Chickpea (Cicer arietinum) is the second most widely grown legume crop after soybean, accounting for a substantial proportion of human dietary nitrogen intake and playing a crucial role in food security in developing countries. We report the∼ 738-Mb draft whole genome shotgun sequence of CDC Frontier, a kabuli chickpea variety, which contains an estimated 28,269 genes. Resequencing and analysis of 90 cultivated and wild genotypes from ten countries identifies targets of both breeding-associated genetic sweeps and breeding-associated balancing selection. Candidate genes for disease resistance and agronomic traits are highlighted, including traits that distinguish the two main market classes of cultivated chickpea—desi and kabuli.

1. From Discovery to Delivery: A
Story of Chickpea
Mahendar Thudi
Senior Scientist (Chickpea Genomics)
Theme - Genomics and Trait Discovery
Research Program - Genetic Gains
ICRISAT, India

2. Contents
Genomic resources
Genome, germplasm sequencing, markers, genetic maps
Trait mapping
QTL-mapping, GWAS, QTL-seq, MutMap
Integration in breeding

3. Samples:
- 5 wild species
- 25 landraces
- 60 breeding lines
 Illumina sequencing used
to generate 153.01 Gb
 73.8% of the genome is
captured in scaffolds
 Genome analysis predicted
28,269 genes
 High levels of synteny
observed between
chickpea and Medicago
 > 81,845 SSRs and 4.4
million variants (SNPs and
INDELs)
Nature Biotechnology
Genome sequence and re-sequence

4. Sequencing of germplasm lines
Mapping population parents
Elite varieties (129)
Reference set (300)
MAGIC lines (1200)
Composite collection (3000)
Represent 10 countries – India, Canada, Australia, Ethiopia, Bangladesh, Kenya,
Myanmar, Sudan, Burlgaria, Spain and ICARDA; includes 78 desi and 42 kabuli type
Representing 32 countries; Whole genome re-sequencing (WGRS) of 292
accessions yielded 2.15 Tb of sequence data with the coverage of 5X to 12X
35 parental lines
Multi-parent advanced generation intercross (MAGIC) population was developed
using eight cultivars/elite lines (ICC 4958, ICCV 10, JAKI 9218, JG 11, JG 130,
JG 16, ICCV 97105 and ICCV 00108) re-sequenced at 5.79 - 16.08X coverage
1956 accessions of the ICRISAT core collection
709 ICARDA cultivated genebank accessions,
39 advanced breeding lines and cultivars and
241 trait-specific accessions and
20 wild Cicer species

5. Genome-wide variations identified were used for developing high density SNP
arrays for genetics and breeding applications
Helicoverpa resistant and
susceptible genotypes.
Vijay, IG 72953, ICC 506 and
ICC 3137
Fusarium wilt resistant and
susceptible genotypes. C 104,
JG 62, WR 315 and ICCV
05530
Ascochyta blight resistant
and susceptible
genotypes- ICCV 04516, JG
62, Pb 7 and ICCV 05530
Resequencing parental lines of mapping populations
a b
c

6.  Large number of unique SNPs in varieties released after 2002 indicate an
enhancement in diversity in the primary gene pool as a result of recent breeding
programs
 Grouping of some desi with kabuli in Cluster II was due to inter crossing of desi
and kabuli genotypes and vice versa for enhancing yield and disease resistance.
 Nucleotide diversity in desi varieties (θπ = 0.684 × 10-3) is higher compared to
kabuli (θπ = 0.650 × 10-3) varieties.
 The high diversity among varieties released in RP3 (θπ = 0.684 × 10-3) can be
attributed to involvement of multiple crosses while developing these varieties,
which is evident from the pedigree information, compared to double or triple
crosses in case of varieties of RP2 or predominantly direct selections from local
collections or involving single or double crosses as in case of RP1.
Recent breeding
programs enhanced
diversity

7. Genomic resources
Features Number
Molecular markers
SSR markers >3000
SNP markers >4 million
DArT markers 15360
Maps
Genetic maps 6
Physical map 1
Bin maps 1
Assembly
Genome
CDC
Frontier
Transcriptome 2
Genotyping platforms
KASP assays 2006
GoldenGate 1536
Affymetrix 50K
High density genetic maps

8. Botrytis grey mould
Must have traits in chickpea
Drought tolerance
Fusarium wilt
Ascochyta blight
Heat tolerance
Dry root rot
Product concept 1
Short- to medium-duration
varieties with resistance to root
diseases and tolerance to
drought and heat stresses
Product concept 2
Medium- to long-duration
varieties with resistance to
Ascochyta blight

9. “QTL- hotspot” for drought tolerance
Theor Appl Genet 2014
Accession Root
depth
(cm)
Root
dry wt
(g)
ICC 8261 123.3 1.25
ICC 283 91.6 0.73
ICC 4958 116.6 1.06
ICC 1882 83.9 0.71
ICC 4958 ICC 1882 ICC 283ICC 8261
ICC 4958 × ICC 1882 - 268 RILs
ICC 283 × ICC 8261 - 289 RILs

10. Fine mapping drought using MAGIC population
8 parents: A) ICC 4958, B) JAKI 9218, C) JG 130, D) ICCV 00108,
E) ICCV 97105, F) ICCV 10, G) JG 11, H) JG 16
F1s raised and selfed in green house
SSD method
SSD method
F2s raised and selfed in green house
1200 F3 progenies raised in field
1200 F4 progenies raised in field
1200 F5 progenies will be raised in field
1200 F6 progenies will be raised in field
SSD method
SSD method
Average of year
2013-2014
Year 2014
Year 2013
In collaboration with Drs Gaur, Srinivasan &Rajeev Varshney

11. (a) SNP locus (Ca2_2323872) associated with
yield under rainfed conditions, present in
the candidate gene (Ca_12546) predicted
to be responsible for AB resistance, the
most important yield limiting factor in
Australia, Canada and USA;
(b) Structure of gene Ca_12546 present on
pseudomolecule Ca2;
(c) A total of 17 haplotypes were identified for
this gene. One mutation at position
2323917 in gene (Ca_12546) results in the
loss of start codon that seems to make the
genotype susceptible to AB. Genome-wide scan for yield under heat stress
Novel marker trait associations
based on genome wide SNPs
From 429 lines

12. QTL-seq for identification of genomic regions
for 100 seed weight (100SDW)
ICC 4958
100SDW (26.27g)
ICC 1882
100SDW (12.22g)
RILs
X
15 Low RILs (12.22
to 12.24g)
15 High RILs
(25.27 to 30.80g)
Low
100SDW pool
High
100SDW pool
ICC 4958
Reference guided
assembly
45,053,978
17.10X
Mapping of reads to CDC Frontier
Mapping of bulk reads on the reference guided
assembly for calculation of Δ SNP Index
17,795,370
9.97 X
20,670,924
11.5 X
Plant Biotechnology Journal, 2016
CcLG04CcLG01
CaLG01:
• 3.07 to 4.15 Mb (1.08 Mb)
• 5 SNPs with SNP index of
‘0’ and ‘1’
• SNP Effect: No candidate
genes
CaLG04:
• 11.12 to 13.82 Mb (2.70 Mb)
• 21 SNPs with SNP index of ‘0’
and ‘1’
• SNP Effect: 5 SNPs in 4 genes

13. Mapping dry root rot
resistance
CaLG01 CaLG02 CaLG03 CaLG04
CaLG05 CaLG06 CaLG07 CaLG08
 The cost effective SNP genotyping
platform, comprising of 50,590 high
quality non-redundant SNPs tiled on to
Affymetrix® Axiom® genotyping array was
used for genotyping BG 212 × ICCV
08305
 A high density genetic map with 13,110
SNP markers developed using RIL
population.
 Phenotyped under field conditions as well
as controlled environment facilities for two
season (2015-16 and 2016-17). One QTL
explaining 9% of phenotypic variation was
identified on linkage group 8.
Funded by Government of Karnataka

14. Major QTLs for heat tolerance
RIL population developed using DCP 92-3 (heat
sensitive) and ICCV 92944 (heat tolerant)
Genetic map comprising 788 SNPs
Traits Total QTLs PVE (%)
100 seed weight 4 31.30-37.23
Biological yield/plant 8 6.92-11.16
Cell membrane stability 3 7.75-11.37
Chlorophyll content 7 6.78-33.52
Days to flowering initiation 4 7.48-8.96
Days to maturity 3 8.96-18.13
Days to pod filling 3 9.38-11.97
Days to pod initiation 6 5.88-43.49
Harvest index 8 7.10-39.31
Nitrogen balance index 10 7.39-13.93
Normalized difference vegetation index 16 6.69-34.02
Number of pods per plant 1
Seed yield/plant 4 6.66-18
Dr Uday Jha, ICAR-IIPR, Kanpur

15. Co-localization of Fe and Zn QTLs in
“QTL-hotspot”
Three QTLs for
seed-Fe and Zn
concentration
(CaqFe4.4,
CaqFe4.5 and
CaqZn4.1) were
co-located in the
“QTL-hotspot”
region, on
CaLG04,
Mapping nutritional traits

16. TraitName Linkage
group
PVE(%)
DF CaLG08 14.23
DF50 CaLG07 10.4
DF50 CaLG08 10.46
DF50 CaLG08 10.09
DM CaLG06 13.55
HSW CaLG01 10.43
HI CaLG06 11.11
HI CaLG08 11.05
BGM1 CaLG05 17.86
BMG2 CaLG04 11.14 In collaboration with Drs. Shivali Sharma and Mamta Sharma
Genomic regions for botrytis grey mould resistance
 AB-QTL population developed from
ICCV 10 × BGM 2013-85
 Genotyped using 56 K Affymetrix®
Axiom® genotyping array
 Genetic map spanning 890 cM
developed with 7079 markers

17. MutMap: early flowering and enhanced seed size
Two MutMap F2 populations in field during crop season
2018-19
JRF employed in the project collecting phenotyping data during
crop season 2018-19
Early flowering
No flowering
Early flowering lines setting
pods and maturing early

18. QTL introgression into
elite cultivar JG 11
 A “QTL-hotspot” containing QTLs for several root and
drought tolerance traits was transferred through
marker assisted backcrossing (MABC) into JG 11, a
leading variety of chickpea in India from the donor
parent ICC 4958.
 After undertaking three backcrosses with foreground
and background selection and two rounds of selfing,
29 BC3F2 plants homozygous for two markers
(ICCM0249 and TAA170) were selected
Dr. PM Gaur, ICRISAT

19. Geletu, the first ever MABC variety of chickpea, in
the background of JG 11 released in Ethiopia
 Geletu is developed in genetic
background of JG 11
 Geletu was released for
commercial production for
wider adoption in the dry semi-
arid tropics to moist agro-
ecological zones in Ethiopia
 The variety delivered the
highest grain yield of 3822
kg/ha at Arsi Robe, Ethiopia,
which translates into an yield
advantage of 15% over the
check variety ‘Teketay’ and
78% more than the local check. The Plant Genome, 2013

20. Supporting NARS in development of Super Annigeri 1
(MABC-WR-SA-1) with fusarium wilt resistance
 Super Annigeri 1 has 7% mean yield
advantage over the Annigeri 1 in AICRP-
Chickpea trials.
 Super Annigeri 1 is tolerant to Fusarium wilt
Dr. DM Mannur, UAS-Raichur

21. Entries Yield in kg/ha Disease
reaction
(mean)
Jabalpur Rewa Ganjbasoda Sagar Mean
JG 74 × JG 11551 2587.2 2435.1 2099.3 2157.6 2319.8 2.25
JG 12 × JG 16-3 2587.3 2153.4 2467.6 2386.1 2398.6 2.25
JG 2016-45 2104.1 1885.4 2030.9 1843.8 1966.1 3
JG 2016-43 2053.8 1995.8 1788.7 2012.5 1962.7 3.5
JG 2016-44 2096.2 1850.5 2107.3 1789.6 1960.9 3.25
JG 24 2560.3 2399.8 2450.6 2245.4 2414 2
JG 2016-9605 2534.1 2222.8 2187.1 2489.5 2358.4 2
ICC 96029 × JG11551 2877.9 2228.4 2455.5 2951.4 2628.3 2
JG 74315-14 2631.9 2399.2 2523.2 2644.4 2549.7 2
JG 12 × JG 16 2230.5 2124.4 2155.9 2517.4 2257.1 2
JG 14 × JG 226 2578.6 2369.7 2249.6 2156.3 2338.6 2.5
JG 14 (Check ) 2286.7 1750.3 2006.4 2111.1 2038.6 3.25
JG 74 (Rec. parent ) 1130.4 1258.2 1169.2 955.2 1128.3 8
CV (%) 7.63 7.36 6.45 8.25
CD at 5% 299.22 258.30 231.42 302.37
Evaluation for yield performance of JG 74315-14 in state
varietal trials in four locations has shown 125% and 25%
mean increase in yield over the JG 74 (recurrent parent) and
JG 14 (local check) respectively. The mean disease reaction
of JG 74315-14 was 2, which is highly resistant
Supporting NARS in development of improved JG 74
Dr Anitha Babbar, JNKVV, Jabalpur

22. Supporting
NARS in
developing
Drought
tolerant and
Fusarium wilt
resistant
lines

23. 10 SNP panel for use in breeding
10 SNP panel
comprise
markers for
drought
tolerance,
Fusarium wilt
and Ascochyta
blight resistance
Intertek SNP ID SNP ID Trait
snpCA0001 CKAM2210 Drought
snpCA0022 CKAM2227 Drought
snpCA0023 CKAM2228 Drought
snpCA0004 CKAM2179 Drought
snpCA0006 CKAM2182 Drought
snpCA0021 CKAM2226 Drought
snpCA0018 CKAM2223 Drought
snpCA0166 FW2_30366103 Fusarium wilt
snpCA0168 FW2_30366146 Fusarium wilt
snpCA0027 Ca4_29092572 Ascochyta Blight
NARS partners
Dr. Asnake Fikre – EIAR, Ethiopia
Dr. Bharadwaj- ICAR-IARI
Dr Laxuman –UAS-Raichur
Dr. Veera Jayalakshmi –RARS-Nandyal

24. Towards developing markers for heat tolerance
QTL-seq approach will be deployed
chromo
some
coordinate reference
base
Bulk-A
consensus
base
SNP-index
Bulk-A
Bulk-B
consensus
base
SNP-index
Bulk-B
delta
(SNP-
index)
Ca5 44596025 G G 0 A 1 -1
Ca5 44727346 A A 0 C 1 -1
Ca5 44897927 A A 0 T 1 -1
Ca5 44922136 A A 0 C 1 -1
Ca5 44922140 G G 0 A 1 -1
Ca5 45095467 C C 0 A 1 -1
Ca5 45415468 C C 0 T 1 -1
Major QTLs for heat tolerance are identified based on
mapping population developed at IIPR (DCP92-3 ×
ICCV92944 )
Development of markers for heat tolerance are in
progress.

25. Acknowledgements
Dr. Rajeev Varshney
Chickpea genomics
team
Collaborators
Funding support

26. T
h
a
n
k
Y
o
u
Build back
better
opportunities
by over
coming
challenges