Xuehui Huang, Xinghua Wei, Tao Sang, Qiang Zhao, Qi Feng, Yan Zhao, Canyang Li, Chuanrang Zhu, Tingting Lu, Zhiwu Zhang, Meng Li, Danlin Fan, Yunli Guo, Ahong Wang, Lu Wang, Liuwei Deng, Wenjun Li, Yiqi Lu, Qijun Weng, Kunyan Liu, Tao Huang, Taoying Zhou, Yufeng Jing, Wei Li, Zhang Lin, Edward S Buckler, Qian Qian, Qi-Fa Zhang, Jiayang Li & Bin Han
Nature Genetics 2010 Nov; 42(11): 961-967 DOI: 10.1038/ng.695
Abstract
Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ~3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ~36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.