Genome-wide association analysis and genomic prediction of salt tolerance trait in soybean germplasm - Xu, Rongqing; Yang, Qing; Liu, Zhi; Shi, Xiaolei; Wu, Xintong; Chen, Yuehan; Du, Xinyu; Gao, Qiqi; He, Di; Shi, Ainong; Tao, Peijun; Yan, Long (Frontiers in Plant Science, 2024)
Soybean is an important protein and oil crop, and improving yield has traditionally been a major breeding goal. However, salt stress is an important abiotic factor that can severely impair soybean yield by disrupting metabolic processes, inhibiting photosynthesis, and hindering plant growth, ultimately leading to a decrease in productivity. This study utilized phenotypic and genotypic data from 563 soybean germplasms sourced from over 20 countries. Employing four distinct models—we performed a genome-wide association study (GWAS) using four models, including MLM, MLMM, FarmCPU, and BLINK in GAPIT 3, we conducted a Genome-Wide Association Study (GWAS) to identify single nucleotide polymorphism (SNP) associated with salt tolerance in soybean. Subsequently, these identified SNP were further analyzed for candidate gene discovery. Using 34,181 SNPs for genomic prediction (GP) to assess prediction accuracy. Our study identified 10 SNPs significantly associated with salt tolerance, located on chromosomes 1, 2, 3, 7, and 16. And we identified 11 genes within a 5 kb window upstream and downstream of the QTLs on chromosomes 1, 3, and 16. Utilizing the GWAS-derived SNP marker sets for genomic prediction (GP) yielded r-values greater than 0.35, indicating a higher level of accuracy. This suggests that genomic selection for salt tolerance is feasible. The 10 identified SNP markers and candidate genes in this study provide a valuable reference for screening and developing salt-tolerant soybean germplasm resources.