Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Zootecnia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982021000100406 |
Resumo: | ABSTRACT The aim of this study was to evaluate genomic information inclusion in genetic parameter estimation of standardized body weight at birth and at 240, 365, and 450 days of age, and visual scores for body structure, precocity, and body muscularity, measured as yearlings in Nelore cattle. We compared genetic parameters, (co)variance components (estimated from Bayesian inference and Gibbs sampling), breeding value accuracies, genetic trends, and principal component analysis (PCA) obtained through traditional GBLUP and ssGBLUP methods. For all traits analyzed, part of the phenotypic variation was explained by the additive genetic effect, thus indicating the capacity of traits to respond to the selection process. Estimates of genetic correlation, in both methodologies, between body weights and visual scores were, in general, high and positive, showing that the selection for visual scores can lead to heavier animals. Genetic trends showed genetic progress, both when estimated breeding values and genomic estimated breeding values were used. The PCA, genetic trends, and accuracy estimates on breeding values showed that inclusion of single nucleotide polymorphism information contributed towards slightly better estimates of the genetic variability of evaluated traits. Genomic information did not bring greater gains in genetic estimates, due to redundancy of kinship information from the pedigree, which already had complete animal kinship data. |
id |
SBZ-1_327811509c288562ce30ae6997b3cdfe |
---|---|
oai_identifier_str |
oai:scielo:S1516-35982021000100406 |
network_acronym_str |
SBZ-1 |
network_name_str |
Revista Brasileira de Zootecnia (Online) |
repository_id_str |
|
spelling |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattlebeef cattlegenetic parametersgenetic trendsgrowth traitsselectionABSTRACT The aim of this study was to evaluate genomic information inclusion in genetic parameter estimation of standardized body weight at birth and at 240, 365, and 450 days of age, and visual scores for body structure, precocity, and body muscularity, measured as yearlings in Nelore cattle. We compared genetic parameters, (co)variance components (estimated from Bayesian inference and Gibbs sampling), breeding value accuracies, genetic trends, and principal component analysis (PCA) obtained through traditional GBLUP and ssGBLUP methods. For all traits analyzed, part of the phenotypic variation was explained by the additive genetic effect, thus indicating the capacity of traits to respond to the selection process. Estimates of genetic correlation, in both methodologies, between body weights and visual scores were, in general, high and positive, showing that the selection for visual scores can lead to heavier animals. Genetic trends showed genetic progress, both when estimated breeding values and genomic estimated breeding values were used. The PCA, genetic trends, and accuracy estimates on breeding values showed that inclusion of single nucleotide polymorphism information contributed towards slightly better estimates of the genetic variability of evaluated traits. Genomic information did not bring greater gains in genetic estimates, due to redundancy of kinship information from the pedigree, which already had complete animal kinship data.Sociedade Brasileira de Zootecnia2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982021000100406Revista Brasileira de Zootecnia v.50 2021reponame:Revista Brasileira de Zootecnia (Online)instname:Sociedade Brasileira de Zootecnia (SBZ)instacron:SBZ10.37496/rbz5020200077info:eu-repo/semantics/openAccessWatanabe,Rafael NakamuraNascimento,Guilherme Batista doBernardes,Priscila ArrigucciCosta,Rebeka Magalhães daLôbo,Raysildo BarbosaBaldi,FernandoMunari,Danísio Pradoeng2021-09-02T00:00:00Zoai:scielo:S1516-35982021000100406Revistahttps://www.rbz.org.br/pt-br/https://old.scielo.br/oai/scielo-oai.php||bz@sbz.org.br|| secretariarbz@sbz.org.br1806-92901516-3598opendoar:2021-09-02T00:00Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ)false |
dc.title.none.fl_str_mv |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
title |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
spellingShingle |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle Watanabe,Rafael Nakamura beef cattle genetic parameters genetic trends growth traits selection |
title_short |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
title_full |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
title_fullStr |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
title_full_unstemmed |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
title_sort |
Inclusion of genomic information in estimation of genetic parameters for body weights and visual scores in Nelore cattle |
author |
Watanabe,Rafael Nakamura |
author_facet |
Watanabe,Rafael Nakamura Nascimento,Guilherme Batista do Bernardes,Priscila Arrigucci Costa,Rebeka Magalhães da Lôbo,Raysildo Barbosa Baldi,Fernando Munari,Danísio Prado |
author_role |
author |
author2 |
Nascimento,Guilherme Batista do Bernardes,Priscila Arrigucci Costa,Rebeka Magalhães da Lôbo,Raysildo Barbosa Baldi,Fernando Munari,Danísio Prado |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Watanabe,Rafael Nakamura Nascimento,Guilherme Batista do Bernardes,Priscila Arrigucci Costa,Rebeka Magalhães da Lôbo,Raysildo Barbosa Baldi,Fernando Munari,Danísio Prado |
dc.subject.por.fl_str_mv |
beef cattle genetic parameters genetic trends growth traits selection |
topic |
beef cattle genetic parameters genetic trends growth traits selection |
description |
ABSTRACT The aim of this study was to evaluate genomic information inclusion in genetic parameter estimation of standardized body weight at birth and at 240, 365, and 450 days of age, and visual scores for body structure, precocity, and body muscularity, measured as yearlings in Nelore cattle. We compared genetic parameters, (co)variance components (estimated from Bayesian inference and Gibbs sampling), breeding value accuracies, genetic trends, and principal component analysis (PCA) obtained through traditional GBLUP and ssGBLUP methods. For all traits analyzed, part of the phenotypic variation was explained by the additive genetic effect, thus indicating the capacity of traits to respond to the selection process. Estimates of genetic correlation, in both methodologies, between body weights and visual scores were, in general, high and positive, showing that the selection for visual scores can lead to heavier animals. Genetic trends showed genetic progress, both when estimated breeding values and genomic estimated breeding values were used. The PCA, genetic trends, and accuracy estimates on breeding values showed that inclusion of single nucleotide polymorphism information contributed towards slightly better estimates of the genetic variability of evaluated traits. Genomic information did not bring greater gains in genetic estimates, due to redundancy of kinship information from the pedigree, which already had complete animal kinship data. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982021000100406 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982021000100406 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.37496/rbz5020200077 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Zootecnia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Zootecnia |
dc.source.none.fl_str_mv |
Revista Brasileira de Zootecnia v.50 2021 reponame:Revista Brasileira de Zootecnia (Online) instname:Sociedade Brasileira de Zootecnia (SBZ) instacron:SBZ |
instname_str |
Sociedade Brasileira de Zootecnia (SBZ) |
instacron_str |
SBZ |
institution |
SBZ |
reponame_str |
Revista Brasileira de Zootecnia (Online) |
collection |
Revista Brasileira de Zootecnia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ) |
repository.mail.fl_str_mv |
||bz@sbz.org.br|| secretariarbz@sbz.org.br |
_version_ |
1750318154117021696 |