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

Genetic Dissection of Diverse Seed Coat Patterns in Cowpea through a Comprehensive GWAS Approach

This study investigates the genetic determinants of seed coat color and pattern variations in cowpea (Vigna unguiculata), employing a genome-wide association approach. Analyzing a mapping panel of 296 cowpea varieties with 110,000 single nucleotide polymorphisms (SNPs), we focused on eight unique coat patterns: (1) Red and (2) Cream seed; (3) White and (4) Brown/Tan seed coat; (5) Pink, (6) Black, (7) Browneye and (8) Red/Brown Holstein. Across six GWAS models (GLM, SRM, MLM, MLMM, FarmCPU from GAPIT3, and TASSEL5), 13 significant SNP markers were identified and led to the discovery of 23 candidate genes. Among these, four specific genes may play a direct role in determining seed coat pigment. These findings lay a foundational basis for future breeding programs aimed at creating cowpea varieties aligned with consumer preferences and market requirements.

Genome-wide SNP discovery and genotyping delineates potential QTLs underlying major yield-attributing traits in buckwheat

Buckwheat (Fagopyrum spp.) is an important nutritional and nutraceutical-rich pseudo-cereal crop. Despite its obvious potential as a functional food, buckwheat has not been fully harnessed due to its low yield, self-incompatibility, increased seed cracking, limited seed set, lodging, and frost susceptibility. The inadequate availability of genomics resources in buckwheat is one of the major reasons for this. In the present study, genome-wide association mapping (GWAS) was conducted to identify loci associated with various morphological and yield-related traits in buckwheat. High throughput genotyping by sequencing led to the identification of 34,978 single nucleotide polymorphisms that were distributed across eight chromosomes. Population structure analysis grouped the genotypes into three sub-populations. The genotypes were also characterized for various qualitative and quantitative traits at two diverse locations, the analysis of which revealed a significant difference in the mean values. The association analysis revealed a total of 71 significant marker-trait associations across eight chromosomes. The candidate genes were identified near 100 Kb of quantitative trait loci (QTLs), providing insights into several metabolic and biosynthetic pathways. The integration of phenology and GWAS in the present study is useful to uncover the consistent genomic regions, related markers associated with various yield-related traits, and potential candidate genes having implications for being utilized in molecular breeding for the improvement of economically important traits in buckwheat. Moreover, the identified QTLs will assist in tracking the desirable alleles of target genes within the buckwheat breeding populations/germplasm.