Local breed proportions and local breed heterozygosity in genomic predictions for crossbred dairy cows.


Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
Nov 2022
Historique:
received: 25 04 2022
accepted: 19 07 2022
pubmed: 29 10 2022
medline: 23 11 2022
entrez: 28 10 2022
Statut: ppublish

Résumé

For genomic prediction of crossbred animals, models that account for the breed origin of alleles (BOA) in marker genotypes can allow the effects of marker alleles to differ depending on their ancestral breed. Previous studies have shown that genomic estimated breeding values for crossbred cows can be calculated using the marker effects that are estimated in the contributing pure breeds and combined based on estimated BOA in the genotypes of the crossbred cows. In the presented study, we further exploit the BOA information for improving the prediction of genomic breeding values of crossbred dairy cows. We investigated 2 types of BOA-derived breed proportions: global breed proportions, defined as the proportion of marker alleles assigned to each breed across the whole genome; and local breed proportions (LBP), defined as the proportions of alleles on chromosome segments which were assigned to each breed. Further, we investigated 2 BOA-derived measures of heterozygosity for the prediction of total genetic value. First, global breed heterozygosity, defined as the proportion of marker loci that have alleles originating in 2 different breeds over the whole genome. Second, local breed heterozygosity (LBH), defined as proportions of marker loci on chromosome segments that had alleles originating in 2 different breeds. We estimated variance related to LBP and LBH on the remaining variation after accounting for prediction with solutions from the genomic evaluations of the pure breeds and validated alternative models for production traits in 5,214 Danish crossbred dairy cows. The estimated LBP variances were 0.9, 1.2, and 1.0% of phenotypic variance for milk, fat, and protein yield, respectively. We observed no clear LBH effect. Cross-validation showed that models with LBP effects had a numerically small but statistically significantly higher predictive ability than models only including global breed proportions. We observed similar improvement in accuracy by the model having an across crossbred residual additive genetic effect, accounting for the additive genetic variation that was not accounted for by the solutions from purebred. For genomic predictions of crossbred animals, estimated BOA can give useful information on breed proportions, both globally in the genome and locally in genome regions, and on breed heterozygosity.

Identifiants

pubmed: 36307242
pii: S0022-0302(22)00619-1
doi: 10.3168/jds.2022-22225
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

9822-9836

Informations de copyright

The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Auteurs

Jón H Eiríksson (JH)

Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark. Electronic address: jonh@qgg.au.dk.

Ismo Strandén (I)

Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland.

Guosheng Su (G)

Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark.

Esa A Mäntysaari (EA)

Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland.

Ole F Christensen (OF)

Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark.

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