Chen Heng, Pan Xiangwen, Wang Feifei, Liu Changkai, Wang Xue, Li Yansheng, Zhang Qiuying
Key Laboratory of Soybean Molecular Design and Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.
Innovation Academy for Seed Design, Chinese Academy of Sciences, Harbin, China.
Front Plant Sci. 2021 Dec 8;12:774270. doi: 10.3389/fpls.2021.774270. eCollection 2021.
Isoflavone, protein, and oil are the most important quality traits in soybean. Since these phenotypes are typically quantitative traits, quantitative trait locus (QTL) mapping has been an efficient way to clarify their complex and unclear genetic background. However, the low-density genetic map and the absence of QTL integration limited the accurate and efficient QTL mapping in previous researches. This paper adopted a recombinant inbred lines (RIL) population derived from 'Zhongdou27'and 'Hefeng25' and a high-density linkage map based on whole-genome resequencing to map novel QTL and used meta-analysis methods to integrate the stable and consentaneous QTL. The candidate genes were obtained from gene functional annotation and expression analysis based on the public database. A total of 41 QTL with a high logarithm of odd (LOD) scores were identified through composite interval mapping (CIM), including 38 novel QTL and 2 Stable QTL. A total of 660 candidate genes were predicted according to the results of the gene annotation and public transcriptome data. A total of 212 meta-QTL containing 122 stable and consentaneous QTL were mapped based on 1,034 QTL collected from previous studies. For the first time, 70 meta-QTL associated with isoflavones were mapped in this study. Meanwhile, 69 and 73 meta-QTL, respectively, related to oil and protein were obtained as well. The results promote the understanding of the biosynthesis and regulation of isoflavones, protein, and oil at molecular levels, and facilitate the construction of molecular modular for great quality traits in soybean.
异黄酮、蛋白质和油是大豆中最重要的品质性状。由于这些表型通常是数量性状，数量性状基因座（QTL）定位一直是阐明其复杂且不明晰遗传背景的有效方法。然而，低密度遗传图谱以及QTL整合的缺失限制了以往研究中QTL定位的准确性和效率。本文采用了源自‘中豆27’和‘合丰25’的重组自交系（RIL）群体以及基于全基因组重测序的高密度连锁图谱来定位新的QTL，并使用元分析方法整合稳定且一致的QTL。通过基于公共数据库的基因功能注释和表达分析获得候选基因。通过复合区间作图（CIM）共鉴定出41个具有高对数似然比（LOD）分数的QTL，包括38个新的QTL和2个稳定QTL。根据基因注释结果和公共转录组数据共预测出660个候选基因。基于从以往研究中收集的1034个QTL绘制了总共212个包含122个稳定且一致QTL的元QTL。本研究首次绘制了70个与异黄酮相关的元QTL。同时，还分别获得了69个和73个与油和蛋白质相关的元QTL。这些结果促进了在分子水平上对异黄酮、蛋白质和油生物合成与调控的理解，并有助于构建大豆优良品质性状的分子模块。
