Sire effects on carcass and meat quality traits of young Nellore bulls

Bonin, Michael; Ferraz, José Bento Sterman; Eler, Joanir Pereira; Rezende, Fernanda Marcondes de; Cucco, D. C.; Carvalho, Minos Esperândio; Silva, R.C.G.; Gomes, Rodrigo da Costa; Oliveira, E.C.M.

doi:10.4238/2014.april.29.3

Cited by 14 publications

(9 citation statements)

References 21 publications

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“…Among the studied traits, WBSF showed the highest coefficient of variation (30%) and the mean value was slightly above the limit of "tender" beef (Shackelford et al, 1997;Destefanis et al, 2008;Rodas-González et al, 2009; Table 1). Our WBSF results were slightly higher than the values reported in the literature for Nelore cattle meat (Bonin et al, 2014;Magalhães et al, 2016;Baldassini et al, 2017) and for Bos taurus beef (O'Connor et al, 1997;Riley et al, 2005), while marbling had a low coefficient of variation and the mean value was similar to previous determinations in Nelore beef (Francisco et al, 2015;Baldassini et al, 2017), which used the same marbling score as our study. Comparison marbling scores is difficult because of the use of different scoring systems.…”

Section: Meat Quality Evaluationsupporting

confidence: 61%

Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy1

Magalhães

Teixeira

Ríos

et al. 2018

Journal of Animal Science

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The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force [Warner-Bratzler shear force (WBSF)], marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R2C), and prediction (R2P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R2P = 0.40) and b* color (RMSEP = 1.21, R2P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R2P = 0.16) and a* (RMSEP = 1.42, R2P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

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Section: Meat Quality Evaluationsupporting

confidence: 61%

Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy1

Magalhães

Teixeira

Ríos

et al. 2018

Journal of Animal Science

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“…Inversely proportional to REA, the backfat thickness (BFT) is related to the percentage of fat in the carcass. BFT is essential to protect the carcass during cooling, avoiding problems such as cold shortening, drip loss and dark cutting [2–4].…”

Section: Introductionmentioning

confidence: 99%

Gene co-expression networks associated with carcass traits reveal new pathways for muscle and fat deposition in Nelore cattle

et al. 2019

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BackgroundPositively correlated with carcass weight and animal growth, the ribeye area (REA) and the backfat thickness (BFT) are economic important carcass traits, which impact directly on producer’s payment. The selection of these traits has not been satisfactory since they are expressed later in the animal’s life and multigene regulated. So, next-generation technologies have been applied in this area to improve animal’s selection and better understand the molecular mechanisms involved in the development of these traits. Correlation network analysis, performed by tools like WGCNA (Weighted Correlation Network Analysis), has been used to explore gene-gene interactions and gene-phenotype correlations. Thus, this study aimed to identify putative candidate genes and metabolic pathways that regulate REA and BFT by constructing a gene co-expression network using WGCNA and RNA sequencing data, to better understand genetic and molecular variations behind these complex traits in Nelore cattle.ResultsThe gene co-expression network analysis, using WGCNA, were built using RNA-sequencing data normalized by transcript per million (TPM) from 43 Nelore steers. Forty-six gene clusters were constructed, between them, three were positively correlated (p-value< 0.1) to the BFT (Green Yellow, Ivory, and Light Yellow modules) and, one cluster was negatively correlated (p-value< 0.1) with REA (Salmon module). The enrichment analysis performed by DAVID and WebGestalt (FDR 5%) identified eight Gene Ontology (GO) terms and three KEGG pathways in the Green Yellow module, mostly associated with immune response and inflammatory mechanisms. The enrichment of the Salmon module demonstrated 19 GO terms and 21 KEGG pathways, related to muscle energy metabolism, lipid metabolism, muscle degradation, and oxidative stress diseases. The Ivory and Light yellow modules have not shown significant results in the enrichment analysis.ConclusionWith this study, we verified that inflammation and immune response pathways modulate the BFT trait. Energy and lipid metabolism pathways, highlighting fatty acid metabolism, were the central pathways associated with REA. Some genes, as RSAD2, EIF2AK2, ACAT1, and ACSL1 were considered as putative candidate related to these traits. Altogether these results allow us to a better comprehension of the molecular mechanisms that lead to muscle and fat deposition in bovine.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5345-y) contains supplementary material, which is available to authorized users.

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“…In the meat industry, an adequate layer of fat acts as a thermal insulator during carcass cooling process, avoiding problems such as cold shortening [8, 9]. Also, the layer of fat is an important source of essential fatty acids and acts in the transport of fat-soluble vitamins, constituting a source of energy and insulation for the body of the animal [10].…”

Section: Introductionmentioning

confidence: 99%

Comparative muscle transcriptome associated with carcass traits of Nellore cattle

et al. 2017

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BackgroundCommercial cuts yield is an important trait for beef production, which affects the final value of the products, but its direct determination is a challenging procedure to be implemented in practice. The measurement of ribeye area (REA) and backfat thickness (BFT) can be used as indirect measures of meat yield. REA and BFT are important traits studied in beef cattle due to their strong implication in technological (carcass yield) and nutritional characteristics of meat products, like the degree of muscularity and total body fat. Thus, the aim of this work was to study the Longissimus dorsi muscle transcriptome of Nellore cattle, associated with REA and BFT, to find differentially expressed (DE) genes, metabolic pathways, and biological processes that may regulate these traits.ResultsBy comparing the gene expression level between groups with extreme genomic estimated breeding values (GEBV), 101 DE genes for REA and 18 for BFT (false discovery rate, FDR 10%) were identified. Functional enrichment analysis for REA identified two KEGG pathways, MAPK (Mitogen-Activated Protein Kinase) signaling pathway and endocytosis pathway, and three biological processes, response to endoplasmic reticulum stress, cellular protein modification process, and macromolecule modification. The MAPK pathway is responsible for fundamental cellular processes, such as growth, differentiation, and hypertrophy. For BFT, 18 biological processes were found to be altered and grouped into 8 clusters of semantically similar terms. The DE genes identified in the biological processes for BFT were ACHE, SRD5A1, RSAD2 and RSPO3. RSAD2 has been previously shown to be associated with lipid droplet content and lipid biosynthesis.ConclusionIn this study, we identified genes, metabolic pathways, and biological processes, involved in differentiation, proliferation, protein turnover, hypertrophy, as well as adipogenesis and lipid biosynthesis related to REA and BFT. These results enlighten some of the molecular processes involved in muscle and fat deposition, which are economically important carcass traits for beef production.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3897-x) contains supplementary material, which is available to authorized users.

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Sire effects on carcass and meat quality traits of young Nellore bulls

Cited by 14 publications

References 21 publications

Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy1

Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy1

Gene co-expression networks associated with carcass traits reveal new pathways for muscle and fat deposition in Nelore cattle

Comparative muscle transcriptome associated with carcass traits of Nellore cattle

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