Image-based GWAS identifies the genetic architecture of seed-related traits in a soybean mutant population

基于图像的全基因组关联分析(GWAS)揭示了大豆突变群体中种子相关性状的遗传结构

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Abstract

Soybean [Glycine max (L.) Merr.] seed morphology markedly influences yield, productivity, and nutritional value. However, assessing quantitative traits remains challenging due to their complexity and strong genotype-by-environment interactions. In this study, a high-throughput phenotyping (HTP) system was used to evaluate 13 image-based traits and a hundred-seed weight in a soybean mutant diversity pool (MDP) comprising 192 genotypes. All traits exhibited significant variations within the mutant diversity pool across multiple environments. Correlation analysis revealed strong positive and negative correlations among the traits regarding seed size, shape, color, and weight. Genome-wide association studies (GWAS) were conducted using 37,249 single nucleotide polymorphisms (SNPs) generated through genotype-by-sequencing (GBS) to uncover the genetic architecture of seed-related traits. The image-based GWAS identified 79 significant quantitative trait nucleotides (QTNs) that were simultaneously detected under all environments. Notably, five novel pleiotropic QTNs were consistently mapped to chromosomes 7, 10, 15, 18, and 20, each associated with a specific candidate gene. These genes exhibited marked expression differences during the seed developmental stages between the wild-type cultivar and its mutant. The HTP-integrated GBS demonstrates a powerful approach for precise trait dissection and genomic selection. These findings provide critical insights into the genetic architecture underlying desirable seed morphology and offer valuable tools for advancing precision soybean breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11032-025-01584-y.

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