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Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods
The aim of this study was to compare three methods of genomic prediction: GBLUP, BayesC and BayesGC for genomic prediction of six maternal traits in Landrace sows using a panel of 660 K SNPs. The effects of different priors for the Bayesian methods were also investigated. GBLUP does not take the gen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9796620/ https://www.ncbi.nlm.nih.gov/pubmed/35758628 http://dx.doi.org/10.1111/jbg.12729 |
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author | Kjetså, Maria V. Gjuvsland, Arne B. Nordbø, Øyvind Grindflek, Eli Meuwissen, Theo |
author_facet | Kjetså, Maria V. Gjuvsland, Arne B. Nordbø, Øyvind Grindflek, Eli Meuwissen, Theo |
author_sort | Kjetså, Maria V. |
collection | PubMed |
description | The aim of this study was to compare three methods of genomic prediction: GBLUP, BayesC and BayesGC for genomic prediction of six maternal traits in Landrace sows using a panel of 660 K SNPs. The effects of different priors for the Bayesian methods were also investigated. GBLUP does not take the genetic architecture into account as all SNPs are assumed to have equally sized effects and relies heavily on the relationships between the animals for accurate predictions. Bayesian approaches rely on both fitting SNPs that describe relationships between animals in addition to fitting single SNP effects directly. Both the relationship between the animals and single SNP effects are important for accurate predictions. Maternal traits in sows are often more difficult to record and have lower heritabilities. BayesGC was generally the method with the higher accuracy, although its accuracy was for some traits matched by that of GBLUP and for others by that of BayesC. For piglet mortality within 3 weeks, BayesGC achieved up to 9.2% higher accuracy. For many of the traits, however, the methods did not show significant differences in accuracies. |
format | Online Article Text |
id | pubmed-9796620 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97966202022-12-30 Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods Kjetså, Maria V. Gjuvsland, Arne B. Nordbø, Øyvind Grindflek, Eli Meuwissen, Theo J Anim Breed Genet Original Articles The aim of this study was to compare three methods of genomic prediction: GBLUP, BayesC and BayesGC for genomic prediction of six maternal traits in Landrace sows using a panel of 660 K SNPs. The effects of different priors for the Bayesian methods were also investigated. GBLUP does not take the genetic architecture into account as all SNPs are assumed to have equally sized effects and relies heavily on the relationships between the animals for accurate predictions. Bayesian approaches rely on both fitting SNPs that describe relationships between animals in addition to fitting single SNP effects directly. Both the relationship between the animals and single SNP effects are important for accurate predictions. Maternal traits in sows are often more difficult to record and have lower heritabilities. BayesGC was generally the method with the higher accuracy, although its accuracy was for some traits matched by that of GBLUP and for others by that of BayesC. For piglet mortality within 3 weeks, BayesGC achieved up to 9.2% higher accuracy. For many of the traits, however, the methods did not show significant differences in accuracies. John Wiley and Sons Inc. 2022-06-27 2022-11 /pmc/articles/PMC9796620/ /pubmed/35758628 http://dx.doi.org/10.1111/jbg.12729 Text en © 2022 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Kjetså, Maria V. Gjuvsland, Arne B. Nordbø, Øyvind Grindflek, Eli Meuwissen, Theo Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods |
title | Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods |
title_full | Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods |
title_fullStr | Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods |
title_full_unstemmed | Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods |
title_short | Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods |
title_sort | accuracy of genomic prediction of maternal traits in pigs using bayesian variable selection methods |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9796620/ https://www.ncbi.nlm.nih.gov/pubmed/35758628 http://dx.doi.org/10.1111/jbg.12729 |
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