title: Performance of genomic selection in mice.
abstract: Selection plans in plant and animal breeding are driven by genetic evaluation. Recent developments suggest using massive genetic marker information, known as "genomic selection." There is little evidence of its performance, though. We empirically compared three strategies for selection: (1) use of pedigree and phenotypic information, (2) use of genomewide markers and phenotypic information, and (3) the combination of both. We analyzed four traits from a heterogeneous mouse population (http://gscan.well.ox.ac.uk/), including 1884 individuals and 10,946 SNP markers. We used linear mixed models, using extensions of association analysis. Cross-validation techniques were used, providing assumption-free estimates of predictive ability. Sampling of validation and training data sets was carried out across and within families, which allows comparing across- and within-family information. Use of genomewide genetic markers increased predictive ability up to 0.22 across families and up to 0.03 within families. The latter is not statistically significant. These values are roughly comparable to increases of up to 0.57 (across family) and 0.14 (within family) in accuracy of prediction of genetic value. In this data set, within-family information was more accurate than across-family information, and populational linkage disequilibrium was not a completely accurate source of information for genetic evaluation. This fact questions some applications of genomic selection.
authors.affiliation: INRA, UR 631, F-31326 Auzeville, France. andres.legarra@toulouse.inra.fr
authors.forename: Andrés
authors.initials: A
authors.lastname: Legarra
authors.forename: Christèle
authors.initials: C
authors.lastname: Robert-Granié
authors.forename: Eduardo
authors.initials: E
authors.lastname: Manfredi
authors.forename: Jean-Michel
authors.initials: JM
authors.lastname: Elsen