Genomic prediction when some animals are not genotyped
By Ole F. Christensen, M. Lund. Genetics Selection Evolution, 2010
813 citations recorded by the source corpus.
BackgroundThe use of genomic selection in breeding programs may increase the rate of genetic improvement, reduce the generation time, and provide higher accuracy of estimated breeding values (EBVs). A number of different methods have been developed for genomic prediction of breeding values, but many of them assume that all animals have been genotyped. In practice, not all animals are genotyped, and the methods have to be adapted to this situation.ResultsIn this paper we provide an extension of a linear mixed model method for genomic prediction to the situation with non-genotyped animals. The model specifies that a breeding value is the sum of a genomic and a polygenic genetic random effect, where genomic genetic random effects are correlated with a genomic relationship matrix constructed from markers and the polygenic genetic random effects are correlated with the usual relationship matrix. The extension of the model to non-genotyped animals is made by using the pedigree to derive an extension of the genomic relationship matrix to non-genotyped animals. As a result, in the extended model the estimated breeding values are obtained by blending the information used to compute traditional EBVs and the information used to compute purely genomic EBVs. Parameters in the model are estimated using average information REML and estimated breeding values are best linear unbiased predictions (BLUPs). The method is illustrated using a simulated data set.ConclusionsThe extension of the method to non-genotyped animals presented in this paper makes it possible to integrate all the genomic, pedigree and phenotype information into a one-step procedure for genomic prediction. Such a one-step procedure results in more accurate estimated breeding values and has the potential to become the standard tool for genomic prediction of breeding values in future practical evaluations in pig and cattle breeding.
Subfields: Genetics, Small Animals
View Paper: https://www.semanticscholar.org/paper/3c159ad5462b295e5516db7f0fac0d686202fa6f
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In Genetics
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Citations in the corpus
- Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding (2013, methodology): “The inverse of G, which can be used to compute GBLUP (see Equation 4), has a relatively simple form (Aguilar et al. 2010; Christensen and Lund 2010); however, computing G21 requires inverting the matrix of genomic relationships of individuals with genotypes that may be singular.”