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Performance of genomic selection in mice.

Andrés Legarra¹, Christèle Robert-Granié, Eduardo Manfredi

¹INRA, UR 631, F-31326 Auzeville, France. andres.legarra@toulouse.inra.fr

|September 2, 2008

Summary

Genomic selection using genomewide markers offers modest gains in predictive ability across families, but limited improvements within families. This study questions its broad application in genetic evaluation.

Area of Science:

Animal and Plant Breeding
Quantitative Genetics
Genomics

Background:

Genetic evaluation is crucial for selection plans in breeding.
Genomic selection, utilizing extensive genetic marker data, is a recent development.
Evidence for the performance of genomic selection is limited.

Purpose of the Study:

To empirically compare the performance of genomic selection against traditional methods.
To assess the impact of genomewide markers versus pedigree and phenotypic information.
To evaluate the utility of across- and within-family information in genetic evaluation.

Main Methods:

Analysis of four traits in a heterogeneous mouse population (1884 individuals, 10,946 SNP markers).
Comparison of three selection strategies: pedigree/phenotype, genomewide markers/phenotype, and combined.

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Application of linear mixed models and cross-validation techniques for predictive ability estimation.

Main Results:

Genomewide markers increased predictive ability by up to 0.22 across families and 0.03 within families.
Increases in accuracy of genetic value prediction were up to 0.57 (across family) and 0.14 (within family).
Within-family information proved more accurate than across-family information; populational linkage disequilibrium showed limitations.

Conclusions:

Genomic selection shows potential for improving across-family predictions but offers minimal gains within families.
The effectiveness of genomic selection may be population- and family-structure dependent.
Populational linkage disequilibrium alone is not a fully reliable basis for genetic evaluation, raising questions about certain genomic selection applications.