Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/977539
Research center of Embrapa/Collection: Embrapa Informática Agropecuária - Artigo em periódico indexado (ALICE)
Date Issued: 2013
Type of Material: Artigo em periódico indexado (ALICE)
Authors: MOKRY, F. B.
HIGA, R. H.
MUDADU, M. de A.
LIMA, A. O. de
MEIRELLES, S. L. C.
SILVA, M. V. G. B. da
CARDOSO, F. F.
OLIVEIRA, M. M. de
URBINATI, I.
NICIURA, S. C. M.
TULLIO, R. R.
ALENCAR, M. M. de
REGITANO, L. C. de A.
Additional Information: FABIANA BARICHELLO MOKRY, UFSCar; ROBERTO HIROSHI HIGA, CNPTIA; MAURÍCIO DE ALVARENGA MUDADU, CPPSE; ANDRESSA OLIVEIRA DE LIMA, UFSCar; SARAH LAGUNA CONCEIÇÃO MEIRELLES, UFV; MARCOS VINICIUS GUALBERTO BARBOSA DA SILVA, CNPGL; FERNANDO FLORES CARDOSO, CPPSUL; MAURÍCIO MORGADO DE OLIVEIRA, CPPSUL; ISMAEL URBINATI, Unesp; SIMONE CRISTINA MÉO NICIURA, CPPSE; RYMER RAMIZ TULLIO, CPPSE; MAURÍCIO MELLO DE ALENCAR, CPPSE; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE.
Title: Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
Publisher: BMC Genetics, London v. 14, n. 47, 2013.
Pages: 11 p.
Language: en
Keywords: Polimorfismo de nucleotídeo único
Metabolismo lipídico
Aprendizado de máquina
Inteligência artificial
Machine learning
Tecido adiposo subcutâneo.
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.
Thesagro: Gado de Corte.
NAL Thesaurus: Single nucleotide polymorphism
Beef cattle
Lipid metabolism
Artificial intelligence
Subcutaneous fat
Data Created: 2014-01-27
Appears in Collections:Artigo em periódico indexado (CNPTIA)

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