The effect of genomic information on optimal contribution selection in livestock breeding programs

Abstract

Background: Long-term benefits in animal breeding programs require that increases in genetic merit be balanced with the need to maintain diversity (lost due to inbreeding). This can be achieved by using optimal contribution selection. The availability of high-density DNA marker information enables the incorporation of genomic data into optimal contribution selection but this raises the question about how this information affects the balance between genetic merit and diversity.

Methods: The effect of using genomic information in optimal contribution selection was examined based on simulated and real data on dairy bulls. We compared the genetic merit of selected animals at various levels of co-ancestry restrictions when using estimated breeding values based on parent average, genomic or progeny test information. Furthermore, we estimated the proportion of variation in estimated breeding values that is due to within-family differences.

Results: Optimal selection on genomic estimated breeding values increased genetic gain. Genetic merit was further increased using genomic rather than pedigree-based measures of co-ancestry under an inbreeding restriction policy. Using genomic instead of pedigree relationships to restrict inbreeding had a significant effect only when the population consisted of many large full-sib families; with a half-sib family structure, no difference was observed. In real data from dairy bulls, optimal contribution selection based on genomic estimated breeding values allowed for additional improvements in genetic merit at low to moderate inbreeding levels. Genomic estimated breeding values were more accurate and showed more within-family variation than parent average breeding values; for genomic estimated breeding values, 30 to 40% of the variation was due to within-family differences. Finally, there was no difference between constraining inbreeding via pedigree or genomic relationships in the real data.

Conclusions: The use of genomic estimated breeding values increased genetic gain in optimal contribution selection. Genomic estimated breeding values were more accurate and showed more within-family variation, which led to higher genetic gains for the same restriction on inbreeding. Using genomic relationships to restrict inbreeding provided no additional gain, except in the case of very large full-sib families.

Figure 1

Average genetic merit of animals selected based on PA EBV or GEBV for various levels of constrained inbreeding based on genomic relationships in a half-sib population.

Figure 2

Average genetic merit of animals selected based on GEBV and constraining inbreeding based on pedigree or genomic relationships in a half sib population.

Figure 3

Increase in genetic gain when selecting on GEBV and constraining inbreeding based on pedigree or genomic relationships in a full sib population.

Figure 4

Optimal contribution selection of ADHIS bulls at different levels of genomic co-ancestry of selected bulls, using three alternative estimates of genetic merit for protein yield.

Figure 5

Optimal contribution selection of LIC Holstein bulls at different levels of genomic co-ancestry of selected bulls, using three alternative estimates of genetic merit for protein yield.

Figure 6

Average increase in genetic merit when selecting LIC bulls on GEBV for protein yield and constraining inbreeding based on pedigree or genomic relationships.

Figure 7

Average increase in genetic merit when selecting ADHIS bulls on GEBV for protein yield and constraining inbreeding based on pedigree or genomic relationships