Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.

Detalhes bibliográficos
Autor(a) principal: BUZANSKAS, M. E.
Data de Publicação: 2017
Outros Autores: VENTURA, R. V., CHUD, T. C. S., BERNARDES, P. A., SANTOS, D. J. de A., REGITANO, L. C. de A., ALENCAR, M. M. de, MUDADU, M. de A., ZANELLA, R., SILVA, M. V. G. B., LI, C., SCHENKE, F. S., MUNARI, D. P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1070093
https://doi.org/10.1371/journal.pone.0171660
Resumo: The aim of this study was to evaluate the level of introgression of breeds in the Canchim (CA: 62.5% Charolais?37.5% Zebu) and MA genetic group (MA: 65.6% Charolais?34.4% Zebu) cattle using genomic information on Charolais (CH), Nelore (NE), and Indubrasil (IB) breeds. The number of animals used was 395 (CA and MA), 763 (NE), 338 (CH), and 37 (IB). The Bovine50SNP BeadChip from Illumina panel was used to estimate the levels of introgression of breeds considering the Maximum likelihood, Bayesian, and Single Regression method. After genotype quality control, 32,308 SNPs were considered in the analysis. Furthermore, three thresholds to prune out SNPs in linkage disequilibrium higher than 0.10, 0.05, and 0.01 were considered, resulting in 15,286, 7,652, and 1,582 SNPs, respectively. For k = 2, the proportion of taurine and indicine varied from the expected proportion based on pedigree for all methods studied. For k = 3, the Regression method was able to differentiate the animals in three main clusters assigned to each purebred breed, showing more reasonable according to its biological viewpoint. Analyzing the data considering k = 2 seems to be more appropriate for Canchim-MA animals due to its biological interpretation. The usage of 32,308 SNPs in the analyses resulted in similar findings between the estimated and expected breed proportions. Using the Regression approach, a contribution of Indubrasil was observed in Canchim-MA when k = 3 was considered. Genetic parameter estimation could account for this breed composition information as a source of variation in order to improve the accuracy of genetic models. Our findings may help assemble appropriate reference populations for genomic prediction for Canchim-MA in order to improve prediction accuracy. Using the information on the level of introgression in each individual could also be useful in breeding or crossing design to improve individual heterosis in crossbred cattle.
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spelling Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.Canchim cattlebeef cattlepolymorphismThe aim of this study was to evaluate the level of introgression of breeds in the Canchim (CA: 62.5% Charolais?37.5% Zebu) and MA genetic group (MA: 65.6% Charolais?34.4% Zebu) cattle using genomic information on Charolais (CH), Nelore (NE), and Indubrasil (IB) breeds. The number of animals used was 395 (CA and MA), 763 (NE), 338 (CH), and 37 (IB). The Bovine50SNP BeadChip from Illumina panel was used to estimate the levels of introgression of breeds considering the Maximum likelihood, Bayesian, and Single Regression method. After genotype quality control, 32,308 SNPs were considered in the analysis. Furthermore, three thresholds to prune out SNPs in linkage disequilibrium higher than 0.10, 0.05, and 0.01 were considered, resulting in 15,286, 7,652, and 1,582 SNPs, respectively. For k = 2, the proportion of taurine and indicine varied from the expected proportion based on pedigree for all methods studied. For k = 3, the Regression method was able to differentiate the animals in three main clusters assigned to each purebred breed, showing more reasonable according to its biological viewpoint. Analyzing the data considering k = 2 seems to be more appropriate for Canchim-MA animals due to its biological interpretation. The usage of 32,308 SNPs in the analyses resulted in similar findings between the estimated and expected breed proportions. Using the Regression approach, a contribution of Indubrasil was observed in Canchim-MA when k = 3 was considered. Genetic parameter estimation could account for this breed composition information as a source of variation in order to improve the accuracy of genetic models. Our findings may help assemble appropriate reference populations for genomic prediction for Canchim-MA in order to improve prediction accuracy. Using the information on the level of introgression in each individual could also be useful in breeding or crossing design to improve individual heterosis in crossbred cattle.Marcos Eli Buzanskas, Unesp; Ricardo Vieira Ventura, USP; Tatiane Cristina Seleguim Chud, Unesp; Priscila Arrigucci Bernardes, Unesp; Daniel Jordan de Abreu Santos, Unesp; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE; MAURICIO MELLO DE ALENCAR, CPPSE; MAURICIO DE ALVARENGA MUDADU, CNPTIA; Ricardo Zanella, UPF; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; Changxi Li, University of Alberta; Flavio Schramm Schenke, University of Guelph; Danísio Prado Munari, Unesp.BUZANSKAS, M. E.VENTURA, R. V.CHUD, T. C. S.BERNARDES, P. A.SANTOS, D. J. de A.REGITANO, L. C. de A.ALENCAR, M. M. deMUDADU, M. de A.ZANELLA, R.SILVA, M. V. G. B.LI, C.SCHENKE, F. S.MUNARI, D. P.2019-05-22T01:07:52Z2019-05-22T01:07:52Z2017-05-2620172019-05-22T01:07:52Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlePlos one, v. 12, p. 1-16, 2017.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1070093https://doi.org/10.1371/journal.pone.0171660enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2019-05-22T01:08:00Zoai:www.alice.cnptia.embrapa.br:doc/1070093Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542019-05-22T01:08falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542019-05-22T01:08Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
title Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
spellingShingle Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
BUZANSKAS, M. E.
Canchim cattle
beef cattle
polymorphism
title_short Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
title_full Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
title_fullStr Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
title_full_unstemmed Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
title_sort Study on the introgression of beef breeds in canchim cattle using single nucleotide polymorphism markers.
author BUZANSKAS, M. E.
author_facet BUZANSKAS, M. E.
VENTURA, R. V.
CHUD, T. C. S.
BERNARDES, P. A.
SANTOS, D. J. de A.
REGITANO, L. C. de A.
ALENCAR, M. M. de
MUDADU, M. de A.
ZANELLA, R.
SILVA, M. V. G. B.
LI, C.
SCHENKE, F. S.
MUNARI, D. P.
author_role author
author2 VENTURA, R. V.
CHUD, T. C. S.
BERNARDES, P. A.
SANTOS, D. J. de A.
REGITANO, L. C. de A.
ALENCAR, M. M. de
MUDADU, M. de A.
ZANELLA, R.
SILVA, M. V. G. B.
LI, C.
SCHENKE, F. S.
MUNARI, D. P.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Marcos Eli Buzanskas, Unesp; Ricardo Vieira Ventura, USP; Tatiane Cristina Seleguim Chud, Unesp; Priscila Arrigucci Bernardes, Unesp; Daniel Jordan de Abreu Santos, Unesp; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE; MAURICIO MELLO DE ALENCAR, CPPSE; MAURICIO DE ALVARENGA MUDADU, CNPTIA; Ricardo Zanella, UPF; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; Changxi Li, University of Alberta; Flavio Schramm Schenke, University of Guelph; Danísio Prado Munari, Unesp.
dc.contributor.author.fl_str_mv BUZANSKAS, M. E.
VENTURA, R. V.
CHUD, T. C. S.
BERNARDES, P. A.
SANTOS, D. J. de A.
REGITANO, L. C. de A.
ALENCAR, M. M. de
MUDADU, M. de A.
ZANELLA, R.
SILVA, M. V. G. B.
LI, C.
SCHENKE, F. S.
MUNARI, D. P.
dc.subject.por.fl_str_mv Canchim cattle
beef cattle
polymorphism
topic Canchim cattle
beef cattle
polymorphism
description The aim of this study was to evaluate the level of introgression of breeds in the Canchim (CA: 62.5% Charolais?37.5% Zebu) and MA genetic group (MA: 65.6% Charolais?34.4% Zebu) cattle using genomic information on Charolais (CH), Nelore (NE), and Indubrasil (IB) breeds. The number of animals used was 395 (CA and MA), 763 (NE), 338 (CH), and 37 (IB). The Bovine50SNP BeadChip from Illumina panel was used to estimate the levels of introgression of breeds considering the Maximum likelihood, Bayesian, and Single Regression method. After genotype quality control, 32,308 SNPs were considered in the analysis. Furthermore, three thresholds to prune out SNPs in linkage disequilibrium higher than 0.10, 0.05, and 0.01 were considered, resulting in 15,286, 7,652, and 1,582 SNPs, respectively. For k = 2, the proportion of taurine and indicine varied from the expected proportion based on pedigree for all methods studied. For k = 3, the Regression method was able to differentiate the animals in three main clusters assigned to each purebred breed, showing more reasonable according to its biological viewpoint. Analyzing the data considering k = 2 seems to be more appropriate for Canchim-MA animals due to its biological interpretation. The usage of 32,308 SNPs in the analyses resulted in similar findings between the estimated and expected breed proportions. Using the Regression approach, a contribution of Indubrasil was observed in Canchim-MA when k = 3 was considered. Genetic parameter estimation could account for this breed composition information as a source of variation in order to improve the accuracy of genetic models. Our findings may help assemble appropriate reference populations for genomic prediction for Canchim-MA in order to improve prediction accuracy. Using the information on the level of introgression in each individual could also be useful in breeding or crossing design to improve individual heterosis in crossbred cattle.
publishDate 2017
dc.date.none.fl_str_mv 2017-05-26
2017
2019-05-22T01:07:52Z
2019-05-22T01:07:52Z
2019-05-22T01:07:52Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Plos one, v. 12, p. 1-16, 2017.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1070093
https://doi.org/10.1371/journal.pone.0171660
identifier_str_mv Plos one, v. 12, p. 1-16, 2017.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1070093
https://doi.org/10.1371/journal.pone.0171660
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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