Evidence map›Paper›PMID 33397289›Full record

ArticleGenetics, selection, evolution : GSE2021

Statistical model and testing designs to increase response to selection with constrained inbreeding in genomic breeding programs for pigs affected by social genetic effects.

Thinh Tuan Chu, Mark Henryon, Just Jensen, Birgitte Ask, Ole Fredslund Christensen

Abstract read
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Article in Genetics, selection, evolution : GSE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Thinh Tuan ChuCenter for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark. Chu.Thinh@qgg.au.dk.ORCID http://orcid.org/0000-0002-7226-3454
Mark HenryonDanish Pig Research Centre, SEGES, Axeltorv 3, 1609, Copenhagen V, Denmark.
Just JensenCenter for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
Birgitte AskDanish Pig Research Centre, SEGES, Axeltorv 3, 1609, Copenhagen V, Denmark.
Ole Fredslund ChristensenCenter for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.

Funding

GUDP (Green Development and Demonstration Programme), Ministry of Environment and Food of Denmark 34009-14-0849
6 · The paper itself

Abstract

backgroundSocial genetic effects (SGE) are the effects of the genotype of one animal on the phenotypes of other animals within a social group. Because SGE contribute to variation in economically important traits for pigs, the inclusion of SGE in statistical models could increase responses to selection (RS) in breeding programs. In such models, increasing the relatedness of members within groups further increases RS when using pedigree-based relationships; however, this has not been demonstrated with genomic-based relationships or with a constraint on inbreeding. In this study, we compared the use of statistical models with and without SGE and compared groups composed at random versus groups composed of families in genomic selection breeding programs with a constraint on the rate of inbreeding.

resultsWhen SGE were of a moderate magnitude, inclusion of SGE in the statistical model substantially increased RS when SGE were considered for selection. However, when SGE were included in the model but not considered for selection, the increase in RS and in accuracy of predicted direct genetic effects (DGE) depended on the correlation between SGE and DGE. When SGE were of a low magnitude, inclusion of SGE in the model did not increase RS, probably because of the poor separation of effects and convergence issues of the algorithms. Compared to a random group composition design, groups composed of families led to higher RS. The difference in RS between the two group compositions was slightly reduced when using genomic-based compared to pedigree-based relationships.

conclusionsThe use of a statistical model that includes SGE can substantially improve response to selection at a fixed rate of inbreeding, because it allows the heritable variation from SGE to be accounted for and capitalized on. Compared to having random groups, family groups result in greater response to selection in the presence of SGE but the advantage of using family groups decreases when genomic-based relationships are used.

Indexed as

Gene-Environment InteractionModels, StatisticalSelective BreedingSocial EnvironmentAnimalsInbreedingModels, GeneticSelection, GeneticSwine

Identifiers

PMID33397289
PMCPMC7784391

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.