☆ 4.5 Article

Effects of DGAT1 gene on meat and carcass fatness quality in Chinese commercial cattle

MOLECULAR BIOLOGY REPORTS (2013)

Journal

MOLECULAR BIOLOGY REPORTS

Volume 40, Issue 2, Pages 1947-1954

Publisher

SPRINGER

DOI: 10.1007/s11033-012-2251-2

Keywords

Cattle; DGAT1 gene; Meat and carcass fatness quality traits; SNPs

Funding

earmarked fund for Modern Agro-industry Technology Research System [CARS-38]
National Natural Science Foundation of China [30871774, 31272428, 31201768]
New Variety of Transgenic Organism Great Breeding Program [2008ZX08007-002, 2009ZX08007-005B, 2009ZX08009-157B]
Twelfth Five-Year Plan National Science and Technology Support Project [2011BAD28B04]
China Postdoctoral Science Foundation [2012M510011]

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Abstract

This study was designed to investigate the candidate single nucleotide polymorphisms (SNPs) in the exon's region of bovine diacylglycerol O-acyltransferase (DGAT1) gene using bioinformatics and experimental methods. A total of 17 SNPs were screened from public data resources and DNA sequencing. Three SNPs (c.572A > G, c.1241C > T and c.1416T > G) of these candidate SNPs were genotyped by created restriction site-polymerase chain reaction (CRS-PCR) methods. The gene-specific SNP markers and their effects on meat and carcass fatness quality traits were evaluated in Chinese commercial cattle. The c.572A > G and c.1416T > G significantly effected on backfat thickness, longissimus muscle area, marbling score, fat color and Warner-Bratzler shear force. No significant association was detected between the c.1241C > T and measured traits. Results from this study suggested that the SNP markers may be effective for the marker-assisted selection of meat and carcass fatness quality traits, and added new evidence that DGAT1 gene is an important candidate gene for the improvement of meat and carcass fatness quality in beef cattle industry.

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Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

Fernando Brito Lopes, Fernando Baldi, Ludmilla Costa Brunes, Marcos Fernando Oliveira e Costa, Eduardo da Costa Eifert, Guilherme Jordao Magalhaes Rosa, Raysildo Barbosa Lobo, Claudio Ulhoa Magnabosco

Summary: This study evaluates the advantage of preselecting SNP markers using the Markov blanket algorithm in genomic prediction for carcass and meat quality traits in Nellore cattle. The results show that using the Markov blanket SNP markers can result in lower prediction accuracy compared to using all SNPs, but in certain cases, still achieve high prediction accuracy. The use of Markov blanket-identified SNP markers can improve genomic selection efficiency and management decisions.

JOURNAL OF ANIMAL BREEDING AND GENETICS (2023)