IC4R006-GWAS-2015-25689273
Contents
Project Title
Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines
The Background of This Project
- Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice.
- Genomic selection is a promising breeding technique that aims to improve the efficiency and speed of the breeding process. While it has been shown to be effective in crops such as wheat and corn, it has not yet been applied to rice breeding. Genome-wide association studies (GWAS), by contrast, are used to identify genes or QTLs that underlie traits of importance to breeding such as yield, flowering time, or plant height, and has been performed successfully in rice. Here, we experiment
with applying genomic selection in conjunction with GWAS to a rice breeding program at the International Rice Research In- stitute in the Philippines and show that genomic selection can result in more accurate predictions of breeding line performance than pedigree data alone and that GWAS results can inform the results of GS. Our results suggest that GS could be an effective tool for increasing the efficiency of rice breeding.
File:.PNG
figure 1 Population structure of current association panel which consisted mostly of the indica accessions. (A) Scree plot from GAPIT showing the selection of PCs for association study. (B) PCA plot of first two components. (C) Bayesian clustering of 220 rice accessions using STRUCTURE program.
Plant Culture & Treatment
Research Findings
Figure 2 Comparison of LD patterns and LD decay in the whole panel and subgroups. The whole genome r 2 values from PLINK are first sorted considering distance, and then divided into 100 blocks of 20 kb. The r 2 values in each block are averaged and plotted against the genetic distance for different subgroups.
Labs working on this Project
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America
- International Rice Research Institute, Los Baños, Philippines
- International Center for Tropical Agriculture, Cali, Colombia
- Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
- US Department of Agriculture—Agricultural Research Service (USDA-ARS), Ithaca, New York, United States of America
Corresponding Author
- Jean-Luc Jannink(jj332@cornell.edu)
- Susan R. McCouch(srm4@cornell.edu)
