Cargando…
The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data
BACKGROUND: Physical removal of individuals from groups causes reductions in group sizes and changes in group composition, which may affect the predictive ability of estimates of indirect genetic effects of animals on phenotypes of group mates. We hypothesized that including indirect genetic effects...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011392/ https://www.ncbi.nlm.nih.gov/pubmed/32041518 http://dx.doi.org/10.1186/s12711-020-0527-x |
_version_ | 1783496060806627328 |
---|---|
author | Ask, Birgitte Christensen, Ole F. Heidaritabar, Marzieh Madsen, Per Nielsen, Hanne M. |
author_facet | Ask, Birgitte Christensen, Ole F. Heidaritabar, Marzieh Madsen, Per Nielsen, Hanne M. |
author_sort | Ask, Birgitte |
collection | PubMed |
description | BACKGROUND: Physical removal of individuals from groups causes reductions in group sizes and changes in group composition, which may affect the predictive ability of estimates of indirect genetic effects of animals on phenotypes of group mates. We hypothesized that including indirect genetic effects of culled animals and of animals without phenotypes in the analysis affects estimates of genetic parameters, improves predictive ability, and reduces bias of predicted breeding values. We tested this by applying different editing procedures, i.e. omission of individuals or groups from the data, and genetic models, i.e. a classical and an indirect genetic model (IGM) without or with weighting of indirect genetic effects based on the relative proportion of time spent in the pen or space allowance. Data consisted of average daily gain for 123,567 pigs in 11,111 groups, from which 3% of individuals in 25% of groups were prematurely removed from the group. RESULTS: The estimate of total heritability was higher (0.29 to 0.34) than that of direct heritability (0.23 to 0.25) regardless of the editing procedures and IGM used. Omission of individuals or groups from the data reduced the predictive ability of estimates of indirect genetic effects by 8 to 46%, and the predictive ability of estimates of the combined direct and indirect genetic effects by up to 4%. Omission of full groups introduced bias in predicted breeding values. Weighting of indirect genetic effects reduced the predictive ability of their estimates by at least 19% and of the estimates of the combined direct and indirect genetic effects by 1%. CONCLUSIONS: We identified significant indirect genetic effects for growth in pigs. Culled animals should neither be removed from the data nor accounted for by weighting their indirect genetic effects in the model based on the relative proportion of time spent in the pen or space allowance, because it will reduce predictive ability and increase bias of predicted breeding values. Information on culled animals is important for prediction of indirect genetic effects and must be accounted for in IGM analyses by including fixed regressions based on relative time spent within the pen or relative space allowance. |
format | Online Article Text |
id | pubmed-7011392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70113922020-02-14 The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data Ask, Birgitte Christensen, Ole F. Heidaritabar, Marzieh Madsen, Per Nielsen, Hanne M. Genet Sel Evol Research Article BACKGROUND: Physical removal of individuals from groups causes reductions in group sizes and changes in group composition, which may affect the predictive ability of estimates of indirect genetic effects of animals on phenotypes of group mates. We hypothesized that including indirect genetic effects of culled animals and of animals without phenotypes in the analysis affects estimates of genetic parameters, improves predictive ability, and reduces bias of predicted breeding values. We tested this by applying different editing procedures, i.e. omission of individuals or groups from the data, and genetic models, i.e. a classical and an indirect genetic model (IGM) without or with weighting of indirect genetic effects based on the relative proportion of time spent in the pen or space allowance. Data consisted of average daily gain for 123,567 pigs in 11,111 groups, from which 3% of individuals in 25% of groups were prematurely removed from the group. RESULTS: The estimate of total heritability was higher (0.29 to 0.34) than that of direct heritability (0.23 to 0.25) regardless of the editing procedures and IGM used. Omission of individuals or groups from the data reduced the predictive ability of estimates of indirect genetic effects by 8 to 46%, and the predictive ability of estimates of the combined direct and indirect genetic effects by up to 4%. Omission of full groups introduced bias in predicted breeding values. Weighting of indirect genetic effects reduced the predictive ability of their estimates by at least 19% and of the estimates of the combined direct and indirect genetic effects by 1%. CONCLUSIONS: We identified significant indirect genetic effects for growth in pigs. Culled animals should neither be removed from the data nor accounted for by weighting their indirect genetic effects in the model based on the relative proportion of time spent in the pen or space allowance, because it will reduce predictive ability and increase bias of predicted breeding values. Information on culled animals is important for prediction of indirect genetic effects and must be accounted for in IGM analyses by including fixed regressions based on relative time spent within the pen or relative space allowance. BioMed Central 2020-02-10 /pmc/articles/PMC7011392/ /pubmed/32041518 http://dx.doi.org/10.1186/s12711-020-0527-x Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Ask, Birgitte Christensen, Ole F. Heidaritabar, Marzieh Madsen, Per Nielsen, Hanne M. The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
title | The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
title_full | The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
title_fullStr | The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
title_full_unstemmed | The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
title_short | The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
title_sort | predictive ability of indirect genetic models is reduced when culled animals are omitted from the data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011392/ https://www.ncbi.nlm.nih.gov/pubmed/32041518 http://dx.doi.org/10.1186/s12711-020-0527-x |
work_keys_str_mv | AT askbirgitte thepredictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT christensenolef thepredictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT heidaritabarmarzieh thepredictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT madsenper thepredictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT nielsenhannem thepredictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT askbirgitte predictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT christensenolef predictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT heidaritabarmarzieh predictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT madsenper predictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata AT nielsenhannem predictiveabilityofindirectgeneticmodelsisreducedwhenculledanimalsareomittedfromthedata |