Predictive ability of selected subsets of single nucleotide polymorphisms (SNPs) in a moderately sized dairy cattle population

J. I. Weller, G. Glick, A. Shirak, E. Ezra, E. Seroussi, M. Shemesh, Y. Zeron, M. Ron
  • animal, January 2014, Cambridge University Press
  • DOI: 10.1017/s1751731113002188

Can genetic markers from a small population be used to predict genetic values of young bulls

What is it about?

Several studies have shown that computation of genomic estimated breeding values with accuracies significantly greater than parent average estimated breeding values requires genotyping of at least several thousand progeny-tested bulls. Genomic estimated breeding values were derived based on selected subsets of markers from the Illumina BovineSNP50 BeadChip. SNPs were selected based on the effects of each marker on the bulls’ genetic evaluations in 2012 and 2008, respectively. The difference between the correlation of GEBV and current EBV and the correlation of the parent average and current EBV was greater than 0.25 for all traits if SNPs were selected based on the 2012 evaluations, but not if SNPS were selected based on 2008 evaluations. Other methods of selection of SNPs may significantly improve genetic evaluations for moderately sized populations.

Why is it important?

Although genomic evaluation works well for very large populations, this is not the case for smaller populations, or traits measured only on a fraction of the population. Genomic evaluations derived from selected sets of markers can outperform evaluations derived from analysis of all markers. Genomic evaluations derived from selected sets of markers can outperform parent averages, even if the training population includes less than 1000 bulls.


Dr Joel Ira Weller (Author)
ARO, The Volcani Center

This study raises the possibility that other methods of selection of SNPs could significantly improve genomic evaluations derived for moderately sized populations.

The following have contributed to this page: Dr Joel Ira Weller