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Soybean plant height QTL mapping and meta‐analysis for mining candidate genes
Authors:Zhengong Yin  Huidong Qi  Qingshan Chen  Zhanguo Zhang  Hongwei Jiang  Rongsheng Zhu  Zhenbang Hu  Xiaoxia Wu  Candong Li  Yong Zhang  Chunyan Liu  Guohua Hu  Dawei Xin  Zhaoming Qi
Affiliation:1. College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China;2. Crop Breeding Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, Heilongjiang, China;3. The Crop Research and Breeding Center of Land‐Reclamation of Heilongjiang Province, Harbin, Heilongjiang, China;4. HeiLongJiang Academy of Agricultural Sciences JiaMuSi branch institute, JiaMuSi, HeiLongJiang, China;5. Suihua Branch of Heilongjiang Academy of Agricultural Sciences, Suihua, Heilongjiang, China
Abstract:Plant height is closely related to seed yield of soybean. The goal of this study was to identify important loci affecting soybean plant height using meta‐analysis based on a reference physical map. Plant height related to QTLs was mapped across eight years with a RIL population by WinQTLCart v2.5. 182 QTLs related to plant height of soybean from database and our research were collected, and each QTL was projected onto the soybean physical map by software BioMercator v2.1. The confidence interval of meta‐QTL ranged from 0.09 to 5.07 Mb, and the mean phenotypic variance ranged from 4.9% to 73.0%. Furthermore, 4,259 candidate genes were located in these consensus QTLs, and 40 of them were involved in the plant growth and stem elongation and annotated as plant hormone signal transduction (pathway ID ko04075) in KEGG pathway. These results would lay a foundation for fine mapping of QTLs/genes related to plant height and marker‐assisted selection for breeding in soybean.
Keywords:candidate genes  meta‐analysis  QTL mapping  soybean plant height
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