Across-country genomic predictions in Norwegian and New Zealand Composite sheep populations with similar development history.

Autor: Oliveira HR; Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.; Department of Animal Biosciences, Centre for Genetic Improvement of Livestock (CGIL), University of Guelph, Guelph, ON, Canada., McEwan JC; AgResearch Limited, Invermay Agricultural Centre, Mosgiel, New Zealand., Jakobsen JH; The Norwegian Association of Sheep and Goat Breeders, Ås, Norway., Blichfeldt T; The Norwegian Association of Sheep and Goat Breeders, Ås, Norway., Meuwissen THE; Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway., Pickering NK; Focus Genetics, Ahuriri, New Zealand., Clarke SM; AgResearch Limited, Invermay Agricultural Centre, Mosgiel, New Zealand., Brito LF; Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.; Department of Animal Biosciences, Centre for Genetic Improvement of Livestock (CGIL), University of Guelph, Guelph, ON, Canada.
Jazyk: angličtina
Zdroj: Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie [J Anim Breed Genet] 2022 Jan; Vol. 139 (1), pp. 1-12. Date of Electronic Publication: 2021 Aug 21.
DOI: 10.1111/jbg.12642
Abstrakt: The goal of this study was to assess the feasibility of across-country genomic predictions in Norwegian White Sheep (NWS) and New Zealand Composite (NZC) sheep populations with similar development history. Different training populations were evaluated (i.e., including only NWS or NZC, or combining both populations). Predictions were performed using the actual phenotypes (normalized) and the single-step GBLUP via Bayesian inference. Genotyped NWS animals born in 2016 (N = 267) were used to assess the accuracy and bias of genomic estimated breeding values (GEBVs) predicted for birth weight (BW), weaning weight (WW), carcass weight (CW), EUROP carcass classification (EUC), and EUROP fat grading (EUF). The accuracy and bias of GEBVs differed across traits and training population used. For instance, the GEBV accuracies ranged from 0.13 (BW) to 0.44 (EUC) for GEBVs predicted including only NWS, from 0.06 (BW) to 0.15 (CW) when including only NZC, and from 0.10 (BW) to 0.41 (EUC) when including both NWS and NZC animals in the training population. The regression coefficients used to assess the spread of GEBVs (bias) ranged from 0.26 (BW) to 0.64 (EUF) for only NWS, 0.10 (EUC) to 0.52 (CW) for only NZC, and from 0.42 (WW) to 2.23 (EUC) for both NWS and NZC in the training population. Our findings suggest that across-country genomic predictions based on ssGBLUP might be possible for NWS and NZC, especially for novel traits.
(© 2021 Wiley-VCH GmbH.)
Databáze: MEDLINE
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