Delivering The Fruits Of Plant Genomics: Using Genotyping-By-Sequencing (Gbs), Genomic Selection (Gs), And Genome-Wide Association Studies (Gwas) To Improve Rice Breeding In The Tropics

Abstract

To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable to keep pace with demand. 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 I evaluate for the first time its efficacy for breeding inbred lines of rice. I performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped using a genotyping-by-sequencing protocol optimized for rice in the first part of this thesis. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Furthermore, the most accurate GS models were those that incorporated fixed variables derived from genome-wide-association studies (GWAS) performed on rice model training data and by incorporating data from multiple environments. Two breeding schemas are then presented, including an extended, two-stream breeding design that can be used to efficiently integrate novel variation into elite breeding populations, expanding genetic diversity and enhancing the potential for sustainable productivity gains.