P.M. VanRaden*1, C.P. Van Tassell1,2, G.R. Wiggans1, T.S. Sonstegard2, R.D. Schnabel3, J.F. Taylor3, and F.S. Schenkel4
1Animal Improvement Programs
Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
2 Bovine Functional Genomics Laboratory, Agricultural Research
Service, USDA, Beltsville, MD 20705-2350
3Division of Animal
Sciences, University of Missouri, Columbia, MO 65211
4 Centre for
Genetic Improvement of Livestock, Department of Animal and Poultry Science,
University of Guelph, Guelph, Ontario N1G 2W1, Canada
2008 J. Dairy Sci. (?)
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Genetic progress will increase when breeders examine genotypes instead of only pedigrees and phenotypes. Genotypes for 38,416 markers and August 2003 genetic evaluations for 3,576 Holstein bulls born before 1999 were used to predict January 2008 daughter deviations for 1,759 bulls born from 1999 through 2002. Genotypes were generated using the Illumina BovineSNP50 BeadChip and DNA from semen contributed by US and Canadian artificial-insemination organizations to the Cooperative Dairy DNA Repository. Genomic predictions for 5 yield traits, 5 fitness traits, 16 conformation traits, and net merit were computed using a linear model with an assumed normal distribution for marker effects and also using a nonlinear model with a heavier tailed prior to account for major genes. The official parent average from 2003 and a 2003 parent average computed from only the subset of genotyped ancestors were combined with genomic predictions using a selection index. Combined predictions were more accurate than official parent averages for all 27 traits. The coefficients of determination (R2) were 0.02 to 0.38 higher with nonlinear genomic predictions included than from parent average alone. Linear genomic predictions had R2 similar to those from nonlinear predictions but averaged just 0.01 lower. Largest benefits of genomic prediction were for fat percentage because of a known gene with large effect. The R2 were converted to realized reliabilities by dividing by mean reliability of 2008 daughter deviations and then adding the difference between published and observed reliabilities of 2003 parent averages. When averaged across all traits, combined genomic predictions had realized reliabilities that were 23% higher than reliabilities of parent averages (50 versus 27%), and gains in information were equivalent to 11 additional daughter records. Reliability increased more by doubling the number of bulls genotyped than the number of markers genotyped. Genomic prediction can greatly increase the accuracy of estimated genetic merit by tracing the inheritance of genes with small effects.
(Key words: genomic selection, genomic prediction, reliability, evaluation accuracy)