Integrative QTL mapping and candidate gene analysis for main stem node number in soybean
Abstract 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...
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BMC
2025-04-01
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| Series: | BMC Plant Biology |
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| Online Access: | https://doi.org/10.1186/s12870-025-06457-2 |
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| author | Bire Zha Chunlei Zhang Rongqiang Yuan Kezhen Zhao Jianqiang Sun Xiulin Liu Xueyang Wang Fengyi Zhang Bixian Zhang Sobhi F. Lamlom Honglei Ren Lijuan Qiu |
| author_facet | Bire Zha Chunlei Zhang Rongqiang Yuan Kezhen Zhao Jianqiang Sun Xiulin Liu Xueyang Wang Fengyi Zhang Bixian Zhang Sobhi F. Lamlom Honglei Ren Lijuan Qiu |
| author_sort | Bire Zha |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-64e998f3330d48d3a4e51daa9d312882 |
| institution | OA Journals |
| issn | 1471-2229 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Plant Biology |
| spelling | doaj-art-64e998f3330d48d3a4e51daa9d3128822025-08-20T01:53:19ZengBMCBMC Plant Biology1471-22292025-04-0125111510.1186/s12870-025-06457-2Integrative QTL mapping and candidate gene analysis for main stem node number in soybeanBire Zha0Chunlei Zhang1Rongqiang Yuan2Kezhen Zhao3Jianqiang Sun4Xiulin Liu5Xueyang Wang6Fengyi Zhang7Bixian Zhang8Sobhi F. Lamlom9Honglei Ren10Lijuan Qiu11Soybean Research Institute of Heilongjiang Academy of Agriculture SciencesSoybean Research Institute of Heilongjiang Academy of Agriculture SciencesSoybean Research Institute of Heilongjiang Academy of Agriculture SciencesSoybean Research Institute of Heilongjiang Academy of Agriculture SciencesCollege of Agronomy, Shenyang Agricultural UniversitySoybean Research Institute of Heilongjiang Academy of Agriculture SciencesSoybean Research Institute of Heilongjiang Academy of Agriculture SciencesSoybean Research Institute of Heilongjiang Academy of Agriculture SciencesInstitute of Biotechnology of Heilongjiang Academy of Agricultural SciencesWorkstation of Science and Technique for Post-doctoral in Sugar Beet Institute, Heilongjiang UniversitySoybean Research Institute of Heilongjiang Academy of Agriculture SciencesInstitute of Crop Sciences, Mlinistry of Agriculture and Rural Affairs, Key Laboratory of Crop Gene Resource and Germplasm Enhancement, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic improvement (NFCRl), Ministry of Agriculture and Rural AffairsAbstract 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.https://doi.org/10.1186/s12870-025-06457-2Main stem node number (MSNN)KASP markerSLAF sequencingSoybeanQTL mapping |
| spellingShingle | Bire Zha Chunlei Zhang Rongqiang Yuan Kezhen Zhao Jianqiang Sun Xiulin Liu Xueyang Wang Fengyi Zhang Bixian Zhang Sobhi F. Lamlom Honglei Ren Lijuan Qiu Integrative QTL mapping and candidate gene analysis for main stem node number in soybean BMC Plant Biology Main stem node number (MSNN) KASP marker SLAF sequencing Soybean QTL mapping |
| title | Integrative QTL mapping and candidate gene analysis for main stem node number in soybean |
| title_full | Integrative QTL mapping and candidate gene analysis for main stem node number in soybean |
| title_fullStr | Integrative QTL mapping and candidate gene analysis for main stem node number in soybean |
| title_full_unstemmed | Integrative QTL mapping and candidate gene analysis for main stem node number in soybean |
| title_short | Integrative QTL mapping and candidate gene analysis for main stem node number in soybean |
| title_sort | integrative qtl mapping and candidate gene analysis for main stem node number in soybean |
| topic | Main stem node number (MSNN) KASP marker SLAF sequencing Soybean QTL mapping |
| url | https://doi.org/10.1186/s12870-025-06457-2 |
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