Utilization of GWAS to Identify Candidate SNPs and Genes Associated with Seed Weight-related Traits in Peanuts (Arachis hypogaea L.)

Seed size and weight are considered important factors influencing crop yield and they are key domestication target in the peanut breeding. Seed weight-related traits include Extra-large kernel weight (ELKW), Medium kernel weight (MKW), Normal kernel weight (NKW), and Mini kernel weight (MNKW), as well as Yield per plot (YP) and Yield per hectare (YH). However, the natural variation and genetic mechanisms underlying peanut seed weight-related traits have not yet been elucidated. In this study, phenotypic analysis of six seed weight-related traits was conducted using 102 peanut samples. Genome-wide association analysis (GWAS) was performed using 12,230 high-quality single nucleotide polymorphisms (SNPs) and the IIIVmrMLM model in R software. A total of 27 SNPs were identified, with the SNPs significantly associated with ELKW, MKW, KW, AOSTW, YR, and YC being 9, 5, 6, 5, 1, and 1, respectively. Based on the candidate regions of three peak SNPs (AX-147226318, AX-176821377, AX-147251710) that appeared repeatedly in different environments or traits, 34 candidate genes related to seed weight were identified and functionally annotated. These significant SNPs and candidate genes will help in understanding the genetic mechanisms of peanut seed-related traits and provide additional insights for the future genetic improvement of peanut germplasm and molecular marker-assisted breeding.