Meta-analysis of soybean amino acid QTLs and candidate gene mining

Autor: Qian-chun GONG, Hong-xiao YU, Xin-rui MAO, Hui-dong QI, Yan SHI, Wei XIANG, Qing-shan CHEN, Zhao-ming QI
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Journal of Integrative Agriculture, Vol 17, Iss 5, Pp 1074-1084 (2018)
Druh dokumentu: article
ISSN: 2095-3119
DOI: 10.1016/S2095-3119(17)61783-0
Popis: 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 Finally, 16 unpublished candidate genes controlling the content of five types of amino acids were identified with Blast.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.
Databáze: Directory of Open Access Journals