Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle

This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest wit...

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Autores: Brunes, Ludmilla Costa, de Faria, Carina Ubirajara, Magnabosco, Cláudio Ulhoa, Lobo, Raysildo Barbosa, Peripolli, Elisa [UNESP], Aguilar, Ignacio, Baldi, Fernando [UNESP]
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:Brasil
Institución:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:inglés
OAI Identifier:oai:repositorio.unesp.br:11449/246348
Acceso en línea:http://dx.doi.org/10.1007/s13353-022-00734-8
http://hdl.handle.net/11449/246348
Access Level:acceso abierto
Palabra clave:Accuracy
Beef cattle
Bos taurus indicus
Feed efficiency
Genomic selection
Residual feed intake equation
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spelling Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattleAccuracyBeef cattleBos taurus indicusFeed efficiencyGenomic selectionResidual feed intake equationThis study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFItest and RFIpop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFItest and RFIpop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFItest and RFIpop genomic breeding values (GEBV). The RFIpop ANOVA showed a higher significance level (p < 0.0001) than did the RFItest for the fixed effects. The RFIpop displayed higher additive genetic variance estimated than the RFItest, although the RFIpop and RFItest displayed similar heritabilities. Overall, the RFItest showed higher residual correlations with growth, reproductive, and carcass traits, while the RFIpop displayed higher genetic correlations with such traits. The GEBV for the RFItest was slightly biased than GEBV RFIpop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFIpop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI.Animal Performance Center Embrapa CerradosCollege of Veterinary Medicine Federal University of UberlandiaNational Association of Breeders and ResearchersDepartament of Animal Science College of Agricultural and Veterinary Sciences Sao Paulo State University (UNESP)Instituto Nacional de Investigación Agropecuaria (INIA)Departament of Animal Science College of Agricultural and Veterinary Sciences Sao Paulo State University (UNESP)Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)Universidade Federal de Uberlândia (UFU)National Association of Breeders and ResearchersUniversidade Estadual Paulista (UNESP)Instituto Nacional de Investigación Agropecuaria (INIA)2023-07-29T12:38:28Z2023-07-29T12:38:28Z2023-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article159-167http://dx.doi.org/10.1007/s13353-022-00734-8Journal of Applied Genetics, v. 64, n. 1, p. 159-167, 2023.2190-38831234-1983http://hdl.handle.net/11449/24634810.1007/s13353-022-00734-82-s2.0-85142351522Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Applied Geneticsinfo:eu-repo/semantics/openAccessBrunes, Ludmilla Costade Faria, Carina UbirajaraMagnabosco, Cláudio UlhoaLobo, Raysildo BarbosaPeripolli, Elisa [UNESP]Aguilar, IgnacioBaldi, Fernando [UNESP]2025-10-22T07:12:26Zoai:repositorio.unesp.br:11449/246348Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462025-10-22T07:12:26Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
title Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
spellingShingle Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
Brunes, Ludmilla Costa
Accuracy
Beef cattle
Bos taurus indicus
Feed efficiency
Genomic selection
Residual feed intake equation
title_short Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
title_full Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
title_fullStr Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
title_full_unstemmed Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
title_sort Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle
dc.creator.none.fl_str_mv Brunes, Ludmilla Costa
de Faria, Carina Ubirajara
Magnabosco, Cláudio Ulhoa
Lobo, Raysildo Barbosa
Peripolli, Elisa [UNESP]
Aguilar, Ignacio
Baldi, Fernando [UNESP]
author Brunes, Ludmilla Costa
author_facet Brunes, Ludmilla Costa
de Faria, Carina Ubirajara
Magnabosco, Cláudio Ulhoa
Lobo, Raysildo Barbosa
Peripolli, Elisa [UNESP]
Aguilar, Ignacio
Baldi, Fernando [UNESP]
author_role author
author2 de Faria, Carina Ubirajara
Magnabosco, Cláudio Ulhoa
Lobo, Raysildo Barbosa
Peripolli, Elisa [UNESP]
Aguilar, Ignacio
Baldi, Fernando [UNESP]
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
Universidade Federal de Uberlândia (UFU)
National Association of Breeders and Researchers
Universidade Estadual Paulista (UNESP)
Instituto Nacional de Investigación Agropecuaria (INIA)
dc.subject.por.fl_str_mv Accuracy
Beef cattle
Bos taurus indicus
Feed efficiency
Genomic selection
Residual feed intake equation
topic Accuracy
Beef cattle
Bos taurus indicus
Feed efficiency
Genomic selection
Residual feed intake equation
description This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFItest and RFIpop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFItest and RFIpop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFItest and RFIpop genomic breeding values (GEBV). The RFIpop ANOVA showed a higher significance level (p < 0.0001) than did the RFItest for the fixed effects. The RFIpop displayed higher additive genetic variance estimated than the RFItest, although the RFIpop and RFItest displayed similar heritabilities. Overall, the RFItest showed higher residual correlations with growth, reproductive, and carcass traits, while the RFIpop displayed higher genetic correlations with such traits. The GEBV for the RFItest was slightly biased than GEBV RFIpop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFIpop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI.
publishDate 2023
dc.date.none.fl_str_mv 2023-07-29T12:38:28Z
2023-07-29T12:38:28Z
2023-02-01
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 http://dx.doi.org/10.1007/s13353-022-00734-8
Journal of Applied Genetics, v. 64, n. 1, p. 159-167, 2023.
2190-3883
1234-1983
http://hdl.handle.net/11449/246348
10.1007/s13353-022-00734-8
2-s2.0-85142351522
url http://dx.doi.org/10.1007/s13353-022-00734-8
http://hdl.handle.net/11449/246348
identifier_str_mv Journal of Applied Genetics, v. 64, n. 1, p. 159-167, 2023.
2190-3883
1234-1983
10.1007/s13353-022-00734-8
2-s2.0-85142351522
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Applied Genetics
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 159-167
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv repositoriounesp@unesp.br
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score 15,300719

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