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Open AccessArticle

Genome-Wide Detection of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean Under Multiple Environments Using High-Density Bin Map

1
Key Laboratory of Biology and Genetics and Breeding for Soybean, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Soybean Research Institution, National Center for Soybean Improvement, Ministry of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
2
Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China
3
College of Life Science, Yan’an University, Yan’an 716000, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Mol. Sci. 2019, 20(4), 979; https://doi.org/10.3390/ijms20040979
Received: 26 December 2018 / Revised: 1 February 2019 / Accepted: 19 February 2019 / Published: 23 February 2019
(This article belongs to the Special Issue Seed Development, Dormancy and Germination)
Seed protein and oil content are the two important traits determining the quality and value of soybean. Development of improved cultivars requires detailed understanding of the genetic basis underlying the trait of interest. However, it is prerequisite to have a high-density linkage map for precisely mapping genomic regions, and therefore the present study used high-density genetic map containing 2267 recombination bin markers distributed on 20 chromosomes and spanned 2453.79 cM with an average distance of 1.08 cM between markers using restriction-site-associated DNA sequencing (RAD-seq) approach. A recombinant inbred line (RIL) population of 104 lines derived from a cross between Linhefenqingdou and Meng 8206 cultivars was evaluated in six different environments to identify main- and epistatic-effect quantitative trait loci (QTLs)as well as their interaction with environments. A total of 44 main-effect QTLs for protein and oil content were found to be distributed on 17 chromosomes, and 15 novel QTL were identified for the first time. Out of these QTLs, four were major and stable QTLs, viz., qPro-7-1, qOil-8-3, qOil-10-2 and qOil-10-4, detected in at least two environments plus combined environment with R2 values >10%. Within the physical intervals of these four QTLs, 111 candidate genes were screened for their direct or indirect involvement in seed protein and oil biosynthesis/metabolism processes based on gene ontology and annotation information. Based on RNA sequencing (RNA-seq) data analysis, 15 of the 111 genes were highly expressed during seed development stage and root nodules that might be considered as the potential candidate genes. Seven QTLs associated with protein and oil content exhibited significant additive and additive × environment interaction effects, and environment-independent QTLs revealed higher additive effects. Moreover, three digenic epistatic QTLs pairs were identified, and no main-effect QTLs showed epistasis. In conclusion, the use of a high-density map identified closely linked flanking markers, provided better understanding of genetic architecture and candidate gene information, and revealed the scope available for improvement of soybean quality through marker assisted selection (MAS). View Full-Text
Keywords: soybean; QTL mapping; protein content; oil content; RAD-seq; high-density bin map; main-effect QTL; epistasis soybean; QTL mapping; protein content; oil content; RAD-seq; high-density bin map; main-effect QTL; epistasis
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Karikari, B.; Li, S.; Bhat, J.A.; Cao, Y.; Kong, J.; Yang, J.; Gai, J.; Zhao, T. Genome-Wide Detection of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean Under Multiple Environments Using High-Density Bin Map. Int. J. Mol. Sci. 2019, 20, 979.

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Int. J. Mol. Sci., EISSN 1422-0067, Published by MDPI AG
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