A Binary Classifier Using SNP Data for Prediction of Phenotypic Outcomes in Hanwoo (Korean) Cattle

Author(s)
Detterer, Dion
Lee, Seung Hwan
Kwan, Paul H
Gondro, Cedric
Publication Date
2013
Abstract
Korean 'Hanwoo' cattle are prized for their high marbling ability and meat quality. Classically, these cattle possess a homogeneous yellow coat colouring, with farmers believing that 'Hanwoo' with white spotted coats are crossbred and therefore unacceptable for breeding purposes. In this study we first attempted to determine if the coat spots were due to a non-'Hanwoo' genetic background or, alternatively, if the trait is intrinsic to the breed. By genotyping 232 (136 spotted) animals from half-sib families on the Illumina Bovine 50K SNP array, we compared the genotyped Hanwoo to other unrelated 'Hanwoo' and European taurine breeds using principal component analysis. Results showed no evidence of crossbreeding in the spotted animals. A differential evolution algorithm was then used to evolve a classifier for the trait which selected 12 SNP with an accuracy of ~82% in separating individuals; further investigation using only haplotypes inherited from the sires resulted in a marked improvement to ~92% accuracy for these 12 SNP. This research highlights the potential for using these SNP as genetic markers to either entirely remove the trait from the population in the long term or manage matings so that the trait is not expressed in the offspring.
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.20, p. 511-514
ISBN
9780473260569
ISSN
1328-3227
Link
Publisher
Association for the Advancement of Animal Breeding and Genetics (AAABG)
Title
A Binary Classifier Using SNP Data for Prediction of Phenotypic Outcomes in Hanwoo (Korean) Cattle
Type of document
Conference Publication
Entity Type
Publication

Files:

NameSizeformatDescriptionLink