Genome-wide and gene-based association mapping for rice eating and cooking characteristics and protein content

Xiaoqian Wang,Jauhar Ali,Jian Zhang,Yunlong Pang,Jianlong Xu,Zhikang Li,Zhichao Wu,Guoyou Ye,Kai Chen

doi:10.1038/s41598-017-17347-5

Abstract

Rice eating and cooking quality and protein content (PC) are important properties affecting consumers’ preferences, nutrition and health. Linkage QTL mapping and association studies are usually applied to genetically dissect related traits, which could be further facilitated by high density SNP markers and gene annotation based on reference genome to rapid identify candidate genes associated with interested traits. Here, we carried out an association study for apparent amylose content (AC), gel consistency (GC), gelatinization temperature (GT) and PC evaluated in two environments using a diverse panel of 258 accessions from 3 K Rice Genome Project. Wide phenotypic variations were observed in this panel. Genome-wide association study using 22,488 high quality SNPs identified 19 QTL affecting the four traits. Combining gene-based association study and haplotype analyses plus functional annotation allowed us to shortlist nine candidate genes for four important QTL regions affecting AC, GC and GT, including two cloned genes (Wx and ALK), and seven novels. The research suggested that GWAS and gene-based association analysis followed by haplotype analysis is an effective way to detect candidate genes. The identified genes and QTL provided valuable sources for future functional characterization and genetic improvement of rice eating and cooking quality and PC.

Highlights

Rice (Oryza sativa L.) is the staple food for more than half of the world’s population
The high density SNP markers and gene annotation based on high quality reference genomes powerfully facilitate the identification of QTL candidate genes associated with interested traits[24]
amylose content (AC) was negatively correlated with gel consistency (GC) and gelatinization temperature (GT) with correlation coefficients (r) of −0.72 (−0.76) and −0.42 (−0.45) in SY (SZ), respectively

Summary

Introduction

Rice (Oryza sativa L.) is the staple food for more than half of the world’s population. Rice kernels with low or intermediate GT need less cooking time which is a desired trait for high quality rice varieties[8]. The high density SNP markers and gene annotation based on high quality reference genomes powerfully facilitate the identification of QTL candidate genes associated with interested traits[24]. Combining genome-wide association study (GWAS) and gene-based association analysis followed by haplotype analysis is an effective way to identify candidate genes for complex traits including rice grain appearance traits[25]. The objective of our study is to identify candidate genes affecting rice grain ECQ and PC using GWAS, and gene-based association analysis combining haplotype analysis. Haplotype analysis was conducted and the phenotype differences among major haplotypes were tested by ANOVA By this way, numbers of candidate genes governing investigated traits were determined

Objectives

Methods

Results

Discussion

Conclusion