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Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals
With an increase in the number of animals genotyped there has been a shift from using pedigree relationship matrices (A) to genomic ones. As the use of genomic relationship matrices (G) has increased, new methods to build or approximate G have developed. We investigated whether the way variance comp...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7053865/ https://www.ncbi.nlm.nih.gov/pubmed/31955195 http://dx.doi.org/10.1093/jas/skaa019 |
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author | Aldridge, Michael N Vandenplas, Jérémie Bergsma, Rob Calus, Mario P L |
author_facet | Aldridge, Michael N Vandenplas, Jérémie Bergsma, Rob Calus, Mario P L |
author_sort | Aldridge, Michael N |
collection | PubMed |
description | With an increase in the number of animals genotyped there has been a shift from using pedigree relationship matrices (A) to genomic ones. As the use of genomic relationship matrices (G) has increased, new methods to build or approximate G have developed. We investigated whether the way variance components are estimated should reflect these changes. We estimated variance components for maternal sow traits by solving with restricted maximum likelihood, with four methods of calculating the inverse of the relationship matrix. These methods included using just the inverse of A ([Formula: see text]), combining [Formula: see text] and the direct inverse of G ([Formula: see text]), including metafounders ([Formula: see text]), or combining [Formula: see text] with an approximated inverse of G using the algorithm for proven and young animals ([Formula: see text]). There was a tendency for higher additive genetic variances and lower permanent environmental variances estimated with [Formula: see text] compared with the three [Formula: see text] methods, which supports that [Formula: see text] is better than [Formula: see text] at separating genetic and permanent environmental components, due to a better definition of the actual relationships between animals. There were limited or no differences in variance estimates between [Formula: see text] , [Formula: see text] , and [Formula: see text]. Importantly, there was limited differences in variance components, repeatability or heritability estimates between methods. Heritabilities ranged between <0.01 to 0.04 for stayability after second cycle, and farrowing rate, between 0.08 and 0.15 for litter weight variation, maximum cycle number, total number born, total number still born, and prolonged interval between weaning and first insemination, and between 0.39 and 0.44 for litter birth weight and gestation length. The limited differences in heritabilities suggest that there would be very limited changes to estimated breeding values or ranking of animals across models using the different sets of variance components. It is suggested that variance estimates continue to be made using [Formula: see text] , however including [Formula: see text] is possibly more appropriate if refining the model, for traits that fit a permanent environmental effect. |
format | Online Article Text |
id | pubmed-7053865 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-70538652020-03-09 Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals Aldridge, Michael N Vandenplas, Jérémie Bergsma, Rob Calus, Mario P L J Anim Sci Animal Genetics and Genomics With an increase in the number of animals genotyped there has been a shift from using pedigree relationship matrices (A) to genomic ones. As the use of genomic relationship matrices (G) has increased, new methods to build or approximate G have developed. We investigated whether the way variance components are estimated should reflect these changes. We estimated variance components for maternal sow traits by solving with restricted maximum likelihood, with four methods of calculating the inverse of the relationship matrix. These methods included using just the inverse of A ([Formula: see text]), combining [Formula: see text] and the direct inverse of G ([Formula: see text]), including metafounders ([Formula: see text]), or combining [Formula: see text] with an approximated inverse of G using the algorithm for proven and young animals ([Formula: see text]). There was a tendency for higher additive genetic variances and lower permanent environmental variances estimated with [Formula: see text] compared with the three [Formula: see text] methods, which supports that [Formula: see text] is better than [Formula: see text] at separating genetic and permanent environmental components, due to a better definition of the actual relationships between animals. There were limited or no differences in variance estimates between [Formula: see text] , [Formula: see text] , and [Formula: see text]. Importantly, there was limited differences in variance components, repeatability or heritability estimates between methods. Heritabilities ranged between <0.01 to 0.04 for stayability after second cycle, and farrowing rate, between 0.08 and 0.15 for litter weight variation, maximum cycle number, total number born, total number still born, and prolonged interval between weaning and first insemination, and between 0.39 and 0.44 for litter birth weight and gestation length. The limited differences in heritabilities suggest that there would be very limited changes to estimated breeding values or ranking of animals across models using the different sets of variance components. It is suggested that variance estimates continue to be made using [Formula: see text] , however including [Formula: see text] is possibly more appropriate if refining the model, for traits that fit a permanent environmental effect. Oxford University Press 2020-01-19 /pmc/articles/PMC7053865/ /pubmed/31955195 http://dx.doi.org/10.1093/jas/skaa019 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Animal Genetics and Genomics Aldridge, Michael N Vandenplas, Jérémie Bergsma, Rob Calus, Mario P L Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
title | Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
title_full | Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
title_fullStr | Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
title_full_unstemmed | Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
title_short | Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
title_sort | variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals |
topic | Animal Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7053865/ https://www.ncbi.nlm.nih.gov/pubmed/31955195 http://dx.doi.org/10.1093/jas/skaa019 |
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