Globally, chickpea production is severely affected by salinity stress. Understanding the genetic basis for salinity tolerance is important to develop salinity tolerant chickpeas. A recombinant inbred line (RIL) population developed using parental lines ICCV 10 (salt-tolerant) and DCP 92-3 (salt-sensitive) was screened under field conditions to collect information on agronomy, yield components, and stress tolerance indices. Genotyping data generated using Axiom^®CicerSNP array was used to construct a linkage map comprising 1856 SNP markers spanning a distance of 1106.3 cM across eight chickpea chromosomes. Extensive analysis of the phenotyping and genotyping data identified 28 quantitative trait loci (QTLs) explaining up to 28.40% of the phenotypic variance in the population. We identified QTL clusters on CaLG03 and CaLG06, each harboring major QTLs for yield and yield component traits under salinity stress. The main-effect QTLs identified in these two clusters were associated with key genes such as calcium-dependent protein kinases, histidine kinases, cation proton antiporter, and WRKY and MYB transcription factors, which are known to impart salinity stress tolerance in crop plants. Molecular markers/genes associated with these major QTLs, after validation, will be useful to undertake marker-assisted breeding for developing better varieties with salinity tolerance.

Identifying a congenially targeted production environment and understanding the effects of genotype by environmental interactions on the adaption of chickpea genotypes is essential for achieving an optimal yield stability. Different models like additive main effect and multiplicative interactions (AMMI 1, AMM2), weighted average absolute scores of BLUPs (WAASB), and genotype plus genotype–environment (GGE) interactions were used to understand their suitability in the precise estimation of variance and their interaction. Our experiment used genotypes that represent the West Asia–North Africa (WANA) region. This trial involved two different sowing dates, two distinct seasons, and three different locations, resulting in a total of 12 environments. Genotype IG 5871(G1) showed a lower heat susceptibility index (HSI) across environments under study. The first four interactions principal component axis (IPCA) explain 93.2% of variations with significant genotype–environment interactions. Considering the AMMI stability value (ASV), the genotypes IG5862(G7), IG5861(G6), ILC239(G40), IG6002(G26), and ILC1932(G39), showing ASV scores of 1.66, 1.80, 2.20, 2.60, and 2.84, respectively, were ranked as the most stable and are comparable to the weighted average absolute scores of BLUPs (WAASB) ranking of genotypes. The which–won–where pattern of genotype plus genotype–environment (GGE) interactions suggested that the target environment consists of one mega environment. IG5866(G10), IG5865(G9), IG5884(G14), and IG5862(G7) displayed higher stability, as they were nearer to the origin. The genotypes that exhibited a superior performance in the tested environments can serve as ideal parental lines for heat-stress tolerance breeding programs. The weighted average absolute scores of BLUPs (WAASB) serve as an ideal tool to discern the variations and identify the stable genotype among all methods.

Chickpea, being an important grain legume crop, is often confronted with the adverse effects of high temperatures at the reproductive stage of crop growth, drastically affecting yield and overall productivity. The current study deals with an extensive evaluation of chickpea genotypes, focusing on the traits associated with yield and their response to heat stress. Notably, we observed significant variations for these traits under both normal and high-temperature conditions, forming a robust basis for genetic research and breeding initiatives. Furthermore, the study revealed that yield-related traits exhibited high heritability, suggesting their potential suitability for marker-assisted selection. We carried out single-nucleotide polymorphism (SNP) genotyping using the genotyping-by-sequencing (GBS) method for a genome-wide association study (GWAS). Overall, 27 marker–trait associations (MTAs) linked to yield-related traits, among which we identified five common MTAs displaying pleiotropic effects after applying a stringent Bonferroni-corrected p-value threshold of 4.95] using the BLINK (Bayesian-information and linkage-disequilibrium iteratively nested keyway) model. Through an in-depth in silico analysis of these markers against the CDC Frontier v1 reference genome, we discovered that the majority of the SNPs were located at or in proximity to gene-coding regions. We further explored candidate genes situated near these MTAs, shedding light on the molecular mechanisms governing heat stress tolerance and yield enhancement in chickpeas such as indole-3-acetic acid–amido synthetase GH3.1 with GH3 auxin-responsive promoter and pentatricopeptide repeat-containing protein, etc. The harvest index (HI) trait was associated with marker Ca3:37444451 encoding aspartic proteinase ortholog sequence of Oryza sativa subsp. japonica and Medicago truncatula, which is known for contributing to heat stress tolerance. These identified MTAs and associated candidate genes may serve as valuable assets for breeding programs dedicated to tailoring chickpea varieties resilient to heat stress and climate change.

An association mapping panel consisting of 380 genotypes of chickpea was evaluated for three different years, including 2014–2015, 2015–2016 and 2016–2017, for yield-contributing parameters, including the seed number and seed weight. The AMMI analysis presented mainly concentrated on the seed weight and seed number, which are the two most important yield-contributing traits. The genotypes contributed 93.08% of the total variance, while the interaction effect was comparatively low, with 4.1% for the two traits. AMMI biplot analysis identified IG5986, IG5982, ILC6025 and ICCV14307 as desirable genotypes for the seed weight and IG5893, ILC6891 and IG5856 for the seed number. Identifying stable genotypes would help in strategic planning for yield improvement through component trait breeding.

In chickpea breeding, drought is a major concern and a complex trait controlled by several genes. To develop drought-tolerant varieties, it is essential to use the available germplasm and genomic resources. Over the years, the landraces have proven to be a good source for the dissection of genes for different yield and yield-related traits. The present investigation for marker–trait associations (MTAs) and candidate gene identification was conducted by studying 125 chickpea landraces collected from the West Asia and North Africa (WANA) region, along with 4 varieties suitable for irrigated and rainfed environments. This study analyzed 13 physio-morphological traits in 2 consecutive years at two isolated locations (IARI, New Delhi, and Dharwad). A strong correlation coefficient was observed between the trait seed yield (SY) and biological yield (BY) under both conditions. The Drought Susceptibility Index (DSI) ranged from 0.02 to 1.84 and 0.10 to 2.04 at the IARI, New Delhi and Dharwad locations, respectively. The genotypic data of 6,367 single nucleotide polymorphisms (SNPs) distributed across the genome were used for genetic diversity study, population structure, and genome-wide association study (GWAS). The average polymorphic information content (PIC) value observed was 0.25, and the average linkage disequilibrium (LD) decay distance was 152,269 bp across the genome. A total of four subgroups were observed within the population for genotypic data. Fixed and random model Circulating Probability Unification (FarmCPU) was used for the GWAS analysis, which considered both fixed- and random-effect models. A total of 52 significant SNPs were reported in both irrigated and rainfed conditions at low locations; 7 SNPs were associated with more than one trait, which may have pleiotropic effects. Significant SNPs were annotated in the pulse database. The identified genomic region found in or near MTA under rainfed conditions encodes for guard cell hydrogen peroxide-resistant1 (GHR1), late embryogenesis-abundant, E3 ubiquitin-protein ligase, walls are thin1 (WAT1), and beta-galactosidase that are known to be associated with drought tolerance.