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Investigating pig survival in different production phases using genomic models
Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404463/ https://www.ncbi.nlm.nih.gov/pubmed/34282454 http://dx.doi.org/10.1093/jas/skab217 |
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author | Leite, Natália Galoro Knol, Egbert Frank Garcia, André Luiz Seccatto Lopes, Marcos Soares Zak, Louisa Tsuruta, Shogo Silva, Fabyano Fonseca e Lourenco, Daniela |
author_facet | Leite, Natália Galoro Knol, Egbert Frank Garcia, André Luiz Seccatto Lopes, Marcos Soares Zak, Louisa Tsuruta, Shogo Silva, Fabyano Fonseca e Lourenco, Daniela |
author_sort | Leite, Natália Galoro |
collection | PubMed |
description | Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework. |
format | Online Article Text |
id | pubmed-8404463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84044632021-09-01 Investigating pig survival in different production phases using genomic models Leite, Natália Galoro Knol, Egbert Frank Garcia, André Luiz Seccatto Lopes, Marcos Soares Zak, Louisa Tsuruta, Shogo Silva, Fabyano Fonseca e Lourenco, Daniela J Anim Sci Animal Genetics and Genomics Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework. Oxford University Press 2021-07-19 /pmc/articles/PMC8404463/ /pubmed/34282454 http://dx.doi.org/10.1093/jas/skab217 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://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 Leite, Natália Galoro Knol, Egbert Frank Garcia, André Luiz Seccatto Lopes, Marcos Soares Zak, Louisa Tsuruta, Shogo Silva, Fabyano Fonseca e Lourenco, Daniela Investigating pig survival in different production phases using genomic models |
title | Investigating pig survival in different production phases using genomic models |
title_full | Investigating pig survival in different production phases using genomic models |
title_fullStr | Investigating pig survival in different production phases using genomic models |
title_full_unstemmed | Investigating pig survival in different production phases using genomic models |
title_short | Investigating pig survival in different production phases using genomic models |
title_sort | investigating pig survival in different production phases using genomic models |
topic | Animal Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404463/ https://www.ncbi.nlm.nih.gov/pubmed/34282454 http://dx.doi.org/10.1093/jas/skab217 |
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