title: On the limited increase in validation reliability using high-density genotypes in genomic best linear unbiased prediction: observations from Fleckvieh cattle.
abstract: This study investigated reliability of genomic predictions using medium-density (40,089; 50K) or high-density (HD; 388,951) marker sets. We developed an approximate method to test differences in validation reliability for significance. Model-based reliability and the effect of HD genotypes on inflation of predictions were analyzed additionally. Genomic breeding values were predicted for at least 1,321 validation bulls based on phenotypes and genotypes of at least 5,324 calibration bulls by means of a linear model in milk, fat, and protein yield; somatic cell score; milkability; muscling; udder, feet, and legs score as well as stature. In total, 1,485 bulls were actually HD genotyped and HD genotypes of the other animals were imputed from 50K genotypes using FImpute software. Validation reliability was measured as the coefficient of determination of the weighted regression of daughter yield deviations on predicted breeding values divided by the reliability of daughter yield deviations and inflation was evaluated by the slope of this regression. Model-based reliability was calculated from the model. Distributions for validation reliability of 50K markers were derived by repeated sampling of 50,000-marker samples from HD to test differences in validation reliability statistically. Additionally, the benefit of HD genotypes in validation reliability was tested by repeated sampling of validation groups and calculation of the difference in validation reliability between HD and 50K genotypes for the sampled groups of bulls. The mean benefit in validation reliability of HD genotypes was 0.015 compared with real 50K genotypes and 0.028 compared with 50K samples from HD affected by imputation error and was significant for all traits. The model-based reliability was, on average, 0.036 lower and the regression coefficient was 0.036 closer to the expected value with HD genotypes. The observed gain in validation reliability with HD genotypes was similar to expectations based on the number of markers and the effective number of segregating chromosome segments. Sampling error in the marker-based relationship coefficients causing overestimation of the model-based reliability was smaller with HD genotypes. Inflation of the genomic predictions was reduced with HD genotypes, accordingly. Similar effects on model-based reliability and inflation, but not on the validation reliability, were obtained by shrinkage estimation of the realized relationship matrix from 50K genotypes.
authors.affiliation: Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, 85586 Poing, Germany. Electronic address: johann.ertl@lfl.bayern.de.
authors.forename: J
authors.initials: J
authors.lastname: Ertl
authors.affiliation: Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, 85586 Poing, Germany.
authors.forename: C
authors.initials: C
authors.lastname: Edel
authors.affiliation: Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, 85586 Poing, Germany.
authors.forename: R
authors.initials: R
authors.lastname: Emmerling
authors.affiliation: Chair of Animal Breeding, Technische Universität München, 85354 Freising, Germany.
authors.forename: H
authors.initials: H
authors.lastname: Pausch
authors.affiliation: Chair of Animal Breeding, Technische Universität München, 85354 Freising, Germany.
authors.forename: R
authors.initials: R
authors.lastname: Fries
authors.affiliation: Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, 85586 Poing, Germany.
authors.forename: K-U
authors.initials: KU
authors.lastname: Götz
mesh_terms: D000818:Animals; D001947:Breeding; D002417:Cattle; D016678:Genome; D023281:Genomics / Q000379:methods*; D005838:Genotype; D016014:Linear Models; D008297:Male; D008892:Milk / Q000737:chemistry; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D015203:Reproducibility of Results
keywords: genomic evaluation; imputation; marker density