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

Haiming Xu,Beibei Jiang,Yingxin Zhang,Xiangyang Lou,Shihua Cheng,Xihong Shen,Xiaodeng Zhan,Liyong Cao,Yujie Cao

doi:10.1155/2015/135782

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.

Highlights

Rice (Oryza sativa L.), a crop species of economic importance, provides the staple food for more than half of the population in the world
Because our real experiment data is based on a rice recombinant inbred lines (RILs) population, we conducted the simulations based on this kind of population to examine our methods
525 single nucleotide polymorphisms (SNPs) were scattered across 3 chromosomes, with 175 markers evenly distributed on each chromosome

Summary

Introduction

Rice (Oryza sativa L.), a crop species of economic importance, provides the staple food for more than half of the population in the world. In China, the super-hybrid rice plays a pivotal role in the country’s food security. Substantial geneticist’s and breeder’s effort is being expended in attempt to further investigate the mechanisms underlying high yield potential, wide adaptability, better grain quality, better disease resistance, and strong resistance to lodging in super-hybrid rice. The majority of these traits are quantitatively inherited. In addition to the increase of grain yield and the improvement of living conditions, more attention has been being paid toward improving grain quality, related to preference of cooking and eating quality of rice varieties

Methods

Results

Conclusion