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Genet Sel Evol. 2011 May 17;43:19. doi: 10.1186/1297-9686-43-19.

Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction.

Author information

1
Christian-Albert-University, Institute of Animal Breeding and Husbandry, 24908 Kiel, Germany. zengting.liu@vit.de

Abstract

BACKGROUND:

The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information.

METHODS:

Direct genomic values were estimated for German Holstein cattle with a genomic BLUP model including a residual polygenic effect. A total of 17,429 genotyped Holstein bulls were evaluated using the phenotypes of 44 traits. The Interbull genomic validation test was implemented to investigate how the inclusion of a residual polygenic effect impacted genomic estimated breeding values.

RESULTS:

As the number of reference bulls increased, both the variance of the estimates of single nucleotide polymorphism effects and the reliability of the direct genomic values of selection candidates increased. Fitting a residual polygenic effect in the model resulted in less biased genome-enhanced breeding values and decreased the correlation between direct genomic values and estimated breeding values of sires in the reference population.

CONCLUSIONS:

Genetic evaluation of dairy cattle enhanced with genomic information is highly effective in increasing reliability, as well as using large genomic reference populations. We found that fitting a residual polygenic effect reduced the bias in genome-enhanced breeding values, decreased the correlation between direct genomic values and sire's estimated breeding values and made genome-enhanced breeding values more consistent in mean and variance as is the case for pedigree-based estimated breeding values.

PMID:
21586131
PMCID:
PMC3107172
DOI:
10.1186/1297-9686-43-19
[Indexed for MEDLINE]
Free PMC Article

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