Zha Bire, Zhang Chunlei, Yuan Rongqiang, Zhao Kezhen, Sun Jianqiang, Liu Xiulin, Wang Xueyang, Zhang Fengyi, Zhang Bixian, Lamlom Sobhi F, Ren Honglei, Qiu Lijuan
Soybean Research Institute of Heilongjiang Academy of Agriculture Sciences, Harbin, 150086, China.
College of Modern Agriculture and Ecological, Environment of Heilongjiang University, Harbin, Heilongjiang, China.
BMC Plant Biol. 2025 Apr 3;25(1):422. doi: 10.1186/s12870-025-06457-2.
Main stem node number (MSNN) is a key yield-related quantitative trait that directly affects the number of branches and seeds per soybean plant. In this study, a QTL mapping using SLAF sequencing and candidate gene analyses were used to determine the detailed genetic basis of MSNN across a diverse set of soybean line. This study investigated the variation characteristics of MSNN in 325 recombinant inbred lines (RILs) obtained from the hybridization of Qihuang 34 and Dongsheng 16. The phenotypic analysis revealed prominent transgressive segregation and continuous variation in MSNN, with a normal distribution observed for MSNN in the RIL population. A genetic map including 6297 SLAF markers was developed which spanned 2945.26 cM, with an average genetic distance of 0.47 cM between adjacent markers. QTL mapping identified five significant QTLs associated with MSNN, were located on chromosomes 6 (qMSNN6.1), 17 (qMSNN17.1), 18 (qMSNN18.1), and 19 (qMSNN19.1 and qMSNN19.2) with LOD values ranging from 3.89 to 37.92, explaining 3.46-43.56% of the phenotypic variance. Among the five QTLs, qMSNN19.2 recorded the highest LOD value, 37.92, indicated a stable environment QTL explaining 43.56% of the variance. Candidate gene mining revealed 64 genes located in the QTL qMSNN19.2, with selections made based on biological processes like regulation of stem cell division and plant hormone signaling. Additionally, specific SNP variations in candidate genes were identified for KASP marker development, offering potential targets for enhancing soybean MSNN traits. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable MSNN.
主茎节数(MSNN)是一个与产量相关的关键数量性状,直接影响每株大豆的分枝数和种子数。在本研究中,利用SLAF测序进行QTL定位和候选基因分析,以确定不同大豆品系中MSNN的详细遗传基础。本研究调查了从齐黄34和东生16杂交获得的325个重组自交系(RIL)中MSNN的变异特征。表型分析显示MSNN存在显著的超亲分离和连续变异,RIL群体中MSNN呈正态分布。构建了一个包含6297个SLAF标记的遗传图谱,图谱跨度为2945.26 cM,相邻标记间的平均遗传距离为0.47 cM。QTL定位鉴定出5个与MSNN相关的显著QTL,分别位于第6号(qMSNN6.1)、17号(qMSNN17.1)、18号(qMSNN18.1)和19号(qMSNN19.1和qMSNN19.2)染色体上,LOD值范围为3.89至37.92,解释了3.46 - 43.56%的表型变异。在这5个QTL中,qMSNN19.2的LOD值最高,为37.92,表明其为一个稳定的环境QTL,解释了43.56%的变异。候选基因挖掘发现位于QTL qMSNN19.2中的64个基因,并基于干细胞分裂调控和植物激素信号传导等生物学过程进行筛选。此外,还鉴定了候选基因中的特定SNP变异用于开发KASP标记,为改良大豆MSNN性状提供了潜在靶点。本研究结果可为大豆育种计划培育具有理想MSNN的品种提供帮助。