title: Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations.
abstract: The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data consisted of genotypes of 15,966 European Holstein bulls from the combined EuroGenomics reference population. Genotypes with the low-density chip were created by erasing markers from 50,000-marker data. The studies were performed in the Nordic countries (Denmark, Finland, and Sweden) using a BLUP model for prediction of DGV and in France using a genomic marker-assisted selection approach for prediction of GEBV. Imputation in both studies was done using a combination of the DAGPHASE 1.1 and Beagle 2.1.3 software. Traits considered were protein yield, fertility, somatic cell count, and udder depth. Imputation of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test data. Mean imputation error rates when using national reference animals was 5.5 and 3.9% in the Nordic countries and France, respectively, whereas imputation based on the EuroGenomics reference data set gave mean error rates of 4.0 and 2.1%, respectively. Prediction of GEBV based on genotypes imputed with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected in the French study, and a loss of 0.06 was observed for the mean reliability of DGV in the Nordic study. Consequently, the reliability of DGV using the imputed SNP data was 0.38 based on national reference data, and 0.48 based on EuroGenomics reference data in the Nordic validation, and the reliability of GEBV using the imputed SNP data was 0.41 based on national reference data, and 0.44 based on EuroGenomics reference data in the French validation.
authors.affiliation: INRA, UMR1313 Génétique Animale et Biologie Intégrative (GABI), 78350 Jouy-en-Josas, France. romain.dassonneville@jouy.inra.fr
authors.forename: R
authors.initials: R
authors.lastname: Dassonneville
authors.forename: R F
authors.initials: RF
authors.lastname: Brøndum
authors.forename: T
authors.initials: T
authors.lastname: Druet
authors.forename: S
authors.initials: S
authors.lastname: Fritz
authors.forename: F
authors.initials: F
authors.lastname: Guillaume
authors.forename: B
authors.initials: B
authors.lastname: Guldbrandtsen
authors.forename: M S
authors.initials: MS
authors.lastname: Lund
authors.forename: V
authors.initials: V
authors.lastname: Ducrocq
authors.forename: G
authors.initials: G
authors.lastname: Su
mesh_terms: D000818:Animals; D001947:Breeding / Q000191:economics / Q000379:methods*; D002417:Cattle / Q000235:genetics*; D005819:Genetic Markers; D005821:Genetic Techniques / Q000662:veterinary*; D016678:Genome; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D019655:Quantitative Trait, Heritable; D015203:Reproducibility of Results; D012641:Selection, Genetic
chemical_list: D005819:Genetic Markers