Genome-wide efficient mixed-model study for meat quality in Nellore cattle

• Published in: Journal of animal science Vol. 94; pp. 428 - 429
• Main Authors: Buss, C E, Tizioto, P C, Oliveira, P S N, Mudadu, M A, Cesar, A S M, Ventura, R V, Afonso, J, Lima, A O D, Coutinho, L L, Tullio, R R, Regitano, L C A
• Format: Journal Article
• Language: English
• Published: Champaign Oxford University Press 01.10.2016
• Subjects: Bayesian analysis; Beef; Beef cattle; Biosynthesis; Bovidae; Cattle; Cattle industry; Cooking; Dynamin; Fatty acids; Genetic diversity; Genomes; Glycan; Lipid metabolism; Meat; Meat quality; Metabolism; Muscles; Phenotypes; Phosphatidylinositol; Polymorphism; Quantitative trait loci; Ribonucleotide reductase; Single-nucleotide polymorphism
• ISSN: 0021-8812; 1525-3163

The quality of meat, which includes several traits such as tenderness, juiciness, and fat thickness, is essential for the beef industry. Previous genome-wide association studies (GWAS) using Bayesian methods have shown that Brazilian Nellore cattle have enough genetic variation for improvement of these traits. Thus, the aim of this study was to further identify quantitative trait loci (QTL) associated with meat-quality-related traits in Nellore beef cattle by using the univariate linear mixed model (LMM) approach implemented in the GEMMA software and compare it with our previous GWA studies performed using Bayesian approaches. A total of 387 Nelore steers comprising 34 half-sib families were genotyped using the IlluminaBovineHDBeadChip. We analyzed the association between markers and Warner-Bratzler shear force, backfat thickness, ribeye muscle area, scanning parameters lightness (L*), redness (a*), and yellowness (b*) to ascertain color characteristics of the meat, water-holding capacity, cooking loss, muscle pH, myofibrillar fragmentation index, saturated fat sum, omega-6 fatty acids sum, omega-3 fatty acids sum, and ethereal extract. These phenotypes were measured in the Longissimus dorsi muscle between the 11th and 13th ribs collected at slaughter. We identified fifty-three genomic regions that each contained at least one single nucleotide polymorphism (SNP) that showed a significant association with meat quality traits (1-Mb SNP windows). Highlighted, we found regions associated with three genes-neuronal growth regulator 1 (NEGR1, chr03: 70884613-71949611), dynamin 3, and phosphatidylinositol glycan anchor biosynthesis class C (DNM3/PIGC, chr16: 37340706-38007593)-related to lipid metabolism and obesity. Our results provide a better understanding of QTL regions associated with meat quality unexplored in our previous Bayesian approach.