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.
journal_name
Heredity (Edinb)journal_title
Heredityauthors
Spindel JE,Begum H,Akdemir D,Collard B,Redoña E,Jannink JL,McCouch Sdoi
10.1038/hdy.2015.113subject
Has Abstractpub_date
2016-04-01 00:00:00pages
395-408issue
4eissn
0018-067Xissn
1365-2540pii
hdy2015113journal_volume
116pub_type
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