ABSTRACT
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.
ABSTRACT
Multidrug and toxic compound extrusion (MATE) transporters comprise a multigene family that mediates multiple functions in plants through the efflux of diverse substrates including organic molecules, specialized metabolites, hormones, and xenobiotics. MATE classification based on genome-wide studies remains ambiguous, likely due to a lack of large-scale phylogenomic studies and/or reference sequence datasets. To resolve this, we established a phylogeny of the plant MATE gene family using a comprehensive kingdom-wide phylogenomic analysis of 74 diverse plant species. We identified more than 4,000 MATEs, which were classified into 14 subgroups based on a systematic bioinformatics pipeline using USEARCH, blast+ and synteny network tools. Our classification was performed using a four-step process, whereby MATEs sharing ≥ 60% protein sequence identity with a ≤ 1E-05 threshold at different sequence lengths (either full-length, ≥ 60% length, or ≥ 150 amino acids) or retaining in the similar synteny blocks were assigned to the same subgroup. In this way, we assigned subgroups to 95.8% of the identified MATEs, which we substantiated using synteny network clustering analysis. The subgroups were clustered under four major phylogenetic groups and named according to their clockwise appearance within each group. We then generated a reference sequence dataset, the usefulness of which was demonstrated in the classification of MATEs in additional species not included in the original analysis. Approximately 74% of the plant MATEs exhibited synteny relationships with angiosperm-wide or lineage-, order/family-, and species-specific conservation. Most subgroups evolved independently, and their distinct evolutionary trends were likely associated with the development of functional novelties or the maintenance of conserved functions. Together with the systematic classification and synteny network profiling analyses, we identified all the major evolutionary events experienced by the MATE gene family in plants. We believe that our findings and the reference dataset provide a valuable resource to guide future functional studies aiming to explore the key roles of MATEs in different aspects of plant physiology. Our classification framework can also be readily extendable to other (super) families.
