title: Single-step genomic model improved reliability and reduced the bias of genomic predictions in Danish Jersey.
abstract: A bias in the trend of genomic estimated breeding values (GEBV) was observed in the Danish Jersey population where the trend of GEBV was smaller than the deregressed proofs for individuals in the validation population. This study attempted to improve the prediction reliability and reduce the bias of predicted genetic trend in Danish Jersey. The data consisted of 1,238 Danish Jersey bulls and 611,695 cows. All bulls were genotyped with the 54K chip, and 1,744 cows were genotyped with either 7K chips (1,157 individuals) or 54K chips (587 individuals). The trait used in the analysis was protein yield. All cows with EBV were used in a single-step approach. Deregressed proofs were used as the response variable. Four alternative approaches were compared with genomic best linear unbiased prediction (GBLUP) model with bulls in the reference data (GBLUPBull): (1) GBLUP with both bulls and genotyped cows in the reference data; (2) GBLUP including a year of birth effect; (3) GEBV from a GBLUP model that accounted for the difference of EBV between dams and maternal grandsires; and (4) using a single-step approach. The results indicated all 4 alternatives could reduce the bias of predicted genetic trend and that the single-step approach performed best. However, not all these approaches improved reliability or reduced inflation of GEBV. The reliability was 0.30 and regression coefficients of deregressed proofs on GEBV were 0.69 in the scenario GBLUPBull. When genotyped cows were included in the reference population, the regression coefficients decreased to 0.59 but the reliability increased to 0.35. If a year effect was included in the model, the prediction reliability decreased to 0.29 and the regression coefficient improved to 0.75. The method in which GEBV were adjusted for the difference between dam EBV and maternal grandsire EBV led to much lower regression coefficients though the reliability increased to 0.4. The single-step approach improved both the reliability, to 0.38 and regression coefficient to 0.78. Therefore, the bias in genetic trend was reduced. The results suggest that implementing the single-step approach is an effective way to improve genomic prediction in Danish Jersey cattle.
authors.affiliation: Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark. Electronic address: peipei.ma@mbg.au.dk.
authors.forename: P
authors.initials: P
authors.lastname: Ma
authors.affiliation: Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark.
authors.forename: M S
authors.initials: MS
authors.lastname: Lund
authors.affiliation: Seges, DK-8200 Aarhus, Denmark.
authors.forename: U S
authors.initials: US
authors.lastname: Nielsen
authors.affiliation: NAV Nordic Cattle Genetic Evaluation, DK-8200 Aarhus, Denmark.
authors.forename: G P
authors.initials: GP
authors.lastname: Aamand
authors.affiliation: Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark.
authors.forename: G
authors.initials: G
authors.lastname: Su
mesh_terms: D000818:Animals; D015982:Bias; D001947:Breeding; D002417:Cattle / Q000235:genetics*; D005260:Female; D016678:Genome; D023281:Genomics / Q000379:methods*; D005838:Genotype; D060005:Genotyping Techniques; D016014:Linear Models; D008297:Male; D008957:Models, Genetic; D008962:Models, Theoretical; D010641:Phenotype; D015203:Reproducibility of Results
keywords: bias of predicted genetic trend; reliability of genomic prediction; single-step method