Mungbean ( Vigna radiata (L.) R. Wilczek var. radiata ) is an important grain legume valued for its high protein content and ability to improve soil fertility through biological nitrogen fixation. Despite its growing importance in tropical agriculture, genetic improvement of yield and protein content remains limited due to insufficient knowledge of the genomic regions controlling these traits. Genome-wide association studies (GWAS) using high-density single nucleotide polymorphism (SNP) markers provide a powerful approach to dissect the genetic architecture of complex traits in crop species. This study aimed to identify genomic loci associated with grain yield and protein content in mungbean using Diversity Arrays Technology sequencing (DArTseq) SNP markers. A panel of 120 mungbean genotypes was evaluated across four environments (Awka dry season, Awka rainy season, Uyo dry season, and Uyo rainy season), revealing substantial phenotypic variation: grain yield ranged from 24.00 to 7810.90 kg ha -1 (means 229.10–2333.66 kg ha - ¹) with strong genotype × environment (G×E) interactions, while protein content varied narrowly (22.10–24.25%; means ~ 23%). Genotyping using DArTseq generated 24,870 SNPs, filtered to 5,037 high-quality markers across 11 chromosomes (avg. PIC 0.27, MAF 0.24). Population structure analysis identified two major genetic clusters (ΔK = 2), PCA explained ~ 23% variation, and LD decayed to r²=0.2 at ~ 368 kb. Multi-locus GWAS (mrMLM, FASTmrMLM, etc.) identified 15 significant marker-trait associations (MTAs) for protein content (Chr1-2908989, Chr3-7994659, Chr2-809453, Chr5-3185830; genes in amino acid metabolism, transcription regulation LOB/SRS factors, protein degradation F-box, ribosomal function) and 15 for yield (Chr3-9213031, Chr3-6148955, Chr4-19860552/Chr4-19961226, Chr5-16189831, Chr6-30896900; genes in carbon metabolism methyltransferase, brassinosteroid signaling BKI1, cell wall development fasciclin-like, ATPase/energy metabolism, thylakoid/photosynthesis THF1). Environment-specific MTAs highlighted G×E effects, with Q-Q plots confirming model control. The study reveals the polygenic, environment-dependent genetic architecture of yield (strong G×E) and stable protein content in mungbean, with moderate LD enabling high-resolution mapping. Identified MTAs, distributed across chromosomes, and candidate genes (transcriptional/protein metabolism for protein; hormonal/cellular/energy pathways for yield) provide robust genomic resources for marker-assisted selection (MAS) and breeding high-yielding, nutritionally enhanced varieties adapted to diverse agro-ecologies.
Obasi et al. (Thu,) studied this question.