数字农科院2.0

Identification of Quantitative Trait Loci for Node Number, Pod Number, and Seed Number in Soybean

文献类型： 外文期刊

作者： Chunlei Zhang;Bire Zha;Rongqiang Yuan;Kezhen Zhao;Jianqiang Sun;Xiulin Liu;Xueyang Wang;Fengyi Zhang;Bixian Zhang;Sobhi F. Lamlom;Honglei Ren;Lijuan Qiu

作者机构：

关键词： differential expression analysis;QTL mapping;SLAF sequencing;soybean

期刊名称： International Journal of Molecular Sciences

ISSN： 1661-6596

年卷期： 2025 年 26 卷 5 期

页码：

收录情况： SCIE（2025版）

摘要： Optimizing soybean yield remains a crucial challenge in meeting global food security demands. In this study, we report a comprehensive genetic analysis of yield-related traits in soybeans using a recombinant inbred line (RIL) population derived from crosses between ‘Qihuang 34’ (GH34) and ‘Dongsheng 16′ (DS16). Phenotypic analysis across two years (2023–2024) revealed significant variations between parental lines. Through high-density genetic mapping with 6297 SLAF markers spanning 2945.26 cM across 20 chromosomes, we constructed a genetic map with an average marker distance of 0.47 cM and 99.17% of gaps under 5 cM. QTL analysis identified ten significant loci across both years: in 2023, we detected six QTLs, including a major main stem node number (MSNN) QTL on chromosome 19 (LOD = 22.59, PVE = 24.57%), two seed number (SN) QTLs on chromosomes 14 and 18 (LOD = 2.52–2.85, PVE = 7.35% combined), and one pod number (PN) QTL on chromosome 20 (LOD = 4.68, PVE = 5.85%). The 2024 analysis revealed four major QTLs, notably a cluster on chromosome 19 harboring significant loci for MSNN (LOD = 37.92, PVE = 43.59%), PN (LOD = 18.16, PVE = 23.02%), and SN (LOD = 15.24, PVE = 19.59%). Within the stable chromosome 19 region, we identified seventeen candidate genes involved in crucial developmental processes. Gene expression analysis revealed distinct temporal patterns between parental lines during vegetative and reproductive stages, with GH34 showing dramatically higher expression of key reproductive genes Glyma.19G201300 and Glyma.19G201400 during the R1 stage. Our findings provide new insights into the genetic architecture of soybean stem node development and yield components, offering multiple promising targets for molecular breeding programs aimed at crop improvement.

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