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Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle
Bias and inflation in genomic evaluation with the single-step methods have been reported in several studies. Incompatibility between the base-populations of the pedigree-based and the genomic relationship matrix (G) could be a reason for these biases. Inappropriate ways of accounting for missing par...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467032/ https://www.ncbi.nlm.nih.gov/pubmed/35752161 http://dx.doi.org/10.1093/jas/skac227 |
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author | Belay, Tesfaye K Eikje, Leiv S Gjuvsland, Arne B Nordbø, Øyvind Tribout, Thierry Meuwissen, Theo |
author_facet | Belay, Tesfaye K Eikje, Leiv S Gjuvsland, Arne B Nordbø, Øyvind Tribout, Thierry Meuwissen, Theo |
author_sort | Belay, Tesfaye K |
collection | PubMed |
description | Bias and inflation in genomic evaluation with the single-step methods have been reported in several studies. Incompatibility between the base-populations of the pedigree-based and the genomic relationship matrix (G) could be a reason for these biases. Inappropriate ways of accounting for missing parents could be another reason for biases in genetic evaluations with or without genomic information. To handle these problems, we fitted and evaluated a fixed covariate (J) that contains ones for genotyped animals and zeros for unrelated non-genotyped animals, or pedigree-based regression coefficients for related non-genotyped animals. We also evaluated alternative ways of fitting the J covariate together with genetic groups on biases and stability of breeding value estimates, and of including it into G as a random effect. In a whole vs. partial data set comparison, four scenarios were investigated for the partial data: genotypes missing, phenotypes missing, both genotypes and phenotypes missing, and pedigree missing. Fitting J either as fixed or random reduced level-bias and inflation and increased stability of genomic predictions as compared to the basic model where neither J nor genetic groups were fitted. In most models, genomic predictions were largely biased for scenarios with missing genotype and phenotype information. The biases were reduced for models which combined group and J effects. Models with these corrected group covariates performed better than the recently published model where genetic groups were encapsulated and fitted as random via the Quaas and Pollak transformation. In our Norwegian Red cattle data, a model which combined group and J regression coefficients was preferred because it showed least bias and highest stability of genomic predictions across the scenarios. |
format | Online Article Text |
id | pubmed-9467032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-94670322022-09-13 Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle Belay, Tesfaye K Eikje, Leiv S Gjuvsland, Arne B Nordbø, Øyvind Tribout, Thierry Meuwissen, Theo J Anim Sci Animal Genetics and Genomics Bias and inflation in genomic evaluation with the single-step methods have been reported in several studies. Incompatibility between the base-populations of the pedigree-based and the genomic relationship matrix (G) could be a reason for these biases. Inappropriate ways of accounting for missing parents could be another reason for biases in genetic evaluations with or without genomic information. To handle these problems, we fitted and evaluated a fixed covariate (J) that contains ones for genotyped animals and zeros for unrelated non-genotyped animals, or pedigree-based regression coefficients for related non-genotyped animals. We also evaluated alternative ways of fitting the J covariate together with genetic groups on biases and stability of breeding value estimates, and of including it into G as a random effect. In a whole vs. partial data set comparison, four scenarios were investigated for the partial data: genotypes missing, phenotypes missing, both genotypes and phenotypes missing, and pedigree missing. Fitting J either as fixed or random reduced level-bias and inflation and increased stability of genomic predictions as compared to the basic model where neither J nor genetic groups were fitted. In most models, genomic predictions were largely biased for scenarios with missing genotype and phenotype information. The biases were reduced for models which combined group and J effects. Models with these corrected group covariates performed better than the recently published model where genetic groups were encapsulated and fitted as random via the Quaas and Pollak transformation. In our Norwegian Red cattle data, a model which combined group and J regression coefficients was preferred because it showed least bias and highest stability of genomic predictions across the scenarios. Oxford University Press 2022-06-25 /pmc/articles/PMC9467032/ /pubmed/35752161 http://dx.doi.org/10.1093/jas/skac227 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Animal Genetics and Genomics Belay, Tesfaye K Eikje, Leiv S Gjuvsland, Arne B Nordbø, Øyvind Tribout, Thierry Meuwissen, Theo Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle |
title | Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle |
title_full | Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle |
title_fullStr | Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle |
title_full_unstemmed | Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle |
title_short | Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle |
title_sort | correcting for base-population differences and unknown parent groups in single-step genomic predictions of norwegian red cattle |
topic | Animal Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467032/ https://www.ncbi.nlm.nih.gov/pubmed/35752161 http://dx.doi.org/10.1093/jas/skac227 |
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