Genomic Prediction in a Numerically Small Sheep Breed Population Using Imputed Sequence Variants

Author(s)
Moghaddar, N
Brown, D J
Swan, A A
MacLeod, I M
van der Werf, J H J
Publication Date
2019-11
Abstract
The accuracy of genomic prediction for a numerically small sheep breed was investigated based on a large multi-breed admixed reference set using moderate or high density SNP genotypes, imputed whole genome sequence genotypes or selected sequence variants based on a genome wide association study (GWAS). Reference set with weight and eating quality phenotypes was divided into a GWAS sub set (n=4,000), a training set (n=13,466 to 38,098) and a validation set with data of 143 to 169 purebred Dorper sheep. Genomic BLUP was used to estimate genomic breeding values and prediction accuracy was evaluated in the validation set based on the correlation between GBV and corrected phenotypes. Results showed a prediction accuracy between 20% and 30% based on 50k genotypes across different trait, which increased on average by 2.5% to 7.0% by using HD genotypes or selected sequence variants derived from an independent GWAS.
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.23, p. 71-74
ISSN
1328-3227
Link
Publisher
Association for the Advancement of Animal Breeding and Genetics (AAABG)
Title
Genomic Prediction in a Numerically Small Sheep Breed Population Using Imputed Sequence Variants
Type of document
Conference Publication
Entity Type
Publication

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