Single-step SNPBLUP evaluation in six German beef cattle breeds.

beef cattle genomic evaluation production traits single-step model

Journal

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
ISSN: 1439-0388
Titre abrégé: J Anim Breed Genet
Pays: Germany
ID NLM: 100955807

Informations de publication

Date de publication:
Sep 2023
Historique:
revised: 03 04 2023
received: 05 01 2023
accepted: 04 04 2023
medline: 15 8 2023
pubmed: 17 4 2023
entrez: 16 4 2023
Statut: ppublish

Résumé

The implementation of genomic selection for six German beef cattle populations was evaluated. Although the multiple-step implementation of genomic selection is the status quo in most national dairy cattle evaluations, the breeding structure of German beef cattle, coupled with the shortcoming and complexity of the multiple-step method, makes single step a more attractive option to implement genomic selection in German beef cattle populations. Our objective was to develop a national beef cattle single-step genomic evaluation in five economically important traits in six German beef cattle populations and investigate its impact on the accuracy and bias of genomic evaluations relative to the current pedigree-based evaluation. Across the six breeds in our study, 461,929 phenotyped and 14,321 genotyped animals were evaluated with a multi-trait single-step model. To validate the single-step model, phenotype data in the last 2 years were removed in a forward validation study. For the conventional and single-step approaches, the genomic estimated breeding values of validation animals and other animals were compared between the truncated and the full evaluations. The correlation of the GEBVs between the full and truncated evaluations in the validation animals was slightly higher in the single-step evaluation. The regression of the full GEBVs on truncated GEBVs was close to the optimal value of 1 for both the pedigree-based and the single-step evaluations. The SNP effect estimates from the truncated evaluation were highly correlated with those from the full evaluation, with values ranging from 0.79 to 0.94. The correlation of the SNP effect was influenced by the number of genotyped animals shared between the full and truncated evaluations. The regression coefficients of the SNP effect of the full evaluation on the truncated evaluation were all close to the expected value of 1, indicating unbiased estimates of the SNP markers for the production traits. The Manhattan plot of the SNP effect estimates identified chromosomal regions harbouring major genes for muscling and body weight in breeds of French origin. Based on the regression intercept and slope of the GEBVs of validation animals, the single-step evaluation was neither inflated nor deflated across the six breeds. Overall, the single-step model resulted in a more accurate and stable evaluation. However, due to the small number of genotyped individuals, the single-step method only provided slightly better results when compared to the pedigree-based method.

Identifiants

pubmed: 37061869
doi: 10.1111/jbg.12774
doi:

Substances chimiques

Nonoxynol 26027-38-3

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

496-507

Subventions

Organisme : Landwirtschaftliche Rentenbank

Informations de copyright

© 2023 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.

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Auteurs

Damilola Adekale (D)

Functional Breeding - Genetik und züchterische Verbesserung funktionaler Merkmale, GAU, Göttingen, Germany.
Biometrie, Vereinigte Informationssysteme Tierhaltung w.V., Verden, Germany.

Hatem Alkhoder (H)

Biometrie, Vereinigte Informationssysteme Tierhaltung w.V., Verden, Germany.

Zengting Liu (Z)

Biometrie, Vereinigte Informationssysteme Tierhaltung w.V., Verden, Germany.

Dierck Segelke (D)

Biometrie, Vereinigte Informationssysteme Tierhaltung w.V., Verden, Germany.

Jens Tetens (J)

Functional Breeding - Genetik und züchterische Verbesserung funktionaler Merkmale, GAU, Göttingen, Germany.

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