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Can multi-subpopulation reference sets improve the genomic predictive ability for pigs?

A Fangmann, S Bergfelder-Drüing, E Tholen

Journal of Animal Science

|December 8, 2015

Summary

This summary is machine-generated.

Multi-subpopulation genomic prediction did not improve breeding values for German Large White pigs compared to within-subpopulation analysis. Increasing reference population size within subpopulations is recommended for enhancing prediction accuracy.

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Area of Science:

Animal Breeding and Genetics
Genomics
Quantitative Genetics

Background:

Genomic evaluations typically use within-breed analyses, requiring substantial reference populations.
Stratified subpopulations in German Large White pigs necessitate exploring multi-subpopulation genomic prediction.

Purpose of the Study:

To determine if multi-subpopulation genomic prediction surpasses within-subpopulation prediction in German Large White pigs.
To assess the impact of subpopulation differentiation on prediction accuracy.

Main Methods:

Genomic BLUP was used to estimate direct genomic breeding values for "number of piglets born alive".
Genotype data from 2,053 German Large White pigs across five commercial breeding companies were analyzed.
A 5-fold cross-validation with 20 replications evaluated prediction accuracy.

Main Results:

Multi-subpopulation genomic prediction did not yield better accuracy than within-subpopulation evaluation.
Prediction accuracy was already high for within-subpopulation analyses.
Closely related subpopulation sets showed marginal improvement over distantly related ones, but not over within-subpopulation sets.

Conclusions:

Limited genetic connectedness between German Large White subpopulations restricts benefits of multi-subpopulation genomic prediction.
Enlarging within-subpopulation reference populations, e.g., with genotyped females, is a more effective strategy.