Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models

Detalhes bibliográficos
Autor(a) principal: Junqueira, V.S.
Data de Publicação: 2016
Outros Autores: Cardoso, F.F., Oliveira, M.M., Sollero, B.P., Silva, F.F., Lopes, P.S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: http://dx.doi.org/10.1111/jbg.12239
http://www.locus.ufv.br/handle/123456789/14982
Resumo: The selection of genetically superior individuals is conditional upon accurate breeding value predictions which, in turn, are highly depend on how precisely relationship is represented by pedigree. For that purpose, the numerator relationship matrix is essential as a priori information in mixed model equations. The presence of pedigree errors and/or the lack of relationship information affect the genetic gain because it reduces the correlation between the true and estimated breeding values. Thus, this study aimed to evaluate the effects of correcting the pedigree relationships using single-nucleotide polymorphism (SNP) markers on genetic evaluation accuracies for resistance of beef cattle to ticks. Tick count data from Hereford and Braford cattle breeds were used as phenotype. Genotyping was carried out using a high-density panel (BovineHD - Illumina â bead chip with 777 962 SNPs) for sires and the Illumina BovineSNP50 panel (54 609 SNPs) for their progenies. The relationship between the parents and progenies of genotyped animals was evaluated, and mismatches were based on the Mendelian conflicts counts. Variance components and genetic parameters estimates were obtained using a Bayesian approach via Gibbs sampling, and the breeding values were predicted assuming a repeatability model. A total of 460 corrections in relationship definitions were made (Table 1) corresponding to 1018 (9.5%) tick count records. Among these changes, 97.17% (447) were related to the sire’s information, and 2.8% (13) were related to the dam’s information. We observed 27.2% (236/868) of Mendelian conflicts for sire–progeny genotyped pairs and 14.3% (13/91) for dam–progeny genotyped pairs. We performed 2174 new definitions of half-siblings according to the correlation coefficient between the coancestry and molecular coancestry matrices. It was observed that higher-quality genetic relationships did not result in significant differences of variance components estimates; however, they resulted in more accurate breeding values predictions. Using SNPs to assess conflicts between parents and progenies increases certainty in relationships and consequently the accuracy of breeding value predictions of candidate animals for selection. Thus, higher genetic gains are expected when compared to the traditional non-corrected relationship matrix.
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spelling Junqueira, V.S.Cardoso, F.F.Oliveira, M.M.Sollero, B.P.Silva, F.F.Lopes, P.S.2017-12-14T09:24:06Z2017-12-14T09:24:06Z2016-09-221439-0388http://dx.doi.org/10.1111/jbg.12239http://www.locus.ufv.br/handle/123456789/14982The selection of genetically superior individuals is conditional upon accurate breeding value predictions which, in turn, are highly depend on how precisely relationship is represented by pedigree. For that purpose, the numerator relationship matrix is essential as a priori information in mixed model equations. The presence of pedigree errors and/or the lack of relationship information affect the genetic gain because it reduces the correlation between the true and estimated breeding values. Thus, this study aimed to evaluate the effects of correcting the pedigree relationships using single-nucleotide polymorphism (SNP) markers on genetic evaluation accuracies for resistance of beef cattle to ticks. Tick count data from Hereford and Braford cattle breeds were used as phenotype. Genotyping was carried out using a high-density panel (BovineHD - Illumina â bead chip with 777 962 SNPs) for sires and the Illumina BovineSNP50 panel (54 609 SNPs) for their progenies. The relationship between the parents and progenies of genotyped animals was evaluated, and mismatches were based on the Mendelian conflicts counts. Variance components and genetic parameters estimates were obtained using a Bayesian approach via Gibbs sampling, and the breeding values were predicted assuming a repeatability model. A total of 460 corrections in relationship definitions were made (Table 1) corresponding to 1018 (9.5%) tick count records. Among these changes, 97.17% (447) were related to the sire’s information, and 2.8% (13) were related to the dam’s information. We observed 27.2% (236/868) of Mendelian conflicts for sire–progeny genotyped pairs and 14.3% (13/91) for dam–progeny genotyped pairs. We performed 2174 new definitions of half-siblings according to the correlation coefficient between the coancestry and molecular coancestry matrices. It was observed that higher-quality genetic relationships did not result in significant differences of variance components estimates; however, they resulted in more accurate breeding values predictions. Using SNPs to assess conflicts between parents and progenies increases certainty in relationships and consequently the accuracy of breeding value predictions of candidate animals for selection. Thus, higher genetic gains are expected when compared to the traditional non-corrected relationship matrix.engJournal of Animal Breeding and Genetics134, p. 14–26, September 2016AccuracyBeef cattleNumerator relationship matrixSNPsUse of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based modelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALJunqueira_et_al-2017-Journal_of_Animal_Breeding_and_Genetics.pdfJunqueira_et_al-2017-Journal_of_Animal_Breeding_and_Genetics.pdftexto completoapplication/pdf305915https://locus.ufv.br//bitstream/123456789/14982/1/Junqueira_et_al-2017-Journal_of_Animal_Breeding_and_Genetics.pdfda4ce5067e9f8136d7da7c8b58d095c2MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/14982/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILJunqueira_et_al-2017-Journal_of_Animal_Breeding_and_Genetics.pdf.jpgJunqueira_et_al-2017-Journal_of_Animal_Breeding_and_Genetics.pdf.jpgIM Thumbnailimage/jpeg5226https://locus.ufv.br//bitstream/123456789/14982/3/Junqueira_et_al-2017-Journal_of_Animal_Breeding_and_Genetics.pdf.jpg75aaeb32a41d05cf7ccbf3a5fb6810ebMD53123456789/149822017-12-14 22:01:40.302oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452017-12-15T01:01:40LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
title Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
spellingShingle Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
Junqueira, V.S.
Accuracy
Beef cattle
Numerator relationship matrix
SNPs
title_short Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
title_full Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
title_fullStr Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
title_full_unstemmed Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
title_sort Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models
author Junqueira, V.S.
author_facet Junqueira, V.S.
Cardoso, F.F.
Oliveira, M.M.
Sollero, B.P.
Silva, F.F.
Lopes, P.S.
author_role author
author2 Cardoso, F.F.
Oliveira, M.M.
Sollero, B.P.
Silva, F.F.
Lopes, P.S.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Junqueira, V.S.
Cardoso, F.F.
Oliveira, M.M.
Sollero, B.P.
Silva, F.F.
Lopes, P.S.
dc.subject.pt-BR.fl_str_mv Accuracy
Beef cattle
Numerator relationship matrix
SNPs
topic Accuracy
Beef cattle
Numerator relationship matrix
SNPs
description The selection of genetically superior individuals is conditional upon accurate breeding value predictions which, in turn, are highly depend on how precisely relationship is represented by pedigree. For that purpose, the numerator relationship matrix is essential as a priori information in mixed model equations. The presence of pedigree errors and/or the lack of relationship information affect the genetic gain because it reduces the correlation between the true and estimated breeding values. Thus, this study aimed to evaluate the effects of correcting the pedigree relationships using single-nucleotide polymorphism (SNP) markers on genetic evaluation accuracies for resistance of beef cattle to ticks. Tick count data from Hereford and Braford cattle breeds were used as phenotype. Genotyping was carried out using a high-density panel (BovineHD - Illumina â bead chip with 777 962 SNPs) for sires and the Illumina BovineSNP50 panel (54 609 SNPs) for their progenies. The relationship between the parents and progenies of genotyped animals was evaluated, and mismatches were based on the Mendelian conflicts counts. Variance components and genetic parameters estimates were obtained using a Bayesian approach via Gibbs sampling, and the breeding values were predicted assuming a repeatability model. A total of 460 corrections in relationship definitions were made (Table 1) corresponding to 1018 (9.5%) tick count records. Among these changes, 97.17% (447) were related to the sire’s information, and 2.8% (13) were related to the dam’s information. We observed 27.2% (236/868) of Mendelian conflicts for sire–progeny genotyped pairs and 14.3% (13/91) for dam–progeny genotyped pairs. We performed 2174 new definitions of half-siblings according to the correlation coefficient between the coancestry and molecular coancestry matrices. It was observed that higher-quality genetic relationships did not result in significant differences of variance components estimates; however, they resulted in more accurate breeding values predictions. Using SNPs to assess conflicts between parents and progenies increases certainty in relationships and consequently the accuracy of breeding value predictions of candidate animals for selection. Thus, higher genetic gains are expected when compared to the traditional non-corrected relationship matrix.
publishDate 2016
dc.date.issued.fl_str_mv 2016-09-22
dc.date.accessioned.fl_str_mv 2017-12-14T09:24:06Z
dc.date.available.fl_str_mv 2017-12-14T09:24:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1111/jbg.12239
http://www.locus.ufv.br/handle/123456789/14982
dc.identifier.issn.none.fl_str_mv 1439-0388
identifier_str_mv 1439-0388
url http://dx.doi.org/10.1111/jbg.12239
http://www.locus.ufv.br/handle/123456789/14982
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.pt-BR.fl_str_mv 134, p. 14–26, September 2016
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dc.publisher.none.fl_str_mv Journal of Animal Breeding and Genetics
publisher.none.fl_str_mv Journal of Animal Breeding and Genetics
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