QTL mapping and candidate gene mining for soybean seed weight per plant

文献类型： 外文期刊

第一作者： Yu, Meng

作者： Yu, Meng;Jiang, Shanshan;Chen, Qingshan;Qi, Zhaoming;Lv, Wenhe;Liu, Zhangxiong;Xu, Ning

作者机构：

关键词： Soybean; grain weight per plant; QTL mapping; gene mining

期刊名称：BIOTECHNOLOGY & BIOTECHNOLOGICAL EQUIPMENT （ 影响因子：1.632； 五年影响因子：2.029 ）

ISSN： 1310-2818

年卷期： 2018 年 32 卷 4 期

页码：

收录情况： SCI

摘要： In this study, 147 recombinant inbred soybean lines constructed from the parents Charleston and Dongnong594, were used to map quantitative trait loci (QTLs) for seed weight per plant in multiple years (2006 to 2010 and 2013). QTL mapping was done using a simple sequence repeat (SSR) map combined with specific-locus amplified fragment (SLAF) map and the composite interval mapping (CIM), multiple interval mapping (MIM) and inclusive complete interval mapping method (ICIM) algorithms. By combining QTLs with the QTL physical locations, two QTL intervals located in the D1a and C2 linkage groups were found in different years. KEGG and GO annotations of the 413 genes located within these QTL intervals were used to screen for candidate genes potentially involved in seed production. Based on WeGo online genetic classification, we ultimately selected four genes related to yield traits, Glyma.01G158700, Glyma.01G156800, Glyma.01G125400 and Glyma.01G147800, as candidate genes.

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