use efficiency in Brassica oleracea1200
by guest on January 13, 2013http://aob.oxfordjournals.org/
three replicates of the 74 commercial cultivars were sown overthree occasions at four [P]ext using an alpha design (Pattersonand Williams, 1976). The Wharf Ground soil is a sandy loamInceptisol in the Wick series of English classification(Whitfield, 1974). Supplementary irrigation was supplied viaoscillating lines when required, and pesticide applicationswere made according to horticultural best-practice. The[P]ext treatments were imposed by incorporating triple super-phosphate [TSP, Ca(H2PO4)2, containing 21 % P] equivalentto 0, 298, 1125 or 2713 kg TSP ha21 to a depth of 0.10 musing a power harrow (Greenwood et al., 2005). Analysis ofsoil samples (to a depth of 30 cm) from these plots gaveaverage Olsen’s extractable P values of 40.7, 39.6, 81.7 and152.1 mg P L21 for the four [P]ext treatments. Unfertilizedsoils had ammonium nitrate-extractable K concentrations of59+ 1.8 mg L21 (mean+ s.e.m., n ¼ 40) and there was anannual overall dressing of 289 kg N ha21 and 250 kg K2Oha21 to the Wharf Ground field. Plant shoots were sampledafter 101, 97 and 93 d growth on the three occasions. Thesetimings were chosen to represent pre-commercial maturity.(3) A second glasshouse experiment (GE2), in which ninereplicates of the 90 AGDH lines plus the A12DHd andGDDH33 parents of the AGDH population and eight referencecommercial cultivars were sown over three occasions betweenFebruary and July, 2005 in the same glasshouse compartmentand at the same two [P]ext as GE1 using an alpha design. Plantshoots were sampled at a comparable growth stage, after 50, 50and 34 d growth on the three occasions. (4) A second fieldexperiment (FE2), conducted on Wharf Ground betweenMarch and May, 2006, in which three replicates of 72 geno-types (62 AGDH lines, A12DHd, GDDH33 and eight refer-ence commercial cultivars) were sown at the same four [P]ext
levels, and with the same amounts of N and K fertilizer, asFE1 using an alpha design. Plant shoots were sampled after105 d growth. (5) A third glasshouse experiment (GE3),undertaken between March and May, 2006, in which threereplicates of 30 genotypes (20 AGSLs, A12DHd, GDDH33and eight reference commercial cultivars) were sown in thesame glasshouse compartment and at the same two [P]ext asGE1 and GE2. Plant shoots were sampled 39 d after sowing.
Potassium analysis
In all experiments, shoot fresh weight (FW), comprising allabove-ground biomass, was recorded immediately upon har-vesting and shoot dry matter (DM) was determined after oven-drying at 60 8C for 72 h. For GE1, [K]shoot was determined bya commercial foliar analysis laboratory (Yara Phosyn Ltd,Pocklington, York, UK). For all other experiments, [K]shoot
was determined at Warwick-HRI using inductively coupledplasma emission spectrometry (JY Ultima 2, Jobin YvonLtd, Stanmore, Middlesex, UK) following the digestion ofdried plant material using the micro Kjeldahl method(Bradstreet, 1965).
Data analysis
Data were analysed using REML procedures in GenStat(Release 9.1.0.147, VSN International, Oxford, UK) to allo-cate sources of variation and estimate accession means for
individual experiments (Patterson and Thompson, 1971;Robinson, 1987). QTL mapping was performed with QTLCartographer 2.0 (Wang et al., 2004), using the compositeinterval mapping (CIM) option as described previously(Broadley et al., 2008; Hammond et al., 2009). Summary stat-istics of [K]shoot for the DFS, commercial cultivars and AGDHlines are expressed as mean+ s.e. for n genotypes.
RESULTS
Species-wide genetic variation in shoot K concentrationin B. oleracea
Species-wide genetic variation in [K]shoot of B. oleracea wasquantified in glasshouse (GE1) and field (FE1) experimentsthat included substrate P concentration ([P]ext) as a treatmentfactor (Fig. 1). There was substantial variation in [K]shoot
among the 343 B. oleracea genotypes of the DFS grown inGE1, among the 75 commercial cultivars grown in GE1 andamong the 72 commercial cultivars grown in FE1.
In GE1, 18.3 % of the total variation in [K]shoot was attrib-uted to the accession, [P]ext and [P]ext � accession terms(Table 1). The genetic variance component was highly signifi-cant (P , 0.001), accounting for 16.8 % of the total variationin [K]shoot (Table 1). [K]shoot was greater at high [P]ext for mostaccessions (Fig. 2A), but [P]ext � accession interactions werenot significant (P . 0.05). In general, therefore, [K]shoot ofB. oleracea genotypes did not respond differently to altered[P]ext. The [K]shoot of B. oleracea genotypes grown in GE1ranged from 2.72 to 6.56 %DM at low [P]ext and from 2.06to 6.94 %DM at high [P]ext (Figs 1 and 2A). [K]shoot differedbetween subtaxa, with botrytis (cauliflower) and gongylodes(kohlrabi) subtaxa having highest values and sabellica (bore-cole/curly kale), acephala (kale/collards) and italica (broc-coli/calabrese) the lowest values (Fig. 1). Averaged acrossboth [P]ext, [K]shoot among DFS accessions ranged from 2.92to 6.64 %DM (n ¼ 343) and the [K]shoot of commercial culti-vars ranged from 3.27 to 5.94 %DM (n ¼ 75). Thus, theextent of variation in [K]shoot observed among commercial cul-tivars was 72 % of the species-wide variation in [K]shoot. Theeffect of shoot DM accumulation on [K]shoot was tested withinsubtaxa, to avoid confounding effects of shoot morphology(data not shown). These relationships were rarely significant.At low [P]ext, [K]shoot was significantly (Fprob , 0.05) inver-sely correlated with shoot DM only within the alboglabra sub-taxon. At high [P]ext, [K]shoot was significantly (Fprob , 0.05)inversely correlated with shoot DM within the acephala andcapitata subtaxa.
There was substantial variation in [K]shoot among the 72commercial cultivars grown in FE1 (Figs 1 and 2C).Variance components attributed to accession, [P]ext and[P]ext � accession terms accounted for 16.4 % of the total vari-ation in [K]shoot (Table 1). Genetic variance components for[K]shoot were highly significant (P , 0.001) in FE1 andaccounted for 10.5 % of the total variation. The [P]ext � acces-sion interactions for [K]shoot were marginally significant (P ,0.05). There were significant positive correlations between[K]shoot at different [P]ext among the 72 commercial cultivarsgrown in FE1 (e.g. Fig. 2C; P , 0.001). However, in contrastto values in GE1, the [K]shoot of most genotypes grown in FE1
White et al. — Genetics of potassium use efficiency in Brassica oleracea 1201
by guest on January 13, 2013http://aob.oxfordjournals.org/
was greater at the lowest [P]ext than at the highest [P]ext
(Fig. 2C). In general, the [K]shoot of plants grown in the fieldwere lower than the [K]shoot of plants grown in the glasshouse,which might, in part, be attributed to differences in available Kand/or the presence of competing cations between the twoenvironments. Averaged across all [P]ext, [K]shoot ofB. oleracea genotypes grown in FE1 ranged from 1.72 to2.70 %DM, and [K]shoot were significantly (P , 0.001) posi-tively correlated among the 70 cultivars grown successfullyin experiments GE1 and FE1 (Fig. 3A), indicating that
genotypic differences in [K]shoot were consistent betweenfield and glasshouse environments. However, the [K]shoot ofall commercial cultivars was higher in GE1 than in FE1(Fig. 3A). Although there was a significant (P ¼ 0.0011) nega-tive relationship between [K]shoot and shoot DM among com-mercial cultivars when grown at high [P]ext in the glasshouse,no significant relationships were obtained between [K]shoot andshoot DM among commercial cultivars when grown at low[P]ext in the glasshouse or at any [P]ext in the field (data notshown).
8A
B C
7
6
5
4
3
2
7
Glasshouse Field Glasshouse Field
Sho
ot K
con
cent
ratio
n (%
DM
)S
hoot
K c
once
ntra
tion
(%D
M)
6
5
4
3
2
1
B. oler
acea
DFS
sabe
llica
acep
hala
italic
a
albog
labra
saba
uda
tronc
huda
gem
mife
ra
capit
ata
gong
ylode
s
botry
tis
FI G. 1 Shoot K concentrations of Brassica oleracea genotypes represented in (A) the structured diversity foundation set (DFS) in glasshouse experiment one(GE1; n ¼ 343), in B. oleracea subtaxa surveyed in GE1 (sabellica, n ¼ 6; acephala, n ¼ 40; italica, n ¼ 89; alboglabra, n ¼ 13; sabauda, n ¼ 15; tronchuda,n ¼ 17; gemmifera, n ¼ 43; capitata, n ¼ 63; gongylodes, n ¼ 23; and botrytis, n ¼ 108), in (B) the commercial cultivars grown in GE1 and field experiment one(FE1; n ¼ 75 and n ¼ 72, respectively), and in (C) lines from the AGDH genetic mapping population grown in GE2 and FE2 (n ¼ 92 and n ¼ 62, respectively).Data are means of genotypes, averaged across all external P concentrations. The boundaries of the box closest to and furthest from zero indicate the 25th and 75thpercentiles, respectively. The solid and dotted lines within the box indicate the median and mean, respectively. Error bars indicate the 10th and 90th percentiles.
Circles indicate genotypes with extreme shoot K concentrations.
White et al. — Genetics of potassium use efficiency in Brassica oleracea1202
by guest on January 13, 2013http://aob.oxfordjournals.org/
QTL affecting shoot K concentration in B. oleracea
Chromosomal QTL associated with [K]shoot were mappedusing an informative subset of 90 DH lines from the AGDHpopulation in both glasshouse (GE2) and field (FE2) exper-iments that included [P]ext as a treatment factor (Table 2).These loci were confirmed and resolved using substitutionlines in a further glasshouse experiment (GE3).
A significant (P ¼ 0.014) positive correlation was observedfor [K]shoot among the nine reference B. oleracea accessionsgrown in both GE1 and GE2 (Fig. 3B), suggesting that theseexperiments were comparable. In GE2, the variance com-ponents attributed to accession, [P]ext and [P]ext � accessionterms amounted to 25.8 % of the total variation in [K]shoot
(Table 1). The genetic variance component was highly signifi-cant (P , 0.001) and accounted for 22.2 % of the total var-iance in [K]shoot. However, in contrast to DFS accessionsand commercial cultivars grown in GE1, [P]ext � accessioninteractions were marginally significant (P , 0.05) for[K]shoot in GE2, despite the highly significant (P , 0.001)positive relationship between [K]shoot at low and high [P]ext
among the genotypes of the AGDH population (Fig. 2B).[K]shoot varied significantly among the 92 DH lines andparents of the AGDH population studied in GE2 and, as wasobserved for the DFS and commercial cultivars studied inGE1, [K]shoot was greater at high [P]ext for most AGDH lines(Figs 1 and 2C). The [K]shoot of the DH lines grown in GE2ranged from 3.93 to 6.50 %DM at low [P]ext and from 3.90to 6.23 %DM at high [P]ext (Figs 1 and 2C). Averaged acrossboth [P]ext, the range of [K]shoot among the 92 B. oleracea gen-otypes sampled in GE2 (4.12–6.36 %DM) suggested that thispopulation approximated 60 % of the species-wide variation in[K]shoot observed in the glasshouse.
A significant (P ¼ 0.039, n ¼ 28) positive correlation wasobserved for [K]shoot among the seven reference B. oleraceaaccessions successfully grown in both FE1 and FE2(Fig. 3C), suggesting that these experiments were comparable.The variance components attributed to accession, [P]ext and[P]ext � accession terms amounted to 27.6 % of the total vari-ation in [K]shoot in FE2 (Table 1). The genetic variance com-ponent was highly significant (P , 0.001) and accounted for23.7 % of the total variation in [K]shoot (Table 1). Averagedover all [P]ext, there was a significant (P , 0.001) positive cor-relation in the [K]shoot of the 62 genotypes from the AGDHpopulation grown in FE2 and GE2 (Fig. 3D), which is consist-ent with the significant positive correlation in [K]shoot of the 70commercial cultivars grown in FE1 and GE1 (Fig. 3A). Inaddition, [K]shoot of all the AGDH population was lower inFE2 than in GE2 (Fig. 3D), as was observed for the commer-cial cultivars grown in FE1 and GE1 (Fig. 3A). The [P]ext �
accession interactions were not significant (P . 0.05) inFE2. Thus, [K]shoot did not respond differently to altered[P]ext among the AGDH lines grown in FE2. Shoot K concen-tration varied significantly among the 62 lines of the AGDHpopulation studied in FE2 and, as was observed for the com-mercial cultivars studied in FE1, [K]shoot was greater at low[P]ext for most of the AGDH population (Figs 1 and 2).There were also significant positive correlations between[K]shoot at different [P]ext among the 62 lines of the AGDHpopulation grown in FE2 (e.g. Fig. 2D; P , 0.001).
TA
BL
E1.
Vari
ance
com
ponen
tsanaly
ses
of
shoot
Kco
nce
ntr
ati
ons
(%D
M)
of
Bra
ssic
agen
oty
pes
gro
wn
inth
eth
ree
gla
sshouse
exper
imen
ts(G
E1,
GE
2and
GE
3)
and
the
two
fiel
dex
per
imen
ts(F
E1,
FE
2)
GE
1F
E1
GE
2F
E2
GE
3
DF
San
dF
1cu
ltiv
ars
F1
cult
ivar
sA
GD
Hac
cess
ions
AG
DH
acce
ssio
ns
AG
SL
acce
ssio
ns
Var
iance
com
ponen
t%
var
iance
,occ
asio
n19. 5
25. 7
32. 1
%var
iance
,occ
asio
n/(
ben
ch,
repli
cate
)7. 3
4. 1
4. 7
12. 3
%var
iance
,occ
asio
n/(
ben
ch,
repli
cate
)/(r
un,
blo
ck)
7. 7
3. 1
2. 9
6. 5
%var
iance
,occ
asio
n/r
epli
cate
/blo
ck/m
ain_plo
t19. 7
12. 2
10. 0
%var
iance
,ac
cess
ion
(VA
)16. 8
10. 5
22. 2
23. 7
39. 3
%var
iance
,[P
] ext
1. 5
5. 1
2. 2
2. 0
14. 2
%var
iance
,[P
] ext/ac
cess
ion
0. 0
0. 8
1. 4
1. 9
-1. 9
%var
iance
,re
sidual
47. 2
30. 9
22. 2
43. 7
48. 3
Fix
edte
rmW
d.f
.x
2W
d.f
.x
2W
d.f
.x
2W
d.f
.x
2W
d.f
.x
2
acce
ssio
n1434
428
,0
. 001
867
71
,0
. 001
936
99
,0. 0
01
512
71
,0. 0
01
235
30
,0. 0
01
[P] e
xt
55
1,
0. 0
01
26
3,
0. 0
01
89
1,
0. 0
01
53
0. 1
63
32
1,
0. 0
01
[P] e
xt/ac
cess
ion
382
424
0. 9
3259
213
0. 0
18
154
99
,0. 0
01
239
213
0. 1
03
28
30
0. 5
77
Sta
ndar
der
rors
of
dif
fere
nce
sof
mea
nA
ver
age
0. 4
60. 0
80
. 20
0. 1
70. 2
0M
axim
um
0. 8
20. 0
90
. 21
0. 1
80. 2
0M
inim
um
0. 2
60. 0
80
. 20
0. 1
60. 1
6
White et al. — Genetics of potassium use efficiency in Brassica oleracea 1203
by guest on January 13, 2013http://aob.oxfordjournals.org/
The [K]shoot of the 62 AGDH lines grown in FE2 ranged from2.04 to 4.11 %DM with the lowest rate of P-fertilizer appli-cation and from 2.05 to 3.57 %DM with the highest rate ofP-fertilizer application (Figs 1 and 2D). Highly significant(P , 0.001) negative relationships were observed between[K]shoot and shoot Ca and Mg concentrations in the AGDHpopulation grown in the glasshouse (Fig. 4), and negativerelationships were also observed between [K]shoot and shootCa (P ¼ 0.0018) and Mg (P ¼ 0.176) in the field (data notshown).
In both glasshouse and field experiments, A12DHd had aconsistently higher [K]shoot than GDDH33 (e.g. Fig. 5).Significant (log-likelihood of there being one vs. no QTL,LOD . 3) or indicative (LOD . 2) QTL associated with[K]shoot were detected on six of the nine linkage groups ofB. oleracea (Table 2). No QTL associated with [K]shoot weredetected on chromosomes C5, C6 or C8. The observed QTLaccounted for 83 % of the additive genetic variance component(VA) for [K]shoot for plants grown in the glasshouse (GE2) and44 % of the VA in [K]shoot for plants grown in the field (FE2).However, no QTL associated with [K]shoot were identified inboth environments, despite the significant positive correlationin [K]shoot among genotypes grown in the glasshouse andfield (Fig. 3). In GE2, there was a positive additive effect ofthe A12DHd allele on [K]shoot at QTL on chromosomes C3,C4 and C7, and a negative effect of the A12DHd alleleon [K]shoot at QTL on chromosomes C1 and C9 (Table 2).
In FE2, there was a positive effect of the A12DHd allele on[K]shoot at QTL on chromosome C2 and a negative effect ofthe A12DHd allele on [K]shoot at the QTL on chromosomeC9 (Table 2).
The presence of QTL associated with [K]shoot in glasshouse-grown plants was tested using the AGSL substitution lines, inwhich segments of GDDH33 are introgressed into theA12DHd background (Rae et al., 1999; Broadley et al.,2008; Hammond et al., 2009). As was observed in previousexperiments in the glasshouse, A12DHd had a higher[K]shoot than GDDH33 (Fig. 5). Of the AGSL lines screened,AGSL118 and ASGL119 were potentially informative for aputative QTL associated with [K]shoot on chromosome C1(91.2 cM) and AGSL121, AGSL122 and ASGL129 werepotentially informative for a putative QTL associated with[K]shoot on chromosome C9 (33.5 cM), although the QTL liewithin chromosomal regions whose parental identity has notyet been attributed in the AGSL lines, and AGSL165 andAGSL168 were informative for a putative QTL associatedwith [K]shoot on chromosome C7 (62.2 cM). The phenotypesof AGSL118, ASGL119, AGSL121, AGSL122 andASGL129 were similar to A12DHd and therefore did notconfirm the putative QTL associated with [K]shoot on chromo-some C1 (91.2 cM) or C9 (33.5 cM). However, the [K]shoot ofAGSL165 and AGSL168 (line 27) were lower than A12DHd,apparently confirming the putative QTL associated with[K]shoot on chromosome C7 (62.2 cM).
8
6
4
2
00
0
1
2
3
4
0 1 2 3 4
0
1
2
3
5
4
0
Shoot K concentration (%DM) at low [P]ext
Sho
ot K
con
cent
ratio
n (%
DM
) at
hig
h [P
] ext
Sho
ot K
con
cent
ratio
n (%
DM
) at
hig
h [P
] ext
Shoot K concentration (%DM) at low [P]ext
1 2 3 54
2
B (GE2) D (FE2)
A (GE1) C (FE1)
4 6 8
8
6
4
2
00 2 4 6 8
FI G. 2 Shoot K concentrations of Brassica oleracea genotypes grown at either low or high external P concentrations ([P]ext) in (A) glasshouse experiment one(GE1) and (B) GE2, and at the lowest and highest P-fertilizer application rate ([P]ext) in (C) field experiment one (FE1) and (D) FE2. Among the 418 genotypescompared in GE1, the following subtaxa were represented: acephala (n ¼ 40), alboglabra (13), botrytis (108), capitata (63), gemmifera (43), gongylodes (23),italica (89), sabauda (15), sabellica (6), tronchuda (17) and one accession with no subtaxon assigned. Among the 72 commercial cultivars compared in FE1, thefollowing subtaxa were represented: acephala (n ¼ 6), alboglabra (1), botrytis (12), capitata (16), gemmifera (7), gongylodes (6), italica (10), sabauda (8) andsabellica (6). Ninety accessions from the AGDH genetic mapping population plus the parents of this population, A12DHd and GDDH33, were compared in GE2
and 61 accessions from the AGDH genetic mapping population plus A12DHd were compared in FE2.
White et al. — Genetics of potassium use efficiency in Brassica oleracea1204
by guest on January 13, 2013http://aob.oxfordjournals.org/
Agronomic K use efficiency is the product of KUpE andKUtE of a crop. The KUtE of a plant can be estimated as
the reciprocal of [K]shoot. There is therefore significantgenetic variation in KUtE, and QTL associated with KUtE cor-respond to QTL associated with [K]shoot (Table 2). The KUpEof a plant can be estimated as the shoot K content and calcu-lated as the product of shoot DM and [K]shoot. When grown inthe glasshouse or field, there is considerable variation in KUpEamong genotypes of B. oleracea. For example, in GE1 KUpEvaried between 1.7 and 62.5 mg K per plant when grown atlow P and between 6.1 and 108.9 mg K per plant whengrown at high P (Fig. 6A). Subtaxa differed in KUpE, withbotrytis and italica subtaxa having the lowest KUpE, andcapitata, sabauda and tronchuda subtaxa having the highestKUpE. KUpE was higher in commercial cultivars than inthe DFS when grown in the glasshouse at low [P]ext (30.8+0.73 mg K per plant, n ¼ 79, vs. 27.8+ 0.47 mg K perplant, n ¼ 340) or high [P]ext (71.4+ 1.76 mg K per plant,n ¼ 79, vs. 59.9+ 1.00 mg K per plant, n ¼ 341). In FE1,KUpE varied between 138.3 and 368.0 mg K per plantamong commercial cultivars when grown at the lowestP-fertilizer application and between 110.3 and 300.3 mg Kper plant when grown at the highest P-fertilizer application(data not shown). The KUpE of commercial cultivars was sig-nificantly (P ¼ 0.0012, n ¼ 70) correlated between glasshouseand field experiments performed with an adequate P supply(data not shown). Several QTL associated with KUpE wereidentified using the AGDH population, which differed
Low [P]ext
High [P]ext
39·6 mg P L–1
3·0A B
DC
2·5
2·0
1·5
1·0
0·5
0·0
0·0 0·5 1·0 1·5 2·0 2·5 3·0
00
1
1
2
2
3
3
4
4
5
5
6
6
7 0 1 2 3 4 5 6
00
2
1
2
3
4
4 86
4
3
2
1
0
40·7 mg P L–1
152·1 mg P L–181·7 mg P L–1
Shoot K concentration (%DM) in GE1 Shoot K concentration (%DM) in GE1
Shoot K concentration (%DM) in FE1
Sho
ot K
con
cent
ratio
n (%
DM
) in
FE
2
Sho
ot K
con
cent
ratio
n (%
DM
) in
FE
2
Sho
ot K
con
cent
ratio
n (%
DM
) in
FE
1
Sho
ot K
con
cent
ratio
n (%
DM
) in
GE
2
Shoot K concentration (%DM) in GE2
FI G. 3 (A) Shoot K concentrations averaged across all P-fertilizer application rates ([P]ext) of 70 Brassica oleracea genotypes grown in both field experiment one(FE1) and glasshouse experiment one (GE1). The fitted line represents a significant linear regression (y ¼ 0.178x þ 1.396, R ¼ 0.402, Fprob , 0.001). (B) ShootK concentrations of nine reference B. oleracea genotypes grown in both GE1 and GE2 at low or high [P]ext as indicated. The fitted line represents a significantlinear regression (y ¼ 0.508x þ 2.293, R ¼ 0.57, Fprob ¼ 0.014, n ¼ 18). (C) Shoot K concentrations of seven reference B. oleracea genotypes grown in both FE1and FE2 at [P]ext of 40.7, 39.6, 81.7 and 152.1 mg P L21 as indicated. The fitted line represents a linear regression (y ¼ 0.563x þ 1.586, R ¼ 0.391, Fprob ¼0.039, n ¼ 28). (D) Shoot K concentrations averaged across all [P]ext of 62 accessions from the AGDH genetic mapping population grown in both field
(FE2) and glasshouse (GE2) environments. The fitted line represents a significant linear regression (y ¼ 0.360x þ 1.117, R ¼ 0.514, Fprob , 0.001).
TABLE 2. Chromosomal quantitative trait loci (QTL) associatedwith shoot K concentration (%DM) of Brassica oleracea grownin glasshouse experiment two (GE2) and field experiment two
The QTL analysis is based on data for 90 lines (GE2) or 61 lines (FE2)from the AGDH genetic mapping population averaged across all Ptreatments.
* Log-likelihood of there being one vs. no QTL.† Additive effect of female (var. alboglabra) alleles.‡ Proportion of additive genetic variance component (VA) explained by
QTL.
White et al. — Genetics of potassium use efficiency in Brassica oleracea 1205
by guest on January 13, 2013http://aob.oxfordjournals.org/
between glasshouse and field environments (Table 3). None ofthese coincided with QTL for KUtE in this population.
DISCUSSION
Genetic factors affecting shoot K concentration in B. oleracea
This study has demonstrated up to 3.4-fold variation in [K]shoot
among B. oleracea genotypes when grown under identicalconditions (Fig. 1), a significant proportion of which couldbe attributed to genetic factors (Table 1). This is consistentwith previous studies showing 1.4- to 2.3-fold variation in[K]shoot among B. oleracea kales and collards grown togetherin the glasshouse or field (Kopsell et al., 2004; Vilar et al.,2008). The [K]shoot of B. oleracea genotypes correlatedbetween glasshouse and field environments (Fig. 3A, D), andwas relatively insensitive to P supply (Table 1, Fig. 2).When grown in the glasshouse, the variation in [K]shoot
among commercial cultivars was about 72 % of the species-wide variation in [K]shoot, and the variation in [K]shoot
among AGDH lines was about 60 % of the species-wide vari-ation in [K]shoot (Fig. 1). This suggests an opportunity to alter[K]shoot through the introduction of alleles from the wider genepool into elite germplasm.
Several QTL associated with [K]shoot were identified usingthe AGDH population, although these differed between glass-house and field environments (Table 2). It is most likely thatenvironmental factors affecting, for example, plant growthrates, rooting volume or differences in K availability deter-mined the most influential physiological traits and thereforethe QTL associated with [K]shoot in the glasshouse and fieldenvironments. It is unlikely that the different QTL arose asan artefact from the different numbers of AGDH linesemployed for mapping QTL in glasshouse and field environ-ments. One of the QTL associated with [K]shoot in glasshouse-grown plants (on chromosome C7 at 62.2 cM) was confirmedfrom the phenotypes of AGSL165 and AGSL168 (Fig. 5). Thislocus falls largely in a region of co-linearity with a section ofarabidopsis chromosome 4 (Parkin et al., 2005). The closestgenetic marker on the B. oleracea map is an orthologue ofarabidopsis AtIRT1 (At4g19690) at 61.3 cM, and a gene encod-ing the putative plasma membrane Kþ transporter AtKUP9(At4g19960) is in the vicinity of AtIRT1 (White and Karley,
A B C
Sho
ot K
con
cent
ratio
n (%
DM
)
Shoot Ca concentration (%DM) Shoot Mg concentration (%DM)Shoot Na concentration (%DM)
FI G. 4. Relationships between shoot K concentration ([K]shoot) and (A) shoot Ca concentration ([Ca]shoot), (B) shoot Mg concentration ([Mg]shoot) and (C) shootNa concentration ([Na]shoot) averaged across both P-fertilizer application rates ([P]ext) for the 90 accessions from the AGDH genetic mapping population grown inglasshouse experiment two (GE2). The fitted lines represent significant linear relationships between [K]shoot and [Ca]shoot (y ¼ 6.728 2 0.887x, R ¼ 0.436,Fprob , 0.001), [K]shoot and [Mg]shoot (7.265 – 4.121x, R ¼ 0.482, Fprob , 0.001), and [K]shoot and [Na]shoot (y ¼ 5.534 � þ3.857, R ¼ 0.296, Fprob ¼ 0.004).
6·0A
B
C1 C9 C7
5·5
5·0
Sho
ot K
con
cent
ratio
n (%
DM
)S
hoot
K c
once
ntra
tion
(%D
M)
4·5
4·0
6·0
5·5
5·0
4·5
4·0
A12DHd
GDDH33
AGSL118
AGSL119
AGSL121
AGSL122
AGSL129
AGSL165
AGSL168
FI G. 5. Shoot K concentrations ([K]shoot) in A12DHd (A alleles), GDDH33(G alleles), and the AGSL substitution lines AGSL118, ASGL119,AGSL121, AGSL122, ASGL129, AGSL165 and AGSL168 in which chromo-somal segments of GDDH33 are introgressed into the A12DHd background(Rae et al., 1999; Broadley et al., 2008; Hammond et al., 2009). LinesAGSL118 and ASGL119 were potentially informative for a putative QTL onchromosome C1 (91.2 cM) in which the G alleles increase [K]shoot. LinesAGSL121, AGSL122 and ASGL129 were potentially informative for a puta-tive QTL associated with [K]shoot on C9 (33.5 cM) in which the G allelesincrease [K]shoot. Lines AGSL165 and AGSL168 were informative for a puta-tive QTL associated with [K]shoot on C7 (62.2 cM) in which the G allelesdecrease [K]shoot. Data show means+ s.e.m. of three replicates of each geno-type grown in glasshouse experiment three (GE3) with (A) low P or (B) high Psupply. Horizontal lines indicate the mean [K]shoot of the parental lines
AD12DHd and GDDH33.
White et al. — Genetics of potassium use efficiency in Brassica oleracea1206
by guest on January 13, 2013http://aob.oxfordjournals.org/
2009). Genes encoding the Kþ channels AtAKT2 (At4g22200),AtKAT2 (At4g18290) and the putative Kþ channel AtTPK3(At4g18160) are also in close proximity to AtIRT1 (Whiteand Karley, 2009). Similarly, this marker is present within asequenced B. rapa BAC (KBrB085J21), which contains anorthologue of AtKUP9. The arabidopsis genome containsapproximately 32 000 genes and about 450 of these arelocated between At4g18160 and At4g222000. Based on atwo-way contingency table, the probability that four of the111 genes encoding Kþ-transporters are found in this region(P ¼ 0.048) suggests that it contains more Kþ-transportersthan would be expected by chance (Karley and White, 2009).To confirm and resolve QTL associated with [K]shoot tosmaller candidate regions a further backcrossing programmewould now be appropriate using a subset of the AGSL lines.
No QTL associated with [K]shoot in the AGDH populationobserved in either the glasshouse or the field co-localizedwith any QTL associated with shoot DM accumulation orshoot P, Mg or Ca concentrations (Broadley et al., 2008;Hammond et al., 2009), despite highly significant (P ,0.001) negative relationships between [K]shoot and shoot Caand Mg concentrations in these plants in the glasshouse(Fig. 4). Similarly, no QTL associated with [K]shoot in theAGDH population observed in either the glasshouse or thefield co-localized with any QTL associated with shoot Na con-centration (Table 4), despite the significant (P ¼ 0.0042) posi-tive correlation between [K]shoot and shoot Na concentrationamong AGDH lines assayed in the glasshouse (Fig. 4C) andthe significant (P ¼ 0.008) negative correlation between[K]shoot and shoot Na concentration among AGDH linesassayed in the field (data not shown). Nor did any QTL associ-ated with [K]shoot co-localize with any QTL associated withaspects of seedling vigour previously identified in this popu-lation (Bettey et al., 2000). No QTL associated with [K]shoot
in the AGDH population co-localized with any QTL associ-ated with leaf N concentration in another B. oleracea geneticmapping population (NGDH) grown in the glasshouse(Hall et al., 2005), nor did any QTL associated with [K]shoot
0·5
0·00 20 40 60 80 100 120
2·5Y
ield
(g
DM
)Y
ield
(g
DM
)K
UtE
(g
DM
mg–
1 K
)
KUtE (g DM mg–1 K)
KUpE (mg K plant–1 )
KUpE (mg K plant–1 )
1·5
2·0
A
B
C
1·0
0·5
0·0
0·06
0·06
0·05
0·05
0·04
0·04
0·03
0·03
0·02
0·02
0·01
0·01
0·00
0·00
0 20 40 60 80 100 120
2·5
1·5
2·0
1·0
FI G. 6. Relationships between shoot biomass and (A) potassium uptake effi-ciency (KUpE), expressed as plant K content, and (B) potassium utilisationefficiency (KUtE), expressed as the reciprocal of shoot K concentration,among B. oleracea genotypes assayed in glasshouse experiment one (GE1)with adequate P supply (high [P]ext). The fitted line in A represents a signifi-cant linear relationship between plant biomass and plant K content (y ¼0.019x þ 0.156, R ¼ 0.904, Fprob , 0.001, n ¼ 420). (C) Relationshipbetween KUtE and KUpE among B. oleracea genotypes assayed in the GE1with adequate P supply (high [P]ext). The fitted line represents a significantlinear relationship between KUtE and KUpE (y ¼ 0.025 2 0.000053x, R ¼
0.314, Fprob , 0.001, n ¼ 420).
TABLE 3. Chromosomal quantitative trait loci (QTL) associatedwith Kþ uptake efficiency (KUpE) of Brassica oleracea grown inglasshouse experiment two (GE2) and field experiment two
The QTL analysis is based on data for 90 lines (GE2) or 61 lines (FE2)from the AGDH genetic mapping population averaged across all Ptreatments.
* Log-likelihood of there being one vs. no QTL.† Additive effect of female (var. alboglabra) alleles.‡ Proportion of additive genetic variance component (VA) explained by
QTL.
White et al. — Genetics of potassium use efficiency in Brassica oleracea 1207
by guest on January 13, 2013http://aob.oxfordjournals.org/
identified in the AGDH population co-localize with any of theQTL for the 17 morphological and developmental traits scoredin the NGDH population (Sebastian et al., 2002). Thus, itwould appear that the QTL associated with [K]shoot reportedhere were not associated with any QTL associated with plantgrowth rate or morphology, nor were they the consequenceof pleiotropic effects of a non-specific QTL.
Significant genetic variation in [K]shoot has also beenobserved among arabidopsis accessions, and genetic variationin [K]shoot among a recombinant inbred population of arabi-dopsis developed from a cross between the Landsberg erecta(Ler) and Cape Verde Island (CVI) accessions has allowedseveral QTL associated with this trait to be mapped (Haradaand Leigh, 2006). Four QTL associated with [K]shoot expressedon a fresh weight basis were mapped to chromosomes 2 (at40 cM), 4 (at 43 cM) and 5 (at 82 and 106 cM), and threeQTL associated with [K]shoot in dry matter were mapped tochromosomes 3 (at 0 cM), 4 (at 43 cM) and 5 (at 106 cM).None of these QTL co-localized with QTL associated witheither FW or DM accumulation, suggesting that [K]shoot andbiomass accumulation were genetically independent underthe environmental conditions in which these plants weregrown. However, the QTL on chromosome 2 co-localizedwith a QTL for seed K concentration occasionally observedin this population (Waters and Grusak, 2008) and the QTLon the bottom of chromosome 3 co-localized with one ofseveral QTL associated with seed K concentration in boththis and three other genetic mapping populations of arabidop-sis (Vreugdenhil et al., 2004; Ghandilyan et al., 2009). Onchromosome 5 the QTL at 82 cM co-localized with a QTLfor seed K concentration occasionally observed in two othergenetic mapping populations of arabidopsis (Waters andGrusak, 2008; Ghandilyan et al., 2009), and the QTL onchromosome 5 at 106 cM co-localized with a QTL associatedwith shoot Cs concentration expressed on a fresh weight basisin the Ler � CVI population (Payne et al., 2004). Candidategenes within these chromosomal QTL include many putativecation transporters, including AtAKT1, AtAKT6, AtKAT1,AtSKOR, AtCNGC1, AtCNGC5, AtCNGC6, AtCNGC14,AtTPK1, AtTPK2, AtKCO3, AtHAK5, AtKEA5 and
AtNHX3 (Harada and Leigh, 2006). Recently, large-scaleionomic profiling programmes have collected data on [K]shoot
for many arabidopsis accessions and for several arabidopsisgenetic mapping populations (Baxter et al., 2007). Rapid pro-gress in linkage mapping and association genetics in arabidop-sis (Nordborg and Weigel, 2008), together with the use ofcomparative genomic information (Parkin et al., 2005;Schranz et al., 2006, 2007), will facilitate the transfer ofknowledge of QTL and genes affecting [K]shoot between arabi-dopsis and other species in the Brassicaceae.
Potassium use efficiency in B. oleracea
The efficiency with which K-fertilizers are used in crop pro-duction is of both commercial and environmental importance.Considerable variation in both KUpE and KUtE was observedamong genotypes of B. oleracea when grown in eitherthe glasshouse or the field (Fig. 6). Several QTL associatedwith KUpE (Table 3) and KUtE (1/[K]shoot, Table 2) wereidentified using the AGDH population, but these QTL differedbetween glasshouse and field environments, suggesting thatthey are influenced profoundly by environmental vagaries.Furthermore, no QTL for KUpE coincided with QTL forKUtE in either environment, and there was a strong negativecorrelation between these traits (Fig. 6C). These observationsimply that several QTL will have to be combined to achieveimproved KUpE and/or KUtE across diverse environments,and that the environmental factors influencing the relativeimportance of specific QTL will have to be defined.
Greater KUpE is generally attributed to better Kþ acqui-sition from the soil solution (Jungk and Claassen, 1997;Baligar et al., 2001; Trehan, 2005; Rengel and Damon,2008; White and Karley, 2009). Theoretical models suggestthat diffusion through, and mass flow of, the soil solution con-tribute most to the delivery of Kþ to the root surface (Jungkand Claassen, 1997). Differences in Kþ acquisition betweengenotypes might therefore be attributed to: (1) the rate of Kþ
uptake across the plasma membrane of root cells, whichreduces the Kþ concentration in the rhizosphere solutionand increases diffusional Kþ fluxes; (2) the release ofnon-exchangeable Kþ by root exudates, which increases Kþ
concentration and availability in the soil solution; (3) the pro-liferation of roots into the soil volume, which increases thearea for Kþ uptake and also reduces the distance required forKþ diffusion and water flow; and (4) the transpiration rate ofthe plant, which drives mass flow of the soil solution to theroot (Jungk and Claassen, 1997; Baligar et al., 2001;Høgh-Jensen and Pedersen, 2003; Trehan, 2005; Rengel andDamon, 2008; White and Karley, 2009). It has been observedthat Brassica genotypes differ greatly in their ability toreduce Kþ concentrations in the rhizosphere (Shi et al.,2004), that members of the Brassicaceae access considerablequantities of soil K from the non-exchangeable fraction(Jungk and Claassen, 1997; Shi et al., 2004), that the identityand quantities of organic acids exuded by roots differ markedlybetween Brassica genotypes (Akhtar et al., 2006, 2008), andthat the growth rate and architecture of the root system differmarkedly between genotypes of B. oleracea (Hammond et al.,2009). Future studies should investigate these properties inB. oleracea genotypes with contrasting KUpE.
TABLE 4. Chromosomal quantitative trait loci (QTL) associatedwith shoot Na concentration (%DM) of Brassica oleracea grownin glasshouse experiment two (GE2) and field experiment two
The QTL analysis is based on data for 90 lines (GE2) or 61 lines (FE2)from the AGDH genetic mapping population averaged across all Ptreatments.
* Log-likelihood of there being one vs. no QTL.† Additive effect of female (var. alboglabra) alleles.‡ Proportion of additive genetic variance component (VA) explained by
QTL.
White et al. — Genetics of potassium use efficiency in Brassica oleracea1208
by guest on January 13, 2013http://aob.oxfordjournals.org/
Greater KUtE, especially at low K supply, can be achievedby better K redistribution within a plant to tissues withimmediate K requirements and/or by improving a plant’sability to maintain appropriate cytoplasmic K concentrations,either by anatomical adaptations or by the substitution of Kþ
for other solutes, such as Ca2þ or Naþ, in the vacuole(Rengel and Damon, 2008; White and Karley, 2009). Futurestudies should investigate these properties in B. oleracea gen-otypes with contrasting KUtE.
There was a highly significant (P , 0.001) negative corre-lation between KUpE and KUtE among B. oleracea genotypesin both the glasshouse and the field (e.g. Fig. 6C). In addition,there was a highly significant (P , 0.001) correlation betweenshoot biomass and KUpE (Fig. 6A), but no relationshipbetween shoot biomass and KUtE (Fig. 6B). This suggeststhat shoot biomass and KUtE are genetically independent.This contrasts with a previous study of 84 canola (B. napus)genotypes, which suggested that growth responses to lowsoil K phytoavailability in glasshouse trials could be deter-mined by either KUpE or KUtE depending upon the genotype(Damon et al., 2007). In their study, Damon et al. (2007)classified canola genotypes as K-efficient based on highvalues for the shoot DM ratio at deficient versus adequateK supply. They observed that growth rates of K-efficient gen-otypes differed considerably at low K supply and concludedthat K-efficient genotypes with high growth rates at lowK supply have the ability to improve yields irrespective ofK supply. Several B. oleracea accessions studied here cansimilarly be identified as having high yields and high KUtEor KUpE when grown with an adequate P supply (Fig. 6).
CONCLUSIONS
Considerable variation in [K]shoot was observed amongB. oleracea genotypes grown in the glasshouse or the field, asignificant proportion of which (between 10 and 25 %) couldbe attributed to genetic factors. This should be sufficient forbreeding for KUtE in B. oleracea. However, althoughseveral QTL associated with [K]shoot were identified usingthe AGDH genetic mapping population, and despite a signifi-cant correlation in [K]shoot among these genotypes grown inthe glasshouse and field, QTL differed between glasshouseand field environments. One of the QTL associated with[K]shoot in glasshouse-grown plants (chromosome C7 at62.2 cM) was confirmed from the phenotypes of AGSL165and AGSL168. This QTL corresponds to a segment of arabi-dopsis chromosome 4 that contains genes encoding theplasma membrane Kþ-transporter AtKUP9 (At4g19960) andthe Kþ channels AtAKT2 (At4g22200), AtKAT2(At4g18290) and AtTPK3 (At4g18160). Agronomic K useefficiency is the product of KUpE and KUtE. In B. oleracea,KUpE correlated strongly with shoot biomass, but KUtE(1/[K]shoot) did not. This implies that KUtE and biomass canbe genetically manipulated independently. In the context ofconventional agriculture, breeding for increased KUtE andKUpE will decrease crop K requirements and K-fertilizerapplications. However, as QTL impacting these traits differbetween glasshouse and field environments, marker-assistedbreeding programmes must consider carefully the conditionsunder which the crop will be grown.
ACKNOWLEDGEMENTS
This work was supported by the UK Biotechnology andBiological Sciences Research Council, the UK Departmentfor Environment, Food and Rural Affairs, and the ScottishGovernment Rural and Environment Research and AnalysisDirectorate.
LITERATURE CITED
Akhtar MS, Oki Y, Adachi T, Murata Y, Khan MHR. 2006. Phosphorusstarvation induced root-mediated pH changes in solubilization and acqui-sition of sparingly soluble P sources and organic acids exudation byBrassica cultivars. Soil Science and Plant Nutrition 52: 623–633.
Akhtar MS, Oki Y, Adachi T. 2008. Genetic variability in phosphorus acqui-sition and utilization efficiency from sparingly soluble P-sources byBrassica cultivars under P-stress environment. Journal of Agronomyand Crop Science 194: 380–392.
Baligar VC, Fageria NK, He ZL. 2001. Nutrient use efficiency in plants.Communications in Soil Science and Plant Analysis 32: 921–950.
Baxter I, Ouzzani M, Orcun S, Kennedy B, Jandhyala SS, Salt DE. 2007.Purdue Ionomics Information Management System. An integrated func-tional genomics platform. Plant Physiology 143: 600–611.
Bettey M, Finch-Savage WE, King GJ, Lynn JR. 2000. Quantitative geneticanalysis of seed vigour and pre-emergence seedling growth traits inBrassica oleracea. New Phytologist 148: 277–286.
Bhardwaj HL, Mamama AA. 2009. Effect of cultivar and growing locationon the mineral composition of canola sprouts. HortScience 44: 508–511.
Bradstreet RB. 1965. The Kjeldahl method for organic nitrogen. London:Academic Press.
Brennan RF, Bolland MDA. 2007. Comparing the potassium requirements ofcanola and wheat. Australian Journal of Agricultural Research 58:359–366.
Broadley MR, Bowen HC, Cotterill HL, et al. 2004. Phylogenetic variationin the shoot mineral concentration of angiosperms. Journal ofExperimental Botany 55: 321–336.
Broadley MR, Hammond JP, King GJ, et al. 2008. Shoot calcium and mag-nesium concentrations differ between subtaxa, are highly heritable, andassociate with potentially pleiotropic loci in Brassica oleracea. PlantPhysiology 146: 1707–1720.
Cogan NOI, Newbury HJ, Oldacres AM, et al. 2004. Identification andcharacterization of QTL controlling Agrobacterium-mediated transientand stable transformation of Brassica oleracea. Plant BiotechnologyJournal 2: 59–69.
Damon PM, Osborne LD, Rengel Z. 2007. Canola genotypes differ in pot-assium efficiency during vegetative growth. Euphytica 156: 387–397.
Fageria NK. 2009. The use of nutrients in crop plants. Boca Raton, FL: CRCPress.
Ghandilyan A, Ilk N, Hanhart C, et al. 2009. A strong effect of growthmedium and organ type on the identification of QTLs for phytate andmineral concentrations in three Arabidopsis thaliana RIL populations.Journal of Experimental Botany 60: 1409–1425.
Greenwood DJ, Stellacci AM, Meacham MC, Broadley MR, White PJ.2005. Phosphorus response components of different Brassica oleraceagenotypes are reproducible in different environments. Crop Science 45:1728–1735.
Greenwood DJ, Stellacci AM, Meacham MC, Mead A, Broadley MR,White PJ. 2006. Relative values of physiological parameters of Presponse of different genotypes can be measured in experiments withonly two P treatments. Plant and Soil 281: 159–179.
Hall NM, Griffiths H, Corlett JA, Jones HG, Lynn J, King GJ. 2005.Relationships between water-use traits and photosynthesis in Brassicaoleracea resolved by quantitative genetic analysis. Plant Breeding 124:557–564.
Hammond JP, Broadley MR, White PJ, et al. 2009. Shoot yield drives phos-phorus use efficiency in Brassica oleracea and correlates with root archi-tecture traits. Journal of Experimental Botany 60: 1953–1968.
Harada H, Leigh RA. 2006. Genetic mapping of natural variation in potass-ium concentrations in shoots of Arabidopsis thaliana. Journal ofExperimental Botany 57: 953–960.
White et al. — Genetics of potassium use efficiency in Brassica oleracea 1209
by guest on January 13, 2013http://aob.oxfordjournals.org/
Himelblau E, Gilchrist EJ, Buono K, et al. 2009. Forward and reverse gen-etics of rapid-cycling Brassica oleracea. Theoretical and AppliedGenetics 118: 953–961.
Høgh-Jensen H, Pedersen MB. 2003. Morphological plasticity by crop plantsand their potassium use efficiency. Journal of Plant Nutrition 26:969–984.
Jungk A, Claassen N. 1997. Ion diffusion in the soil-root system. Advances inAgronomy 61: 53–110.
Karley AJ, White PJ. 2009. Moving cationic minerals to edible tissues:potassium, magnesium, calcium. Current Opinion in Plant Science 12:291–298.
Kopsell DE, Kopsell DA, Lefsrud MG, Curran-Celentano J. 2004.Variability in elemental accumulations among leafy Brassica oleraceacultivars and selections. Journal of Plant Nutrition 27: 1813–1826.
Lægreid M, Bøckman OC, Kaarstad O. 1999. Agriculture, fertilizers andthe environment. Wallingford, UK: CABI Publishing.
Nordborg M, Weigel D. 2008. Next-generation genetics in plants. Nature 456:720–723.
Parkin IAP, Gulden SM, Sharpe AG, et al. 2005. Segmental structure of theBrassica napus genome based on comparative analysis with Arabidopsisthaliana. Genetics 171: 765–781.
Patterson HD, Thompson R. 1971. Recovery of inter-block information whenblock sizes are unequal. Biometrika 58: 545–554.
Patterson HD, Williams ER. 1976. A new class of resolvable incompleteblock designs. Biometrika 63: 83–92.
Payne KA, Bowen HC, Hammond JP, et al. 2004. Natural genetic variationin caesium (Cs) accumulation by Arabidopsis thaliana. New Phytologist162: 535–548.
Pelletier S, Belanger G, Tremblay GF, Virkajarvi P, Allard G. 2008.Timothy mineral concentration and derived indices related to cattle meta-bolic disorders: a review. Canadian Journal of Plant Science 88:1043–1055.
Pettigrew WT. 2008. Potassium influences on yield and quality production formaize, wheat, soybean and cotton. Physiologia Plantarum 133: 670–681.
Pink D, Bailey L, McClement S, et al. 2008. Double haploids, markers andQTL analysis in vegetable brassicas. Euphytica 164: 509–514.
Rae AM, Howell EC, Kearsey MJ. 1999. More QTL for flowering timerevealed by substitution lines in Brassica oleracea. Heredity 83:586–596.
Rengel Z, Damon PM. 2008. Crops and genotypes differ in efficiency of pot-assium uptake and use. Physiologia Plantarum 133: 624–636.
Robinson DL. 1987. Estimation and use of variance components. Statistician36: 3–14.
Rose TJ, Rengel Z, Ma Q, Bowden JW. 2007. Differential accumulation pat-terns of phosphorus and potassium by canola cultivars compared towheat. Journal of Plant Nutrition and Soil Science 170: 404–411.
Schranz ME, Lysak MA, Mitchell-Olds T. 2006. The ABC’s of comparativegenomics in the Brassicaceae: building blocks of crucifer genomes.Trends in Plant Science 11: 535–542.
Schranz ME, Song B-H, Windsor AJ, Mitchell-Olds T. 2007. Comparativegenomics in the Brassicaceae: a family-wide perspective. CurrentOpinion in Plant Biology 10: 168–175.
Sebastian RL, Howell EC, King GJ, Marshall DF, Kearsey MJ. 2000. Anintegrated AFLP and RFLP Brassica oleracea linkage map from two mor-phologically distinct doubled-haploid mapping populations. Theoreticaland Applied Genetics 100: 75–81.
Sebastian RL, Kearsey MJ, King GJ. 2002. Identification of quantitativetrait loci controlling developmental characteristics of Brassica oleraceaL. Theoretical and Applied Genetics 104: 601–609.
Shi W, Wang X, Yan W. 2004. Distribution patterns of available P and K inrape rhizosphere in relation to genotypic difference. Plant and Soil 261:11–16.
Szczerba MW, Britto DT, Kronzucker HJ. 2009. Kþ transport in plants:physiology and molecular biology. Journal of Plant Physiology 166:447–466.
Trehan SP. 2005. Nutrient management by exploiting genetic diversity ofpotato – a review. Potato Journal 32: 1–15.
Vilar M, Cartea ME, Padilla G, Soengas P, Velasco P. 2008. The potentialof kales as a promising vegetable crop. Euphytica 159: 153–165.
Vreugdenhil D, Aarts MGM, Koornneef M, Nelissen H, Ernst WHO.2004. Natural variation and QTL analysis for cationic mineral contentin seeds of Arabidopsis thaliana. Plant, Cell and Environment 27:828–839.
Wang S, Basten CJ, Zeng Z-B. 2004. Windows QTL Cartographer 2.0.Raleigh, NC: Department of Statistics, North Carolina State University.
Watanabe T, Broadley MR, Jansen S, et al. 2007. Evolutionary control ofleaf element composition in plants. New Phytologist 174: 516–523.
Waters BM, Grusak MA. 2008. Quantitative trait locus mapping for seedmineral concentrations in two Arabidopsis thaliana recombinant inbredpopulations. New Phytologist 179: 1033–1047.
White PJ, Karley AJ. 2009. Potassium. In: Hell R, Mendel R. eds. Cellbiology of metals and nutrients in plants. Dordrecht: Springer, in press.
White PJ, Broadley MR, Greenwood DJ, Hammond JP. 2005. Proceedingsof the International Fertiliser Society 568. Genetic modifications toimprove phosphorus acquisition by roots. York, UK: InternationalFertiliser Society.
Whitfield WAD. 1974. The soils of the National Vegetable Research Station,Wellesbourne. In: Report of the National Vegetable Research Station for1973. Stratford-upon-Avon, UK: Herald Press, pp. 21–30.
Wu J, Yuan Y-X, Zhang X-W, et al. 2008. Mapping QTLs for mineralaccumulation and shoot dry biomass under different Zn nutritional con-ditions in Chinese cabbage (Brassica rapa L. ssp. pekinensis). Plantand Soil 310: 25–40.
White et al. — Genetics of potassium use efficiency in Brassica oleracea1210
by guest on January 13, 2013http://aob.oxfordjournals.org/
