Zhang Hongmei, Zhang Guwen, Zhang Wei, Wang Qiong, Xu Wenjing, Liu Xiaoqing, Cui Xiaoyan, Chen Xin, Chen Huatao
Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing Jiangsu, China.
Institute of Vegetables, Zhejiang Academy of Agricultural Sciences, Hangzhou Zhejiang, China.
Front Plant Sci. 2022 Dec 2;13:1045953. doi: 10.3389/fpls.2022.1045953. eCollection 2022.
Soybean [ (L.) Merr.] is an excellent source of protein. Understanding the genetic basis of protein content (PC) will accelerate breeding efforts to increase soybean quality. In the present study, a genome-wide association study (GWAS) was applied to detect quantitative trait loci (QTL) for PC in soybean using 264 re-sequenced soybean accessions and a high-quality single nucleotide polymorphism (SNP) map. Eleven QTL were identified as associated with PC. The QTL was detected by GWAS in both environments and was shown to have undergone strong selection during soybean improvement. Fifteen candidate genes were identified in , and three candidate genes showed differential expression between a high-PC and a low-PC variety during the seed development stage. The QTL identified here will be of significant use in molecular breeding efforts, and the candidate genes will play essential roles in exploring the mechanisms of protein biosynthesis.
大豆[(L.)Merr.]是优质蛋白质来源。了解蛋白质含量(PC)的遗传基础将加速提高大豆品质的育种工作。在本研究中,利用264份重测序大豆种质和高质量单核苷酸多态性(SNP)图谱,应用全基因组关联研究(GWAS)检测大豆中与PC相关的数量性状位点(QTL)。鉴定出11个与PC相关的QTL。该QTL在两种环境下均通过GWAS检测到,并且在大豆改良过程中经历了强烈选择。在其中鉴定出15个候选基因,并且三个候选基因在种子发育阶段的高PC品种和低PC品种之间表现出差异表达。这里鉴定出的QTL将在分子育种工作中具有重要用途,并且候选基因将在探索蛋白质生物合成机制中发挥重要作用。