Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea.

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

High confidence QTLs and key genes identified using Meta-QTL analysis for enhancing heat tolerance in chickpea (Cicer arietinum L.).

The rising global temperatures seriously threaten sustainable crop production, particularly the productivity and production of heat-sensitive crops like chickpeas. Multiple QTLs have been identified to enhance the heat stress tolerance in chickpeas, but their successful use in breeding programs remains limited. Towards this direction, we constructed a high-density genetic map spanning 2233.5 cM with 1069 markers. Using 138 QTLs reported earlier, we identified six Meta-QTL regions for heat tolerance whose confidence interval was reduced by 2.7-folds compared to the reported QTLs. Meta-QTLs identified on CaLG01 and CaLG06 harbor QTLs for important traits, including days to 50% flowering, days to maturity, days to flower initiation, days to pod initiation, number of filled pods, visual score, seed yield per plant, biological yield per plant, chlorophyll content, and harvest index. In addition, key genes identified in Meta-QTL regions like Pollen receptor-like kinase 3 (CaPRK3), Flowering-promoting factor 1 (CaFPF1), Flowering Locus C (CaFLC), Heat stress transcription factor A-5 (CaHsfsA5), and Pollen-specific leucine-rich repeat extensins (CaLRXs) play an important role in regulating the flowering time, pollen germination, and growth. The consensus genomic regions, and the key genes reported in this study can be used in genomics-assisted breeding for enhancing heat tolerance and developing heat-resilient chickpea cultivars.

Genetic variation in CaTIFY4b contributes to drought adaptation in chickpea.

Chickpea production is vulnerable to drought stress. Identifying the genetic components underlying drought adaptation is crucial for enhancing chickpea productivity. Here, we present the fine mapping and characterization of 'QTL-hotspot', a genomic region controlling chickpea growth with positive consequences on crop production under drought. We report that a non-synonymous substitution in the transcription factor CaTIFY4b regulates seed weight and organ size in chickpea. Ectopic expression of CaTIFY4b in Medicago truncatula enhances root growth under water deficit. Our results suggest that allelic variation in 'QTL-hotspot' improves pre-anthesis water use, transpiration efficiency, root architecture and canopy development, enabling high-yield performance under terminal drought conditions. Gene expression analysis indicated that CaTIFY4b may regulate organ size under water deficit by modulating the expression of GRF-INTERACTING FACTOR1 (GIF1), a transcriptional co-activator of Growth-Regulating Factors. Taken together, our study offers new insights into the role of CaTIFY4b and on diverse physiological and molecular mechanisms underpinning chickpea growth and production under specific drought scenarios.

Translational Chickpea Genomics Consortium to Accelerate Genetic Gains in Chickpea (Cicer arietinum L.).

The Translational Chickpea Genomics Consortium (TCGC) was set up to increase the production and productivity of chickpea (Cicer arietinum L.). It represents research institutes from six major chickpea growing states (Madhya Pradesh, Maharashtra, Andhra Pradesh, Telangana, Karnataka and Uttar Pradesh) of India. The TCGC team has been engaged in deploying modern genomics approaches in breeding and popularizing improved varieties in farmers' fields across the states. Using marker-assisted backcrossing, introgression lines with enhanced drought tolerance and fusarium wilt resistance have been developed in the genetic background of 10 elite varieties of chickpea. Multi-location evaluation of 100 improved lines (70 desi and 30 kabuli) during 2016-2017 and 2018-2019 enabled the identification of top performing desi and kabuli lines. In total, 909 Farmer Participatory Varietal Selection trials were conducted in 158 villages in 16 districts of the five states, during 2017-2018, 2018-2019, and 2019-2020, involving 16 improved varieties. New molecular breeding lines developed in different genetic backgrounds are potential candidates for national trials under the ICAR-All India Coordinated Research Project on Chickpea. The comprehensive efforts of TCGC resulted in the development and adoption of high-yielding varieties that will increase chickpea productivity and the profitability of chickpea growing farmers.

Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia.

Much of the world's population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.

Integrating genomics for chickpea improvement: achievements and opportunities.

KEY MESSAGE: Integration of genomic technologies with breeding efforts have been used in recent years for chickpea improvement. Modern breeding along with low cost genotyping platforms have potential to further accelerate chickpea improvement efforts. The implementation of novel breeding technologies is expected to contribute substantial improvements in crop productivity. While conventional breeding methods have led to development of more than 200 improved chickpea varieties in the past, still there is ample scope to increase productivity. It is predicted that integration of modern genomic resources with conventional breeding efforts will help in the delivery of climate-resilient chickpea varieties in comparatively less time. Recent advances in genomics tools and technologies have facilitated the generation of large-scale sequencing and genotyping data sets in chickpea. Combined analysis of high-resolution phenotypic and genetic data is paving the way for identifying genes and biological pathways associated with breeding-related traits. Genomics technologies have been used to develop diagnostic markers for use in marker-assisted backcrossing programmes, which have yielded several molecular breeding products in chickpea. We anticipate that a sequence-based holistic breeding approach, including the integration of functional omics, parental selection, forward breeding and genome-wide selection, will bring a paradigm shift in development of superior chickpea varieties. There is a need to integrate the knowledge generated by modern genomics technologies with molecular breeding efforts to bridge the genome-to-phenome gap. Here, we review recent advances that have led to new possibilities for developing and screening breeding populations, and provide strategies for enhancing the selection efficiency and accelerating the rate of genetic gain in chickpea.

Genomics, genetics and breeding of tropical legumes for better livelihoods of smallholder farmers.

Legumes are important components of sustainable agricultural production, food, nutrition and income systems of developing countries. In spite of their importance, legume crop production is challenged by a number of biotic (diseases and pests) and abiotic stresses (heat, frost, drought and salinity), edaphic factors (associated with soil nutrient deficits) and policy issues (where less emphasis is put on legumes compared to priority starchy staples). Significant research and development work have been done in the past decade on important grain legumes through collaborative bilateral and multilateral projects as well as the CGIAR Research Program on Grain Legumes (CRP-GL). Through these initiatives, genomic resources and genomic tools such as draft genome sequence, resequencing data, large-scale genomewide markers, dense genetic maps, quantitative trait loci (QTLs) and diagnostic markers have been developed for further use in multiple genetic and breeding applications. Also, these mega-initiatives facilitated release of a number of new varieties and also dissemination of on-the-shelf varieties to the farmers. More efforts are needed to enhance genetic gains by reducing the time required in cultivar development through integration of genomics-assisted breeding approaches and rapid generation advancement.

Functional Dissection of the Chickpea (Cicer arietinum L.) Stay-Green Phenotype Associated with Molecular Variation at an Ortholog of Mendel's I Gene for Cotyledon Color: Implications for Crop Production and Carotenoid Biofortification.

"Stay-green" crop phenotypes have been shown to impact drought tolerance and nutritional content of several crops. We aimed to genetically describe and functionally dissect the particular stay-green phenomenon found in chickpeas with a green cotyledon color of mature dry seed and investigate its potential use for improvement of chickpea environmental adaptations and nutritional value. We examined 40 stay-green accessions and a set of 29 BC2F4-5 stay-green introgression lines using a stay-green donor parent ICC 16340 and two Indian elite cultivars (KAK2, JGK1) as recurrent parents. Genetic studies of segregating populations indicated that the green cotyledon trait is controlled by a single recessive gene that is invariantly associated with the delayed degreening (extended chlorophyll retention). We found that the chickpea ortholog of Mendel's I locus of garden pea, encoding a SGR protein as very likely to underlie the persistently green cotyledon color phenotype of chickpea. Further sequence characterization of this chickpea ortholog CaStGR1 (CaStGR1, for carietinum stay-green gene 1) revealed the presence of five different molecular variants (alleles), each of which is likely a loss-of-function of the chickpea protein (CaStGR1) involved in chlorophyll catabolism. We tested the wild type and green cotyledon lines for components of adaptations to dry environments and traits linked to agronomic performance in different experimental systems and different levels of water availability. We found that the plant processes linked to disrupted CaStGR1 gene did not functionality affect transpiration efficiency or water usage. Photosynthetic pigments in grains, including provitaminogenic carotenoids important for human nutrition, were 2-3-fold higher in the stay-green type. Agronomic performance did not appear to be correlated with the presence/absence of the stay-green allele. We conclude that allelic variation in chickpea CaStGR1 does not compromise traits linked to environmental adaptation and agronomic performance, and is a promising genetic technology for biofortification of provitaminogenic carotenoids in chickpea.

Resequencing of 429 chickpea accessions from 45 countries provides insights into genome diversity, domestication and agronomic traits.

We report a map of 4.97 million single-nucleotide polymorphisms of the chickpea from whole-genome resequencing of 429 lines sampled from 45 countries. We identified 122 candidate regions with 204 genes under selection during chickpea breeding. Our data suggest the Eastern Mediterranean as the primary center of origin and migration route of chickpea from the Mediterranean/Fertile Crescent to Central Asia, and probably in parallel from Central Asia to East Africa (Ethiopia) and South Asia (India). Genome-wide association studies identified 262 markers and several candidate genes for 13 traits. Our study establishes a foundation for large-scale characterization of germplasm and population genomics, and a resource for trait dissection, accelerating genetic gains in future chickpea breeding.

Super Annigeri 1 and improved JG 74: two Fusarium wilt-resistant introgression lines developed using marker-assisted backcrossing approach in chickpea (Cicer arietinum L.).

Annigeri 1 and JG 74 are elite high yielding desi cultivars of chickpea with medium maturity duration and extensively cultivated in Karnataka and Madhya Pradesh, respectively. Both cultivars, in recent years, have become susceptible to race 4 of Fusarium wilt (FW). To improve Annigeri 1 and JG 74, we introgressed a genomic region conferring resistance against FW race 4 (foc4) through marker-assisted backcrossing using WR 315 as the donor parent. For foreground selection, TA59, TA96, TR19 and TA27 markers were used at Agricultural Research Station, Kalaburagi, while GA16 and TA96 markers were used at Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur. Background selection using simple sequence repreats (SSRs) for the cross Annigeri 1 × WR 315 in BC1F1 and BC2F1 lines resulted in 76-87% and 90-95% recurrent parent genome recovery, respectively. On the other hand, 90-97% genome was recovered in BC3F1 lines in the case of cross JG 74 × WR 315. Multilocation evaluation of 10 BC2F5 lines derived from Annigeri 1 provided one superior line referred to as Super Annigeri 1 with 8% increase in yield and enhanced disease resistance over Annigeri 1. JG 74315-14, the superior line in JG 74 background, had a yield advantage of 53.5% and 25.6% over the location trial means in Pantnagar and Durgapura locations, respectively, under Initial Varietal Trial of All India Coordinated Research Project on Chickpea. These lines with enhanced resistance and high yield performance are demonstration of successful deployment of molecular breeding to develop superior lines for FW resistance in chickpea.

Co-localization of genomic regions associated with seed morphology and composition in a desi chickpea (Cicer arietinum L.) population varying in seed protein concentration.

KEY MESSAGE: Major QTL on LG 1 and 3 control seed filling and seed coat development, thereby affecting seed shape, size, color, composition and weight, key determinants of crop yield and quality. A chickpea (Cicer arietinum L.) population consisting of 189 recombinant inbred lines (RILs) derived from a cross between medium-protein ICC 995 and high-protein ICC 5912 genotypes of the desi market class was analyzed for seed properties. Seed from the parental lines and RILs was produced in four different environments for determination of seed shape (SS), 100-seed weight (100-SW), protein (PRO) and starch (STA) concentration. Polymorphic genetic markers for the population were identified by Genotyping by Sequencing and assembled into a 522.5 cM genetic map. Phenotype data from the different growth environments were analyzed by QTL mapping done by single and multi-environment analyses and in addition, single marker association mapping. The analyses identified in total 11 QTL, of which the most significant (P < 0.05) loci were located on LG 1 (q-1.1), LG 2 (q-2.1), LG 3 (q-3.2, q-3.3), LG 4 (q-4.2), and LG 5 (q-5.1). STA was mostly affected by q-1.1, which explained 19.0% of the phenotypic variance for the trait. The largest QTL effects were demonstrated by q-3.2 that explained 52.5% of the phenotypic variances for 100-SW, 44.3% for PRO, and 14.6% for SS. This locus was also highly associated with flower color (COL; 95.2% explained) and showed q-3.2 alleles from the ICC 5912 parent conferred the blue flower color and production of small, round seeds with relatively high protein concentration. Genes affecting seed filling at q-1.1 and seed coat development at q-3.2, respectively, were considered to underlie differences in seed composition and morphology in the RIL population.

Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea.

Genomic selection (GS) by selecting lines prior to field phenotyping using genotyping data has the potential to enhance the rate of genetic gains. Genotype × environment (G × E) interaction inclusion in GS models can improve prediction accuracy hence aid in selection of lines across target environments. Phenotypic data on 320 chickpea breeding lines for eight traits for three seasons at two locations were recorded. These lines were genotyped using DArTseq (1.6 K SNPs) and Genotyping-by-Sequencing (GBS; 89 K SNPs). Thirteen models were fitted including main effects of environment and lines, markers, and/or naïve and informed interactions to estimate prediction accuracies. Three cross-validation schemes mimicking real scenarios that breeders might encounter in the fields were considered to assess prediction accuracy of the models (CV2: incomplete field trials or sparse testing; CV1: newly developed lines; and CV0: untested environments). Maximum prediction accuracies for different traits and different models were observed with CV2. DArTseq performed better than GBS and the combined genotyping set (DArTseq and GBS) regardless of the cross validation scheme with most of the main effect marker and interaction models. Improvement of GS models and application of various genotyping platforms are key factors for obtaining accurate and precise prediction accuracies, leading to more precise selection of candidates.

Molecular Mapping of QTLs for Heat Tolerance in Chickpea.

Chickpea (Cicer arietinum L.), a cool-season legume, is increasingly affected by heat-stress at reproductive stage due to changes in global climatic conditions and cropping systems. Identifying quantitative trait loci (QTLs) for heat tolerance may facilitate breeding for heat tolerant varieties. The present study was aimed at identifying QTLs associated with heat tolerance in chickpea using 292 F8-9 recombinant inbred lines (RILs) developed from the cross ICC 4567 (heat sensitive) × ICC 15614 (heat tolerant). Phenotyping of RILs was undertaken for two heat-stress (late sown) and one non-stress (normal sown) environments. A genetic map spanning 529.11 cM and comprising 271 genotyping by sequencing (GBS) based single nucleotide polymorphism (SNP) markers was constructed. Composite interval mapping (CIM) analysis revealed two consistent genomic regions harbouring four QTLs each on CaLG05 and CaLG06. Four major QTLs for number of filled pods per plot (FPod), total number of seeds per plot (TS), grain yield per plot (GY) and % pod setting (%PodSet), located in the CaLG05 genomic region, were found to have cumulative phenotypic variation of above 50%. Nineteen pairs of epistatic QTLs showed significant epistatic effect, and non-significant QTL × environment interaction effect, except for harvest index (HI) and biomass (BM). A total of 25 putative candidate genes for heat-stress were identified in the two major genomic regions. This is the first report on QTLs for heat-stress response in chickpea. The markers linked to the above mentioned four major QTLs can facilitate marker-assisted breeding for heat tolerance in chickpea.

Ecology and genomics of an important crop wild relative as a prelude to agricultural innovation.

Domesticated species are impacted in unintended ways during domestication and breeding. Changes in the nature and intensity of selection impart genetic drift, reduce diversity, and increase the frequency of deleterious alleles. Such outcomes constrain our ability to expand the cultivation of crops into environments that differ from those under which domestication occurred. We address this need in chickpea, an important pulse legume, by harnessing the diversity of wild crop relatives. We document an extreme domestication-related genetic bottleneck and decipher the genetic history of wild populations. We provide evidence of ancestral adaptations for seed coat color crypsis, estimate the impact of environment on genetic structure and trait values, and demonstrate variation between wild and cultivated accessions for agronomic properties. A resource of genotyped, association mapping progeny functionally links the wild and cultivated gene pools and is an essential resource chickpea for improvement, while our methods inform collection of other wild crop progenitor species.

Plant vigour QTLs co-map with an earlier reported QTL hotspot for drought tolerance while water saving QTLs map in other regions of the chickpea genome.

BACKGROUND: Terminal drought stress leads to substantial annual yield losses in chickpea (Cicer arietinum L.). Adaptation to water limitation is a matter of matching water supply to water demand by the crop. Therefore, harnessing the genetics of traits contributing to plant water use, i.e. transpiration rate and canopy development dynamics, is important to design crop ideotypes suited to a varying range of water limited environments. With an aim of identifying genomic regions for plant vigour (growth and canopy size) and canopy conductance traits, 232 recombinant inbred lines derived from a cross between ICC 4958 and ICC 1882, were phenotyped at vegetative stage under well-watered conditions using a high throughput phenotyping platform (LeasyScan). RESULTS: Twenty one major quantitative trait loci (M-QTLs) were identified for plant vigour and canopy conductance traits using an ultra-high density bin map. Plant vigour traits had 13 M-QTLs on CaLG04, with favourable alleles from high vigour parent ICC 4958. Most of them co-mapped with a previously fine mapped major drought tolerance "QTL-hotspot" region on CaLG04. One M-QTL was found for canopy conductance on CaLG03 with the ultra-high density bin map. Comparative analysis of the QTLs found across different density genetic maps revealed that QTL size reduced considerably and % of phenotypic variation increased as marker density increased. CONCLUSION: Earlier reported drought tolerance hotspot is a vigour locus. The fact that canopy conductance traits, i.e. the other important determinant of plant water use, mapped on CaLG03 provides an opportunity to manipulate these loci to tailor recombinants having low/high transpiration rate and plant vigour, fitted to specific drought stress scenarios in chickpea.

Food Legumes and Rising Temperatures: Effects, Adaptive Functional Mechanisms Specific to Reproductive Growth Stage and Strategies to Improve Heat Tolerance.

Ambient temperatures are predicted to rise in the future owing to several reasons associated with global climate changes. These temperature increases can result in heat stress- a severe threat to crop production in most countries. Legumes are well-known for their impact on agricultural sustainability as well as their nutritional and health benefits. Heat stress imposes challenges for legume crops and has deleterious effects on the morphology, physiology, and reproductive growth of plants. High-temperature stress at the time of the reproductive stage is becoming a severe limitation for production of grain legumes as their cultivation expands to warmer environments and temperature variability increases due to climate change. The reproductive period is vital in the life cycle of all plants and is susceptible to high-temperature stress as various metabolic processes are adversely impacted during this phase, which reduces crop yield. Food legumes exposed to high-temperature stress during reproduction show flower abortion, pollen and ovule infertility, impaired fertilization, and reduced seed filling, leading to smaller seeds and poor yields. Through various breeding techniques, heat tolerance in major legumes can be enhanced to improve performance in the field. Omics approaches unravel different mechanisms underlying thermotolerance, which is imperative to understand the processes of molecular responses toward high-temperature stress.

Molecular Mapping of Flowering Time Major Genes and QTLs in Chickpea (Cicer arietinum L.).

Flowering time is an important trait for adaptation and productivity of chickpea in the arid and the semi-arid environments. This study was conducted for molecular mapping of genes/quantitative trait loci (QTLs) controlling flowering time in chickpea using F2 populations derived from four crosses (ICCV 96029 × CDC Frontier, ICC 5810 × CDC Frontier, BGD 132 × CDC Frontier and ICC 16641 × CDC Frontier). Genetic studies revealed monogenic control of flowering time in the crosses ICCV 96029 × CDC Frontier, BGD 132 × CDC Frontier and ICC 16641 × CDC Frontier, while digenic control with complementary gene action in ICC 5810 × CDC Frontier. The intraspecific genetic maps developed from these crosses consisted 75, 75, 68 and 67 markers spanning 248.8 cM, 331.4 cM, 311.1 cM and 385.1 cM, respectively. A consensus map spanning 363.8 cM with 109 loci was constructed by integrating four genetic maps. Major QTLs corresponding to flowering time genes efl-1 from ICCV 96029, efl-3 from BGD 132 and efl-4 from ICC 16641 were mapped on CaLG04, CaLG08 and CaLG06, respectively. The QTLs and linked markers identified in this study can be used in marker-assisted breeding for developing early maturing chickpea.

Correction: Genetic Dissection of Drought and Heat Tolerance in Chickpea through Genome-Wide and Candidate Gene-Based Association Mapping Approaches.

[This corrects the article DOI: 10.1371/journal.pone.0096758.].

Recent breeding programs enhanced genetic diversity in both desi and kabuli varieties of chickpea (Cicer arietinum L.).

In order to understand the impact of breeding on genetic diversity and gain insights into temporal trends in diversity in chickpea, a set of 100 chickpea varieties released in 14 countries between 1948 and 2012 were re-sequenced. For analysis, the re-sequencing data for 29 varieties available from an earlier study was also included. Copy number variations and presence absence variations identified in the present study have potential to drive phenotypic variations for trait improvement. Re-sequencing of a large number of varieties has provided opportunities to inspect the genetic and genomic changes reflecting the history of breeding, which we consider as breeding signatures and the selected loci may provide targets for crop improvement. Our study also reports enhanced diversity in both desi and kabuli varieties as a result of recent chickpea breeding efforts. The current study will aid the explicit efforts to breed for local adaptation in the context of anticipated climate changes.

Genome-Enabled Prediction Models for Yield Related Traits in Chickpea.

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped extensively for yield and yield related traits at two different locations (Delhi and Patancheru, India) during the crop seasons 2011-12 and 2012-13 under rainfed and irrigated conditions. In parallel, these lines were also genotyped using DArTseq platform to generate genotyping data for 3000 polymorphic markers. Phenotyping and genotyping data were used with six statistical GS models to estimate the prediction accuracies. GS models were tested for four yield related traits viz. seed yield, 100 seed weight, days to 50% flowering and days to maturity. Prediction accuracy for the models tested varied from 0.138 (seed yield) to 0.912 (100 seed weight), whereas performance of models did not show any significant difference for estimating prediction accuracy within traits. Kinship matrix calculated using genotyping data reaffirmed existence of two different groups within selected lines. There was not much effect of population structure on prediction accuracy. In brief, present study establishes the necessary resources for deployment of GS in chickpea breeding.