Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/41906 |
Resumo: | Background: meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal’s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality. Results: the set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism. Conclusions: these results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. |
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Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approachBovineLipid metabolismMachine learningSingle nucleotide polymorphism (SNP)Subcutaneous fatTropical composite cattleBackground: meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal’s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality. Results: the set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism. Conclusions: these results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle.BioMed Central (BMC)2020-07-13T13:09:02Z2020-07-13T13:09:02Z2013-06-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfMOKRY, F. B. et al. Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach. BMC Genetics, [S.l.], v. 14, p. 1-11, June 2013. DOI: 10.1186/1471-2156-14-47.http://repositorio.ufla.br/jspui/handle/1/41906BMC Geneticsreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessMokry, Fabiana BarichelloHiga, Roberto HiroshiMudadu, Maurício de AlvarengaLima, Andressa Oliveira deMeirelles, Sarah Laguna ConceiçãoSilva, Marcos Vinicius Gualberto Barbosa daCardoso, Fernando FloresOliveira, Maurício Morgado deUrbinati, IsmaelNiciura, Simone Cristina MéoTullio, Rymer RamizAlencar, Maurício Mello deRegitano, Luciana Correia de Almeidaeng2020-07-13T13:09:02Zoai:localhost:1/41906Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-07-13T13:09:02Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
title |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
spellingShingle |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach Mokry, Fabiana Barichello Bovine Lipid metabolism Machine learning Single nucleotide polymorphism (SNP) Subcutaneous fat Tropical composite cattle |
title_short |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
title_full |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
title_fullStr |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
title_full_unstemmed |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
title_sort |
Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach |
author |
Mokry, Fabiana Barichello |
author_facet |
Mokry, Fabiana Barichello Higa, Roberto Hiroshi Mudadu, Maurício de Alvarenga Lima, Andressa Oliveira de Meirelles, Sarah Laguna Conceição Silva, Marcos Vinicius Gualberto Barbosa da Cardoso, Fernando Flores Oliveira, Maurício Morgado de Urbinati, Ismael Niciura, Simone Cristina Méo Tullio, Rymer Ramiz Alencar, Maurício Mello de Regitano, Luciana Correia de Almeida |
author_role |
author |
author2 |
Higa, Roberto Hiroshi Mudadu, Maurício de Alvarenga Lima, Andressa Oliveira de Meirelles, Sarah Laguna Conceição Silva, Marcos Vinicius Gualberto Barbosa da Cardoso, Fernando Flores Oliveira, Maurício Morgado de Urbinati, Ismael Niciura, Simone Cristina Méo Tullio, Rymer Ramiz Alencar, Maurício Mello de Regitano, Luciana Correia de Almeida |
author2_role |
author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Mokry, Fabiana Barichello Higa, Roberto Hiroshi Mudadu, Maurício de Alvarenga Lima, Andressa Oliveira de Meirelles, Sarah Laguna Conceição Silva, Marcos Vinicius Gualberto Barbosa da Cardoso, Fernando Flores Oliveira, Maurício Morgado de Urbinati, Ismael Niciura, Simone Cristina Méo Tullio, Rymer Ramiz Alencar, Maurício Mello de Regitano, Luciana Correia de Almeida |
dc.subject.por.fl_str_mv |
Bovine Lipid metabolism Machine learning Single nucleotide polymorphism (SNP) Subcutaneous fat Tropical composite cattle |
topic |
Bovine Lipid metabolism Machine learning Single nucleotide polymorphism (SNP) Subcutaneous fat Tropical composite cattle |
description |
Background: meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal’s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality. Results: the set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism. Conclusions: these results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-06-05 2020-07-13T13:09:02Z 2020-07-13T13:09:02Z |
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 |
MOKRY, F. B. et al. Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach. BMC Genetics, [S.l.], v. 14, p. 1-11, June 2013. DOI: 10.1186/1471-2156-14-47. http://repositorio.ufla.br/jspui/handle/1/41906 |
identifier_str_mv |
MOKRY, F. B. et al. Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach. BMC Genetics, [S.l.], v. 14, p. 1-11, June 2013. DOI: 10.1186/1471-2156-14-47. |
url |
http://repositorio.ufla.br/jspui/handle/1/41906 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
BioMed Central (BMC) |
publisher.none.fl_str_mv |
BioMed Central (BMC) |
dc.source.none.fl_str_mv |
BMC Genetics reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1784550172243525632 |