Accuracy of Genomic Prediction for Merino Wool Traits Using High-Density Marker Genotypes

Author(s)
Moghaddar, Nasiroddin
Swan, Andrew
Van Der Werf, Julius H
Publication Date
2015
Abstract
High-density (HD) marker genotypes could increase the accuracy of genomic prediction by providing stronger linkage disequilibrium (LD) between markers and quantitative trait loci affecting a trait, especially in populations with a high genetic diversity such as Australian Merino sheep. The aim of this study was to compare the accuracy of genomic prediction for Merino yearling and adult wool traits based on observed and imputed 600K single nucleotide polymorphism (SNP) marker genotypes with the accuracy based on moderate-density (50K) marker genotypes. Genomic best linear unbiased prediction (GBLUP) and a Bayesian approach (BayesR) were used as prediction methods. Results showed a small relative increase in accuracy between 2 to 15% (of the previous accuracy) when using a HD marker set. The results of BayesR were on average similar to GBLUP. Considerably higher (up to 25% relative increase) in prediction accuracy was observed for animals with lower genomic relationship to the reference population.
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.21, p. 165-168
ISBN
9780646945545
ISSN
1328-3227
Link
Publisher
Association for the Advancement of Animal Breeding and Genetics (AAABG)
Title
Accuracy of Genomic Prediction for Merino Wool Traits Using High-Density Marker Genotypes
Type of document
Conference Publication
Entity Type
Publication

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