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Journal of Integrative Agriculture  2018, Vol. 17 Issue (05): 1074-1084    DOI: 10.1016/S2095-3119(17)61783-0
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Meta-analysis of soybean amino acid QTLs and candidate gene mining
GONG Qian-chun*, YU Hong-xiao*, MAO Xin-rui, QI Hui-dong, SHI Yan, XIANG Wei, CHEN Qing-shan, QI Zhao-ming
Key Laboratory of Soybean Biology, Ministry of Education/College of Agriculture, Northeast Agricultural University, Harbin 150030, P.R.China
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Abstract  The composition and quantity of amino acids influence the protein content and nutritional value of soybeans and also have an important impact upon soybean quality.  After integrating and proofreading 140 original QTLs associated with amino acid contentfrom soybase (http://www.soybase.org/), 138 QTLs were further analyzed to determine high-confidence QTL regions.  Meta-analysis was first carried out using the BioMercator ver. 2.1 software, yielding 33 consensus QTLs.  The consensus QTL confidence intervals (CIs) ranged from 0.07 to 19.85 Mb.  Next, the overview method was used to optimize the CIs, and 57 “real” QTLs were mapped.  Candidate genes in the consensus QTL regions were obtained from Phytozome and were annotated using the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Swissprot, and gene annotation databases.  Finally, 16 unpublished candidate genes controlling the content of five types of amino acids were identified with Blast.  These results laid the foundation for fine mapping of soybean amino acid-related QTLs and marker-assisted selection.
Keywords:  soybean        amino acid QTLs        meta-analysis        overview analysis       candidate genes  
Received: 18 April 2017   Accepted:
Fund: 

This study was financially supported by the National Key R&D Program of China (2016YFD0100500, 2016YFD0100300, 2016YFD0100201-21), the “Challenge Cup” National College Student Curricular Academic Science and Technology Works Competition of Ministry of Education of China (to Gong Qianchun, guided by Qi Zhaoming), the National Natural Science Foundation of China (31701449, 31471516, 31401465, 31400074, 31501332), the China Post Doctoral Project (2015M581419), the Dongnongxuezhe Project (to Chen Qingshan), China, the Young Talent Project (to Qi Zhaoming) of Northeast Agriculture University, China (518062), the Heilongjiang Funds for Distinguished Young Scientists, China (JC2016004), and the Outstanding Academic Leaders Projects of Harbin, China (2015RQXXJ018).

Corresponding Authors:  Correspondence CHEN Qing-shan, Tel/Fax: +86-451-55191945, E-mail: qshchen@126.com; QI Zhao-ming, E-mail: qizhaoming1860@126.com    
About author:  GONG Qian-chun, E-mail: superqian@outlook.com; YU Hong-xiao, E-mail: 13303619805@163.com; * These authors contributed equally to this study.

Cite this article: 

GONG Qian-chun, YU Hong-xiao, MAO Xin-rui, QI Hui-dong, SHI Yan, XIANG Wei, CHEN Qing-shan,. 2018. Meta-analysis of soybean amino acid QTLs and candidate gene mining. Journal of Integrative Agriculture, 17(05): 1074-1084.

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