ARS | Publication request: Genome-wide and fine resolution association studies of 14 agronomic traits in rice land races

Submitted to: Nature Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 24, 2010
Publication Date: October 24, 2010
Citation: Huang, X., Sang, T., Zhao, Q., Wei, X., Feng, Q., Zhao, Y., Li, C., Zhu, C., Lu, T., Zhang, Z., Li, M., Fan, D., Guo, Y., Wang, A., Wang, L., Deng, L., Li, W., Lu, Y., Weng, Q., Liu, K., Huang, T., Zhou, T., Jing, Y., Li, W., Zhang, L., Buckler IV, E.S., Qian, Q., Zhang, Q., Li, J., Han, B. 2010. Genome-wide and fine resolution association studies of 14 agronomic traits in rice land races. Nature Genetics. 42:961-967.

Interpretive Summary: Uncovering the genetic basis of how diverse landraces have adapted to various agro-climatic conditions since domestication is critical to the food security of the world. The small genome of rice provides an excellent test for applying the latest genome sequencing and statistical genetics tools. This study successfully identified genomic variation across these diverse varieties of rice, and for many simpler traits was very successful in identifying key gene controlling these traits. However, the landraces analysis was less successful for complex traits involved in large-scale adaptation, which suggests that other approaches that involve specially created genetic populations will be needed. This study highlights the power of novel approaches to now tap genetic diversity in diverse rice landraces.

Technical Abstract: Here we report genome sequences of 517 diverse rice land races and the identification of ~3.6 million single nucleotide polymorphisms. A high-density haplotype map of rice genome was constructed using a highly accurate imputation method developed for next-generation sequencing data. Initial genome-wide association studies revealed 80 loci with strong association signals underlying fourteen agronomic traits. We further inspected the genetic architecture of the fourteen agronomic traits that explained ~36% of the phenotypic variance on average, which is much higher than those of GWAS in human. The peak signals for six known loci tied to the previously identified genes at high resolution.