Genome-wide association analysis of stress tolerance indices in an interspecific population of chickpea

Unraveling the genetics of heat tolerance in chickpea landraces (Cicer arietinum L.) using genome-wide association studies

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 <0.05 [-log10(p) > 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.

Freezing stress response of wild and cultivated chickpeas

Chickpea is an economically and nutritionally important grain legume globally, however, cold stress has adverse effects on its growth. In cold countries, like Canada where the growing season is short, having cold stress-tolerant varieties is crucial. Crop wild relatives of chickpea, especially Cicer reticulatum, can survive in suboptimal environments and are an important resource for crop improvement. In this study, we explored the performance of eleven C. reticulatum wild accessions and two chickpea cultivars, CDC Leader and CDC Consul, together with a cold sensitive check ILC533 under freezing stress. Freezing tolerance was scored based on a 1-9 scale. The wild relatives, particularly Kesen_075 and CudiA_152, had higher frost tolerance compared to the cultivars, which all died after frost treatment. We completed transcriptome analysis via mRNA sequencing to assess changes in gene expression in response to freezing stress and identified 6,184 differentially expressed genes (DEGs) in CDC Consul, and 7,842 DEGs in Kesen_075. GO (gene ontology) analysis of the DEGs revealed that those related to stress responses, endogenous and external stimuli responses, secondary metabolite processes, and photosynthesis were significantly over-represented in CDC Consul, while genes related to endogenous stimulus responses and photosynthesis were significantly over-represented in Kesen_075. These results are consistent with Kesen_075 being more tolerant to freezing stress than CDC Consul. Moreover, our data revealed that the expression of CBF pathway-related genes was impacted during freezing conditions in Kesen_075, and expression of these genes is believed to alleviate the damage caused by freezing stress. We identified genomic regions associated with tolerance to freezing stress in an F2 population derived from a cross between CDC Consul and Kesen_075 using QTL-seq analysis. Eight QTLs (P<0.05) on chromosomes Ca3, Ca4, Ca6, Ca7, Ca8, and two QTLs (P<0.01) on chromosomes Ca4 and Ca8, were associated with tolerance to freezing stress. Interestingly, 58 DEGs co-located within these QTLs. To our knowledge, this is the first study to explore the transcriptome and QTLs associated with freezing tolerance in wild relatives of chickpea under controlled conditions. Altogether, these findings provide comprehensive information that aids in understanding the molecular mechanism of chickpea adaptation to freezing stress and further provides functional candidate genes that can assist in breeding of freezing-stress tolerant varieties.

Fatty acid composition and genome-wide associations of a chickpea (Cicer arietinum L.) diversity panel for biofortification efforts

Chickpea is a nutritionally dense pulse crop with high levels of protein, carbohydrates, micronutrients and low levels of fats. Chickpea fatty acids are associated with a reduced risk of obesity, blood cholesterol, and cardiovascular diseases in humans. We measured four primary chickpea fatty acids; palmitic acid (PA), linoleic acid (LA), alpha-linolenic acid (ALA), and oleic acid (OA), which are crucial for human health and plant stress responses in a chickpea diversity panel with 256 accessions (Kabuli and desi types). A wide concentration range was found for PA (450.7-912.6 mg/100 g), LA (1605.7-3459.9 mg/100 g), ALA (416.4-864.5 mg/100 g), and OA (1035.5-1907.2 mg/100 g). The percent recommended daily allowances also varied for PA (3.3-6.8%), LA (21.4-46.1%), ALA (34.7-72%), and OA (4.3-7.9%). Weak correlations were found among fatty acids. Genome-wide association studies (GWAS) were conducted using genotyping-by-sequencing data. Five significant single nucleotide polymorphisms (SNPs) were identified for PA. Admixture population structure analysis revealed seven subpopulations based on ancestral diversity in this panel. This is the first reported study to characterize fatty acid profiles across a chickpea diversity panel and perform GWAS to detect associations between genetic markers and concentrations of selected fatty acids. These findings demonstrate biofortification of chickpea fatty acids is possible using conventional and genomic breeding techniques, to develop superior cultivars with better fatty acid profiles for improved human health and plant stress responses.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.