Genetic dissection of yield traits in super hybrid rice Xieyou9308 using both unconditional and conditional genome-wide association mapping

Aike Zhu,Liyuan Zhou,Xiangyang Lou,Weixun Wu,Xihong Shen,Haiming Xu,Qunen Liu,Shihua Cheng,Liyong Cao,Daibo Chen,Yingxin Zhang,Xiaodeng Zhan

doi:10.1038/s41598-017-00938-7

Abstract

With the development and application of super rice breeding, elite rice hybrids with super high-yielding potential have been widely developed in last decades in China. Xieyou9308 is one of the most famous super hybrid rice varieties. To uncover the genetic mechanism of Xieyou9308’s high yield potential, a recombinant inbred line (RIL) population derived from cross of XieqingzaoB and Zhonghui9308 was re-sequenced and investigated on the grain yield (GYD) and its three component traits, number of panicles per plant (NP), number of filled grains per panicle (NFGP), and grain weight (GW). Unconditional and conditional genome-wide association analysis, based on a linear mixed model with epistasis and gene-environment interaction effects, were conducted, using ~0.7 million identified SNPs. There were six, four, seven, and seven QTSs identified for GYD, NP, NFGP, and GW, respectively, with accumulated explanatory heritability varying from 43.06% to 48.36%; additive by environment interactions were detected for GYD, some minor epistases were detected for NP and NFGP. Further, conditional genetic mapping analysis for GYD given its three components revealed several novel QTSs associated with yield than that were suppressed in our unconditional mapping analysis.

Highlights

Rice is a fundamentally important staple crop, and improving rice yields has remained a major goal in world agriculture
Even though genome-wide association studies (GWASs) have led to some promising scientific discoveries, they have encountered the ‘missing heritability’ problem. This refers to the situation where identified genetic variants only explain a small proportion of the expected heritability estimated from classical pedigree analyses
Gene-by-environment interactions were detected for GYD (Table 3), which might partly account for the significant differences for mean of grain yield in the two environments that we observed in our phenotypic analysis (Table 1)

Summary

Introduction

Rice is a fundamentally important staple crop, and improving rice yields has remained a major goal in world agriculture. A subsequent study from Huang et al.[12] reported 32 new loci associated with 11 agronomic traits based on a natural population of 950 worldwide rice varieties. Another GWAS based on 413 diverse accessions of O. sativa from 82 countries identified 234 loci associated with 34 agronomic traits using 44,100 identified SNP variants[11]. These studies confirm that GWAS is a powerful approach that can be used in rice to identify genetic variants associated with complex traits with high resolution. Conditional genetic analysis is a methodology first introduced by Zhu[13] to study developmental quantitative genetics; it was later extended for the analysis of the genetic contributions of component traits to an integrated trait at the molecular level[14, 15]

Methods

Results

Conclusion