SNP-SNP Interaction Analysis on Soybean Oil Content under Multi-Environments.

Soybean oil content is one of main quality traits. In this study, we used the multifactor dimensionality reduction (MDR) method and a soybean high-density genetic map including 5,308 markers to identify stable single nucleotide polymorphism (SNP)-SNP interactions controlling oil content in soybean a...

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Bibliographic Details
Main Authors: Qingshan Chen, Xinrui Mao, Zhanguo Zhang, Rongsheng Zhu, Zhengong Yin, Yue Leng, Hongxiao Yu, Huiying Jia, Shanshan Jiang, Zhongqiu Ni, Hongwei Jiang, Xue Han, Chunyan Liu, Zhenbang Hu, Xiaoxia Wu, Guohua Hu, Dawei Xin, Zhaoming Qi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5036806?pdf=render
Description
Summary:Soybean oil content is one of main quality traits. In this study, we used the multifactor dimensionality reduction (MDR) method and a soybean high-density genetic map including 5,308 markers to identify stable single nucleotide polymorphism (SNP)-SNP interactions controlling oil content in soybean across 23 environments. In total, 36,442,756 SNP-SNP interaction pairs were detected, 1865 of all interaction pairs associated with soybean oil content were identified under multiple environments by the Bonferroni correction with p <3.55×10-11. Two and 1863 SNP-SNP interaction pairs detected stable across 12 and 11 environments, respectively, which account around 50% of total environments. Epistasis values and contribution rates of stable interaction (the SNP interaction pairs were detected in more than 2 environments) pairs were detected by the two way ANOVA test, the available interaction pairs were ranged 0.01 to 0.89 and from 0.01 to 0.85, respectively. Some of one side of the interaction pairs were identified with previously research as a major QTL without epistasis effects. The results of this study provide insights into the genetic architecture of soybean oil content and can serve as a basis for marker-assisted selection breeding.
ISSN:1932-6203