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Heredity (Edinb). 2016 Apr;116(4):395-408. doi: 10.1038/hdy.2015.113. Epub 2016 Feb 10.

Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement.

Author information

1
Department of Plant Breeding and Genetics, 240 Emerson Hall, Cornell University, Ithaca, NY, USA.
2
Department of Plant Breeding, Genetics and Biotechnology, International Rice Research Institute, Los Baños, Philippines.
3
USDA-ARS, North Atlantic Ares, Robert W. Holley Center for Agriculture and Health, Ithaca, NY, USA.

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 technique that helps accelerate the rate of genetic gain in breeding by using whole-genome data to predict the breeding value of offspring. Here, we describe a new GS model that combines RR-BLUP with markers fit as fixed effects selected from the results of a genome-wide-association study (GWAS) on the RR-BLUP training data. We term this model GS + de novo GWAS. In a breeding population of tropical rice, GS + de novo GWAS outperformed six other models for a variety of traits and in multiple environments. On the basis of these results, we propose an extended, two-part breeding design that can be used to efficiently integrate novel variation into elite breeding populations, thus expanding genetic diversity and enhancing the potential for sustainable productivity gains.

PMID:
26860200
PMCID:
PMC4806696
DOI:
10.1038/hdy.2015.113
[Indexed for MEDLINE]
Free PMC Article

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