Back to Search Start Over

Detection of Epistatic and Gene-Environment Interactions Underlying Three Quality Traits in Rice Using High-Throughput Genome-Wide Data.

Authors :
Xu, Haiming
Jiang, Beibei
Cao, Yujie
Zhang, Yingxin
Zhan, Xiaodeng
Shen, Xihong
Cheng, Shihua
Lou, Xiangyang
Cao, Liyong
Source :
BioMed Research International. 8/4/2015, Vol. 2015, p1-7. 7p.
Publication Year :
2015

Abstract

With development of sequencing technology, dense single nucleotide polymorphisms (SNPs) have been available, enabling uncovering genetic architecture of complex traits by genome-wide association study (GWAS). However, the current GWAS strategy usually ignores epistatic and gene-environment interactions due to absence of appropriate methodology and heavy computational burden. This study proposed a new GWAS strategy by combining the graphics processing unit- (GPU-) based generalized multifactor dimensionality reduction (GMDR) algorithm with mixed linear model approach. The reliability and efficiency of the analytical methods were verified through Monte Carlo simulations, suggesting that a population size of nearly 150 recombinant inbred lines (RILs) had a reasonable resolution for the scenarios considered. Further, a GWAS was conducted with the above two-step strategy to investigate the additive, epistatic, and gene-environment associations between 701,867 SNPs and three important quality traits, gelatinization temperature, amylose content, and gel consistency, in a RIL population with 138 individuals derived from super-hybrid rice Xieyou9308 in two environments. Four significant SNPs were identified with additive, epistatic, and gene-environment interaction effects. Our study showed that the mixed linear model approach combining with the GPU-based GMDR algorithm is a feasible strategy for implementing GWAS to uncover genetic architecture of crop complex traits. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23146133
Volume :
2015
Database :
Academic Search Index
Journal :
BioMed Research International
Publication Type :
Academic Journal
Accession number :
109031032
Full Text :
https://doi.org/10.1155/2015/135782