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QTL mapping of soybean node numbers on the main stem and meta-analysis for mining candidate genes

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posted on 2018-05-18, 07:37 authored by Zhengong Yin, Huidong Qi, Xinrui Mao, Jingxin Wang, Zhenbang Hu, Xiaoxia Wu, Chunyan Liu, Dawei Xin, Xin Zuo, Qingshan Chen, Zhaoming Qi

The soybean (Glycine max) node number on the main stem (NNMS) is closely related to seed yield of soybean. The aim of this study was to identify important loci affecting soybean NNMS using meta-analysis based on a reference physical map. Twenty-nine NNMS-related QTLs were mapped across 8 years with a recombination inbred line (RIL) population. Fifty-four QTLs related to NNMS of soybean identified from the database and our research were collected and each QTL was projected onto the soybean physical map. Through meta-analysis, 11 consensus soybean NNMS QTLs were obtained and located on LG D1b, LG C2, LG B1, LG F, LG L, and LG I. The map distance was from 0.02 to 4.22 Mb, the variation of original QTLs was from 2 to 4, and the mean R2 values ranged from 6.90% to 27.40%. Furthermore, 488 candidate genes were located in these consensus QTLs, 6 of which had a relationship with NNMS. These results may help lay a foundation for fine mapping of QTLs/genes related to NNMS that can be used to help breed high-yield soybean cultivars.

Funding

This study was conducted in the Key Laboratory of Soybean Biology at the Chinese Ministry of Education in Heilongjiang Province and was financially supported by China Post Doctoral Project [grant number 2015M581419], [grant number 2015M581419]; Young Talent Project of Northeast Agriculture University [grant number 518062]; Soybean Quality Improvement [grant number 2016YFD0100500]; Soybean Germplasm Innovation [grant number 2016YFD0100304 −1–2]; National Natural Science Foundation of China [grant number 31400074], [grant number 31401465], [grant number 31471516], [grant number 31501332]; Heilongjiang Funds for Distinguished Young Scientists [grant number JC2016004]; and the Outstanding Academic Leaders Projects of Harbin [grant number 2015RQXXJ018].

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