Velu Govindan, Leonardo Crespo-Hererra, Susanne Dreisigacker, Carlos Guzman, S. Mondal and Ravi P. Singh
Global Wheat Program
International Maize and Wheat Improvement Center (CIMMYT)
Email: [email protected]
Getting good genes and high-
throughput phenotyping for nutritious
wheat breeding
Hidden hunger: 2 billion + affected
WHO, 2012
Prevalence of stunting (a) and underweight (b) among >5 yr children
a
b
zinc.org
Increasing demand for nutritious diet – Linking
agriculture and nutrition a paradigm shift
Target areas and Zn breeding target
Baseline Micronutrient
Level in Commercial
Crop 25 ppm
Target 12 ppm
Nutritional quality from genetic resources in wheat: as sources for high zinc and iron
0
20
40
% e
ntr
ies
Zn concentration (ppm)
3-4 fold variation for Zn content in T. dicoccoides from Israel (>300 accessions) in
Zn-enriched area
0
50
100
150
200
Nu
mb
er
of
ac
ce
ss
ion
s
Grain Zn and Fe concentrations (mg/kg)
Zn (mg/kg)
Fe (mg/kg)
Up to 100 ppm Zn in Iranian landraces
0
10
20
30
40
45 50 55 60 70 80 <90
% e
ntr
ies
Grain Zinc (ppm)
T. dicoccon based synthetic wheat with 90 ppm Zn
Diverse genetic resources with high Zn
& Fe identified by 2005 and
subsequent years
Shuttle Breeding: Key to CIMMYT’s widely adapted germplasm
Winter Cycle:
Obregón
(28oN, 38 masl)
November - May.
Diseases: Leaf
Rust, Karnal bunt
Summer Cycle:
Toluca/El Batan
(18.5oN, 2600 masl)
May - October.
*Days getting
longer
•Days getting shorter
* Initial period after sowing
1,200 Km
29º
19º
Annually >400 simple and 300 top-crosses, early generation selection for agronomic traits (F1Top to F4)
selection for Zn and agronomic traits (>10,000 F5 & F6 small plots with repeated checks)
1st year yield trials (1,500 lines) = selection for yield and Zn (F6 & F7)
2nd year multi-env. yield trials (150 lines) = zinc and yield stability
HPAN and HPYT distribution to partners
8
From genetic resources to High zinc wheat in farmers’ fields of South Asia in less than 10 years
Zincol 2016: 1st high zinc wheat in Pakistan with +6 ppm Zn = 2000 tons of seed to be sown in 2016-17 OASIS/SKAUZ//4*BCN/3/2*PASTOR/4/T.SPELTA PI348449/5/BACEU #1/6/WBLL1*2/CHAPIO
Zn-Shakti’ PVS variety: Extra-early with +14 ppm Zn (40% increase) adopted by >40000 farmers in NEPZ
CROC1_/AE.SQUARROSA(210)// INQALAB 91*2/KUKUNA/3/ PBW343*2/KUKUNA
Progenitors:
=
T. durum based SHW
T. dicoccon T.DICOCCONCI9309/AE.SQUARROSA (409)//MUTUS/3/2*MUTUS =
WB02/HPPW-01 Two sister lines (+6 ppm Zn) released for NWPZ of India
=
T. spelta
Identification of novel markers for zinc in wheat
• QTL mapping studies in diverse set of mapping populations
• GWAS analysis – HPAM panel
• Validation in related biparental populations
Technical problems:
• Spatial variability for available Zn in field – large E than G x E
• Grain contamination from soil and metal farm equipment
• High-throughput analysis (XRF vs ICP)
• Needs fairly large population size for mapping & breeding
• False positive QTLs (flowering, height, grain weight) = co-variate
analysis
About 25 QTL were identified on 16 different chromosomes in diploid (T. monococcum and T. boeoticum), tetraploid (T. dicoccoides and T. durum), or hexaploid wheat (T. aestivum) sources
Zinc QTL discovery
Names of mapping population in black = outside CIMMYT research; Red = CIMMYT, Mexico work; Green = BHU/CIMMYT-India research; Orange = Turkish populations mapped at CIMMYT. Figures in parenthesis represents % phenotypic variation explained (PVE)
Chromosome Genom
e 1 2 3 4 5 6 7
A T.monococcum ID-362, T.aestivum, Adana x 70711 (12%)
T. durum Langdon, T. dicoccoides G18-16
T.aestivum, Kenya Swara, (15%) T. aestivum, Adana x 70711 (14%)
T. aestivum Hanxuan 10
T. aestivum Hanxuan 10, T. dicoccoides G18-16, T. aestivum Xiaoyan 54, T. monococcum ID-362
T.spelta H+26 (PI 348449)(7%), T.aestivum Picus/Francolin(8.6%), T. aestivum Seri x SYN (8.3%)
T. aestivum, Adana x 70711 (9%), T.aestivum Lumai, T. dicoccoides G18-16, T. boeoticum Pau 5088, T. monococcum Pau 14087, T.aestivum RAC875-2
B T.aestivum Picus/Francolin(11.5%), Berkut x Krichauff(12%), Adana x 70711 (12%), T. durum Saricanak x MM5/4 (9%),
T.aestivum PBW 343 X Swara (12%), T. aestivum HUW 234 x T.spelta H+26
(PI 348449 (16%), Berkut x Krichauff (24%), T. aestivum, Adana x 70711 (10%)
T. aestivum Seri M82 x SYN (17%), T. aestivum Jing 411, T. aestivum RAC875-2
T.aestivum Picus/Francolin (9%)
T.aestivum, Seri x SYN (8.4%), T.dicoccoides G18-16, T.dicoccoides LDN (DIC-6B), T.durum, Saricanak x MM5/4 (12%)
T. dicoccoides G18-16
D T.aestivum Adana x 70711 (13%)
T.aestivum Picus/Francolin (6%)
T.aestivum Lumai 14
Common QTLs on Chr 1B (12%), 2B (17%), 3A (12-15%), 6B
(11%) & 7A (12%) identified and validated with GWAS
KASP SNP being used to advance and fine-map
Gene discovery for grain Zn in wheat
PBW343/Kenya Swara 177 RILs; PBW343: 50.1 mg/kg; Kenya Swara: 56.1 mg/kg
RILs: 44.0 to 70.6 mg/kg (means)
2B
3A
Seri M82 x SHW population PBW 343 x Kenya Swara population
Hao et al, 2014 Mol breeding
Crespo et al, 2016
MAS for 4B QTL for Seri M82 / SHW
Associated markers converted to more easy-
to-use KASP SNP assays. In collaboration
with S. Dreisigacker
New SNPs are under validation phase.
GWAS panel
HPAM panel of 320 advanced lines and
two checks (PBW343 and Waxwing)
These lines derived from 29-diverse
progenitors
90k Illumina SNP markers were used
for genotyping
The loci on chromosome 2B, 6B, 7B were
stably detected for association with high Zn
Obregon 2015-16
Obregon 2014-15
Two new SHW-derived / T. spelta derived biparental
populations
Findings: SHW-derived / T. spelta derived populations
QTL 7B
+4.5 ppm
GZn
A major QTL on chromosome 7B probably
shared the same locus as the one
identified by GWAS
Next steps: validation in different genetic
background and use in MAS
Identified 45 significant SNPs more than 2
environments – KASP assay to be developed
Genomic prediction for Zn
G A G+A (GxE) (AxE) (GxE)+ (AxE) G+(GxE) A+(AxE)
G+A+(GxE)+ (AxE)
CV1 BHU_2013 0.1942 0.2054 0.2228 0.1577 0.1297 0.1808 0.2123 0.2308 0.2504 DWR_2013 0.3346 0.3390 0.3298 0.3488 0.3866 0.3735 0.3837 0.3944 0.3851 MCO_2012 0.5252 0.4690 0.5052 0.5707 0.4838 0.5548 0.5870 0.5189 0.5660 MCO_2013 0.4552 0.4421 0.4513 0.4383 0.4154 0.4376 0.4590 0.4427 0.4581 PAU_2013 0.2891 0.3433 0.3121 0.3539 0.4043 0.3882 0.3892 0.4230 0.4009
Avg 0.3597 0.3598 0.3642 0.3739 0.3640 0.3870 0.4062 0.4019 0.4121 CV2
BHU_2013 0.3086 0.2971 0.3185 0.1071 0.0778 0.1360 0.3187 0.3156 0.3309 DWR_2013 0.5119 0.5117 0.5168 0.3707 0.4208 0.4043 0.5727 0.5744 0.5847 MCO_2012 0.6859 0.6408 0.6795 0.5617 0.4594 0.5418 0.7123 0.6364 0.6941 MCO_2013 0.6386 0.6069 0.6370 0.4518 0.4185 0.4500 0.6028 0.5683 0.5947 PAU_2013 0.3908 0.4019 0.3986 0.3982 0.4301 0.4275 0.5051 0.4919 0.5068
Avg 0.5071 0.4917 0.5101 0.3779 0.3613 0.3919 0.5423 0.5173 0.5423
Correlations between observed and predicted values for GZn
80% of the AM
panel lines to the
training set and
20% to the testing
set.
Challenges: Field variation of GZn in
Borlaug100 across field Y15-16
0
20
40
60
80
Zn in
pp
m
1 1st HPYT 2010- 3rd HPYT
2012-13 : 4th
season after
ZnSO4
application
2nd HPYT
2011-12: 3rd
season after
ZnSO4
application
23
ppm
5
ppm
23
ppm
GPS based soil imaging would help us to understand pattern
of soil Zn
AgroSat – FYPA company in Mexico provides service for
GPS soil map
Precision Phenotyping
High-throughput analytical methods Paltridge et al.2012
ICP-AES
XRF screening method:
10,000+ samples analyzed annually
lines with low Zn discarded
■ Rapid and low cost technique
■ Non-destructive analysis
How are we overcoming challenges?
• Technical issues
Soil and metal equipment contamination
• New methods to minimize contamination
• 5-10 sec cleaning with rice polisher can remove the external contamination
Zinc localization in wheat grain
Biofortified wheat (Zn- shakti)
Normal variety (Baj)
Guerra & Velu et al. 2017)
Zooming in on wheat grain
Daniel & Søren Husted, Univ. of Copenhagen
HTP- aerial imaging
• Zn-dense wheat have higher levels
of Zn in the peduncle and rachis
just after anthesis (Stomph et al,
2010)
• Peak loading of Zn just after
anthesis (Palmer et al., 2014) –
sampling done 10, 15, 20 DAA
• Use of hyperspectral narrow band
images (400-850 nm region) for
thermal & NDVI can be optimized
• Non-significant to -0.14 (r) of VI
with hyperspectral images.
Climate resilient high zinc wheat
0
5
10
15
20
25
85 90 95 100 105 110 >120%
en
trie
s
Grain yield (% checks mean)
Grain yield under severe droght stress, Obregon 2016-17
Spike length, seed size matters?
Kachu/Solala = Bari Gom 33
(late 2017) in Bangladesh
2NS segment for partial blast
resistance
• Solala – derived from T. polonicum
(long spike Polish wheat crossed
with CIMMYT wheat)
• Mapping populations being
developed using Solala (F4 stage)
Summary • Genetic nature of genes enhancing Zn- QTLs mostly have small to intermediate
effects- mostly additive (may be some interactions).
• Many genomic regions from diverse origins mapped: further progress possible by
accumulating the additive effect QTLs over time.
• Molecular markers along with HTP can facilitate early generation selection would
accelerate breeding efficiency.
• Need appropriate testing program in target countries NARS with precision field
trials – to minimize G x E and to select ‘best bets’
• Translocation and chromosome addition/substitution lines can be utilized
• New SNPs have been developed for Zn, MAB populations are being advanced
Validating usefulness of the new SNPs in breeding and mapping populations
Acknowledgements
GP Singh
Ravish Chatrath
VK Mishra
B Arun
Ramesh
Chand
VS Sohu
NS Bains
GS Mavi
Anju
Mahendru
Yaqub Mujahid
Atiq Rattu,
Qadir Buloch
ND Barma
Farhad James
Stangoulis
Georgia
WH Pfeiffer
P. Virk
M.S. Andersson
Thank you
for your
interest!
