Computer simulation was used to examine the relationship between the number of loci included in the model and the accuracy of whole-genome methods for genetic evaluation. Random-regression BLUP (RR-BLUP) and Bayesian inference (Bayes-B) were compared with BLUP based on trait phenotypes and pedigree (TP-BLUP), where the genomic information consisted of genotypes at 110 or 2010 unlinked SNP loci. Of these loci, 10 were the actual trait loci. Accuracies for RR-BLUP were much higher than for TP-BLUP with 110 loci, but they were closer to TP-BLUP with 2010 loci. Accuracies with Bayes-B were close to 1 with 110 or with 2010 loci. Results for Bayes-B were also examined with a range of 3000 to 60 000 markers in linkage disequilibrium on 30 chromosomes. Increasing the number of markers did not lower the accuracy of Bayes-B. Thus, Bayes-B seems to be well suited for whole-genome analyses with large numbers of loci. This may not be the case for RR-BLUP.
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Document Type: Research Article
Department of Animal Science, Iowa State University, Ames, IA, USA,Center for Integrated Animal Genomics, Iowa State University, Ames, IA, USA
Department of Animal Science, Iowa State University, Ames, IA, USA
Applied Genetics Network, Davos, Switzerland
Pioneer Hi-Bred, a DuPont Business, Johnston, IA, USA
Publication date: 01 December 2007
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