GWAS analysis revealed genomic loci and candidate genes associated with the 100-seed weight in high-latitude-adapted soybean germplasm

Abstract

In the present study, we identified 22 significant SNPs, eight stable QTLs and 17 potential candidate genes associated with 100-seed weight in soybean. Soybean is an economically important crop that is rich in seed oil and protein. The 100-seed weight (HSW) is a crucial yield contributing trait. This trait exhibits complex inheritance regulated by many genes and is highly sensitive to environmental factors. In this study, an integrated strategy of association mapping, QTL analysis, candidate gene and haplotype analysis was utilized to elucidate the complex genetic architecture of HSW in a panel of diverse soybean cultivars. Our study revealed 22 SNPs significantly associated with HSW through association mapping using five GWAS models across multiple environments plus a combined environment. By considering the detection of SNPs in multiple environments and GWAS models, the genomic regions of eight consistent SNPs within the ± 213.5 kb were depicted as stable QTLs. Among the eight QTLs, four, viz. qGW1.1, qGW1.2, qGW9 and qGW16, are reported here for the first time, and the other four, viz. qGW4, qGW8, qGW17 and qGW19, have been reported in previous studies. Thirty-two genes were detected as putative candidates within physical intervals of eight QTLs by in silico analysis. Twelve genes (out of total 32) showed significant differential expression patterns among the soybean accessions with contrasting HSW. Moreover, different haplotype alleles of 10 candidate genes are associated with different phenotypes of HSW. The outcome of the current investigation can be used in soybean breeding programs for producing cultivars with higher yields.