Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Genomic prediction of weight and wool traits in a multi-breed sheep population

N. Moghaddar A B D , A. A. Swan A C and J. H. J. van der Werf A B
+ Author Affiliations
- Author Affiliations

A Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW 2351, Australia.

B Schools of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.

C Animal Genetics & Breeding Unit (AGBU), University of New England, Armidale, NSW 2351, Australia.

D Corresponding author. Email: n.moghaddar@une.edu.au

Animal Production Science 54(5) 544-549 https://doi.org/10.1071/AN13129
Submitted: 4 April 2013  Accepted: 16 July 2013   Published: 17 September 2013

Abstract

The objective of this study was to predict the accuracy of genomic prediction for 26 traits, including weight, muscle, fat, and wool quantity and quality traits, in Australian sheep based on a large, multi-breed reference population. The reference population consisted of two research flocks, with the main breeds being Merino, Border Leicester (BL), Poll Dorset (PD), and White Suffolk (WS). The genomic estimated breeding value (GEBV) was based on GBLUP (genomic best linear unbiased prediction), applying a genomic relationship matrix calculated from the 50K Ovine SNP chip marker genotypes. The accuracy of GEBV was evaluated as the Pearson correlation coefficient between GEBV and accurate estimated breeding value based on progeny records in a set of genotyped industry animals. The accuracies of weight traits were relatively low to moderate in PD and WS breeds (0.11–0.27) and moderate to relatively high in BL and Merino (0.25–0.63). The accuracy of muscle and fat traits was moderate to relatively high across all breeds (between 0.21 and 0.55). The accuracy of GEBV of yearling and adult wool traits in Merino was, on average, high (0.33–0.75). The results showed the accuracy of genomic prediction depends on trait heritability and the effective size of the reference population, whereas the observed GEBV accuracies were more related to the breed proportions in the multi-breed reference population. No extra gain in within-breed GEBV accuracy was observed based on across breed information. More investigations are required to determine the precise effect of across-breed information on within-breed genomic prediction.


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