Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models

Detalhes bibliográficos
Autor(a) principal: Mota, Rodrigo R.
Data de Publicação: 2016
Outros Autores: Tempelman, Robert J., Lopes, Paulo S., Aguilar, Ignacio, Silva, Fabyano F., Cardoso, Fernando F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: http://dx.doi.org/ 10.1186/s12711-015-0178-5
http://www.locus.ufv.br/handle/123456789/12794
Resumo: The cattle tick is a parasite that adversely affects livestock performance in tropical areas. Although countries such as Australia and Brazil have developed genetic evaluations for tick resistance, these evaluations have not considered genotype by environment (G*E) interactions. Genetic gains could be adversely affected, since breedstock comparisons are environmentally dependent on the presence of G*E interactions, particularly if residual variability is also heterogeneous across environments. The objective of this study was to infer upon the existence of G*E interactions for tick resistance of cattle based on various models with different assumptions of genetic and residual variability. Data were collected by the Delta G Connection Improvement program and included 10,673 records of tick counts on 4363 animals. Twelve models, including three traditional animal models (AM) and nine different hierarchical Bayesian reaction norm models (HBRNM), were investigated. One-step models that jointly estimate environmental covariates and reaction norms and two-step models based on previously estimated environmental covariates were used to infer upon G*E interactions. Model choice was based on the deviance criterion information. The best-fitting model specified heterogeneous residual variances across 10 subclasses that were bounded by every decile of the contemporary group (CG) estimates of tick count effects. One-step models generally had the highest estimated genetic variances. Heritability estimates were normally higher for HBRNM than for AM. One-step models based on heterogeneous residual variances also usually led to higher heritability estimates. Estimates of repeatability varied along the environmental gradient (ranging from 0.18 to 0.45), which implies that the relative importance of additive and permanent environmental effects for tick resistance is influenced by the environment. Estimated genetic correlations decreased as the tick infestation level increased, with negative correlations between extreme environmental levels, i.e., between more favorable (low infestation) and harsh environments (high infestation). HBRNM can be used to describe the presence of G*E interactions for tick resistance in Hereford and Braford beef cattle. The preferred model for the genetic evaluation of this population for tick counts in Brazilian climates was a one-step model that considered heteroscedastic residual variance. Reaction norm models are a powerful tool to identify and quantify G*E interactions and represent a promising alternative for genetic evaluation of tick resistance, since they are expected to lead to greater selection efficiency and genetic progress.
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spelling Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm modelsGenotypeEnvironment interactionResistanceThe cattle tick is a parasite that adversely affects livestock performance in tropical areas. Although countries such as Australia and Brazil have developed genetic evaluations for tick resistance, these evaluations have not considered genotype by environment (G*E) interactions. Genetic gains could be adversely affected, since breedstock comparisons are environmentally dependent on the presence of G*E interactions, particularly if residual variability is also heterogeneous across environments. The objective of this study was to infer upon the existence of G*E interactions for tick resistance of cattle based on various models with different assumptions of genetic and residual variability. Data were collected by the Delta G Connection Improvement program and included 10,673 records of tick counts on 4363 animals. Twelve models, including three traditional animal models (AM) and nine different hierarchical Bayesian reaction norm models (HBRNM), were investigated. One-step models that jointly estimate environmental covariates and reaction norms and two-step models based on previously estimated environmental covariates were used to infer upon G*E interactions. Model choice was based on the deviance criterion information. The best-fitting model specified heterogeneous residual variances across 10 subclasses that were bounded by every decile of the contemporary group (CG) estimates of tick count effects. One-step models generally had the highest estimated genetic variances. Heritability estimates were normally higher for HBRNM than for AM. One-step models based on heterogeneous residual variances also usually led to higher heritability estimates. Estimates of repeatability varied along the environmental gradient (ranging from 0.18 to 0.45), which implies that the relative importance of additive and permanent environmental effects for tick resistance is influenced by the environment. Estimated genetic correlations decreased as the tick infestation level increased, with negative correlations between extreme environmental levels, i.e., between more favorable (low infestation) and harsh environments (high infestation). HBRNM can be used to describe the presence of G*E interactions for tick resistance in Hereford and Braford beef cattle. The preferred model for the genetic evaluation of this population for tick counts in Brazilian climates was a one-step model that considered heteroscedastic residual variance. Reaction norm models are a powerful tool to identify and quantify G*E interactions and represent a promising alternative for genetic evaluation of tick resistance, since they are expected to lead to greater selection efficiency and genetic progress.Genetics Selection Evolution2017-11-07T09:55:58Z2017-11-07T09:55:58Z2016-01-14info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlepdfapplication/pdf1297-9686http://dx.doi.org/ 10.1186/s12711-015-0178-5http://www.locus.ufv.br/handle/123456789/12794eng48:3, January 2016Mota, Rodrigo R.Tempelman, Robert J.Lopes, Paulo S.Aguilar, IgnacioSilva, Fabyano F.Cardoso, Fernando F.info:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFV2024-07-12T06:34:13Zoai:locus.ufv.br:123456789/12794Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452024-07-12T06:34:13LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
title Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
spellingShingle Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
Mota, Rodrigo R.
Genotype
Environment interaction
Resistance
title_short Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
title_full Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
title_fullStr Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
title_full_unstemmed Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
title_sort Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
author Mota, Rodrigo R.
author_facet Mota, Rodrigo R.
Tempelman, Robert J.
Lopes, Paulo S.
Aguilar, Ignacio
Silva, Fabyano F.
Cardoso, Fernando F.
author_role author
author2 Tempelman, Robert J.
Lopes, Paulo S.
Aguilar, Ignacio
Silva, Fabyano F.
Cardoso, Fernando F.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Mota, Rodrigo R.
Tempelman, Robert J.
Lopes, Paulo S.
Aguilar, Ignacio
Silva, Fabyano F.
Cardoso, Fernando F.
dc.subject.por.fl_str_mv Genotype
Environment interaction
Resistance
topic Genotype
Environment interaction
Resistance
description The cattle tick is a parasite that adversely affects livestock performance in tropical areas. Although countries such as Australia and Brazil have developed genetic evaluations for tick resistance, these evaluations have not considered genotype by environment (G*E) interactions. Genetic gains could be adversely affected, since breedstock comparisons are environmentally dependent on the presence of G*E interactions, particularly if residual variability is also heterogeneous across environments. The objective of this study was to infer upon the existence of G*E interactions for tick resistance of cattle based on various models with different assumptions of genetic and residual variability. Data were collected by the Delta G Connection Improvement program and included 10,673 records of tick counts on 4363 animals. Twelve models, including three traditional animal models (AM) and nine different hierarchical Bayesian reaction norm models (HBRNM), were investigated. One-step models that jointly estimate environmental covariates and reaction norms and two-step models based on previously estimated environmental covariates were used to infer upon G*E interactions. Model choice was based on the deviance criterion information. The best-fitting model specified heterogeneous residual variances across 10 subclasses that were bounded by every decile of the contemporary group (CG) estimates of tick count effects. One-step models generally had the highest estimated genetic variances. Heritability estimates were normally higher for HBRNM than for AM. One-step models based on heterogeneous residual variances also usually led to higher heritability estimates. Estimates of repeatability varied along the environmental gradient (ranging from 0.18 to 0.45), which implies that the relative importance of additive and permanent environmental effects for tick resistance is influenced by the environment. Estimated genetic correlations decreased as the tick infestation level increased, with negative correlations between extreme environmental levels, i.e., between more favorable (low infestation) and harsh environments (high infestation). HBRNM can be used to describe the presence of G*E interactions for tick resistance in Hereford and Braford beef cattle. The preferred model for the genetic evaluation of this population for tick counts in Brazilian climates was a one-step model that considered heteroscedastic residual variance. Reaction norm models are a powerful tool to identify and quantify G*E interactions and represent a promising alternative for genetic evaluation of tick resistance, since they are expected to lead to greater selection efficiency and genetic progress.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-14
2017-11-07T09:55:58Z
2017-11-07T09:55:58Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv 1297-9686
http://dx.doi.org/ 10.1186/s12711-015-0178-5
http://www.locus.ufv.br/handle/123456789/12794
identifier_str_mv 1297-9686
url http://dx.doi.org/ 10.1186/s12711-015-0178-5
http://www.locus.ufv.br/handle/123456789/12794
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 48:3, January 2016
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv Genetics Selection Evolution
publisher.none.fl_str_mv Genetics Selection Evolution
dc.source.none.fl_str_mv reponame:LOCUS Repositório Institucional da UFV
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str LOCUS Repositório Institucional da UFV
collection LOCUS Repositório Institucional da UFV
repository.name.fl_str_mv LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv fabiojreis@ufv.br
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