Beef Quality: The Actual Research Challenge for Consumer Satisfaction
Canadian beef producers have a tremendous opportunity to meet the increasing global demand for high quality animal protein products. However, high feed costs and inconsistent quality remain significant challenges. Research has been underway towards addressing these challenges through the use of DNA panels to allow animals to be selected and specifically managed according to DNA profile to increase the production efficiency and product quality.
Beef quality audits in Canada continue to identify beef tenderness as a top quality concern consumers have with beef. If beef was more consistently tender, consumers would be willing to pay more for beef and purchase it more often (Shackelford et al., 2001). Although feed efficiency and beef quality represent tremendous challenges and opportunities for the industry showing a moderate to high heritability (between 0.12-0.53), the ability of the industry to address these through improved genetics has been almost impossible until very recently with the development of genomics technologies. Traditional approaches to genetic improvement for these traits are not successful as the traits are too expensive and difficult to measure. Current research going on in our group at University of Guelph and University of Alberta in collaboration with AgSights (ON) and Delta Genomics (AB) is designed to improve the genomic tools available to increase selection efficiency and address new traits of importance for consumers and with benefit to beef producers.
The Canadian beef industry is highly segmented and contains multiple stakeholders (seedstock, cow-calf, feedlot, processor, retailer and consumer). The division between groups along the supply chain enables individual stakeholders to make logical decisions regarding their own business practices. However, in light of the entire chain, these decisions can at times be detrimental to the end product and to consumer satisfaction. With little or no market signal back along the supply chain, needed changes are not necessarily made for the end product, which can impact desire for the end product and competition with other protein choices. Poor information flow along the beef supply chain can lead to inefficiencies, as demonstrated in the decline in high yielding carcasses in the past decade (down from 66% to 41%, Canadian Beef Grading Agency data).
Genomic approaches offer an opportunity to accelerate genetic improvement, but genomics requires accurate phenotypes (and genotypes) from genomically-linked individual animals. Selection efficiency with EPDs (expected progeny differences) will be higher with the knowledge gained from functional genomics studies using the new - OMICS technologies such as transcriptomics (Cánovas, 2016; Van Eenennaam, 2016). Despite a growing molecular and physiological understanding of complex traits, little is known about the target genes determining the traits and their precise function, and a significant unexplained source of variation of phenotypes remains in beef cattle. Within this context, a more complete understanding of the key regulator genes and regulatory pathways involved in economically important traits such as tenderness in beef cattle will provide knowledge to help improve genetic selection and production management. Therefore, studying the transcriptome using high throughput -OMICS data (RNA-Sequencing) from muscle and fat biopsies of the most divergent animals with extreme Warner-Bratzler shear force (WBSF) values (HIGH and LOW tenderness groups) will complement these tools and further advance identification of key regulator genes and functional SNP within a systems biology approach (Canovas et al., 2014; Fonseca et al., 2018). Additionally, fatty acid composition of beef has also been rated as an important factor for a more nutritious and healthier food; therefore, identification of genetic markers that are associated with meat tenderness and fatty acid composition in beef cattle along with a precise understanding of the biology underlying the traits will provide a more effective improvement in meat quality and marker-assisted diet management.
Genome-wide association studies (GWAS) can provide great insight into the genetic architecture of complex traits, potential causal variants and candidate genes in beef cattle (Suravajhala, et al., 2016). Numerous GWAS studies have been performed in Bos taurus, Bos indicus and crossbred beef cattle on meat quality and carcass traits (Magalhães et al., 2016). Several of these studies have focused on WBSF as a relevant trait and identified genetic markers mostly on chromosome 10 within the genomic sequence of CAPN3 gene in Brahman cattle (Barendse, et al., 2008) and on chromosomes 7 (spanning CAST gene) and 29 (spanning CAPN1 gene) for Angus, Charolais, Hereford, Limousin and Simmental breeds (Hulsman et al., 2014).
In the same context, preliminary results from our project identified nine markers (SNPs) significantly associated with tenderness (WBSF) in a crossbreed (Angus x Simmental) population located at the Elora Beef Research Center (Elora, ON). Six of these markers were located on chromosome 29, and two were on chromosome 2 (P<0.05). In addition, looking at the genes containing significant SNPs, we also identified 105 genes in close proximity (<500 Kb) of significant SNPs because they could be segregating with (in linkage disequilibrium) the causal variant. Among the 105 genes proximal to the WBSF SNPs, metabolic process made up most of the functional classification, which included CAPN1 gene. Three SNPs were located in the CAPN1 gene on chromosome 29. The CAPN1 gene is well known for affecting meat tenderness. The CAPN1 gene is involved in post-mortem proteolysis of muscle fibres and has been shown to be associated with meat tenderness in Bos taurus, Bos indicus, and their crossbreeds (Pinto et al., 2011). The effect of CAPN1 haplotypes (the group of genetic variants inherited together within the CAPN1 region) has been shown to be significant for tender alleles at both CAPN1 and CAST which together would have 4.11 kg lower WBSF than animals homozygous for tough alleles (a lower WBSF score represents more tender meat. In addition, two SNPs located in the glycogen phosphorylase (PYGM) and the Neurexin2 (NRXN2) genes were significantly associated with WBSF. Functional analysis showed that the PYGM gene is involved in the generation of precursor metabolites and energy during glycolysis (Nogales-gadea et al., 2012) and is responsible for the breakdown of cellular glycogen into glucose, which is the sugar used for cellular energy. The NRXN2 gene is associated with biological processes related with angiogenesis, blood coagulation and heart, nervous system and skeletal system development.
Other studies investigating gene expression through RNA-Sequencing provided new possibilities of identifying novel functional variants and future changes in the product levels and structure of the genes of the Longissimus thoracis (ribeye) muscle in different breeds. Transcriptomic analysis could detect key regulator genes involved in the biological processes associated with the tenderness of the meat such as organization and synthesis of collagen fibrils, cell growth, development and muscle contraction. Currently, Cánovas Lab at U of G is collaborating with UNESP in Brazil (Albuquerque Lab) where they are performing similar research in Nellore cattle, a Bos indicus beef breed. Preliminary results have revealed differentially expressed genes associated with residual feed intake, tenderness, marbling, and other carcass and quality meat traits in the Longissimus thoracis muscle from animals with different environment conditions, ages and management systems including castrated and uncastrated animals. The purpose of our study is to increase the number of genotyped animals (pure and cross-bred) with phenotype records for WBSF in Canadian beef cattle. The results of this study, including transcriptomic analysis, will be validated across beef breeds and independent populations to increase the efficiency of genetic selection for tenderness and other meat quality related traits in beef cattle.
- Barendse, W., Harrison, B. E., Bunch, R. J., & Thomas, M. B. (2008). Variation at the Calpain 3 gene is associated with meat tenderness in zebu and composite breeds of cattle. BMC Genetics, 9(41), 1-8.
- Beef Cattle Research Council. (2019).
- Cánovas, A. (2016). Looking Ahead: Applying new Genomic Technologies to Accelerate Genetic Improvement in Beef Cattle Looking Ahead: Applying new Genomic Technologies to Accelerate Genetic Improvement in. Ceiba, 54(1), 41-49.
- Cánovas, A., Reverter, A., Deatley, K. L., Ashley, R. L., Colgrave, M. L., Silver, G. A., ... Thomas, M. G. (2014). Multi-Tissue Omics Analyses Reveal Molecular Regulatory Networks for Puberty in Composite Beef Cattle. PLoS ONE, 9(7), e102551.
- Fonseca, P. A. S., Id-lahoucine, S., Reverter, A., Medrano, F., Id, M. S. F., Casellas, J., ... Cánovas, A. (2018). Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle. PLoS ONE, 13(10), 1-22.
- Hulsman, L. L., Garrick, D. J., Gill, C. A., Herring, A. D., Riggs, P. K., Miller, R. K., ... Riley, D. G. (2014). Genome-wide association study of temperament and tenderness using different Bayesian approaches in a Nellore - Angus crossbred population. Livestock Science, 161, 17-27.
- Magalhães, A. F. B., Camargo, M. F. de, Junior, F. G. ., Gordo, D. G. M., Tonussi, R. L., Costa, R. B., ... Albuquerque, L. G. de. (2016). Genome-Wide Association Study of Meat Quality Traits in Nellore Cattle. PLoS ONE, 1-12.
- Nogales-gadea, G., Luna, D., Marti, M. A., Garcia-arum, E., Camara, Y., Brull, A., & Andreu, A. L. (2012). Knock-in mice for the R50X mutation in the PYGM gene present with McArdle disease. Brain, 135, 2048-2057.
- Pinto, L. F., Ferraz, J. B. S., Meirelles, F. V., Eler, J. P., Rezende, F. M., Carvalho, M. E., ... Silva, R. C. G. (2011). Association of SNPs on CAPN1 and CAST genes with tenderness in Nellore cattle genes with tenderness in Nellore cattle. Genetics and Molecular Research, 9(3), 1431-1442.
- Shackelford, S. D., Wheeler, T. L., Meade, M. K., Reagan, J. O., Byrnes, B. L., & Koohmaraie, M. (2001). Consumer impressions of Tender Select beef. Journal of animal science, 79(10), 2605-2614
- Suravajhala, P., Kogelman, L. J. A., & Kadarmideen, H. N. (2016). Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare. Genetics Selection Evolution, 48(38), 1-14.
- Van Eenennaam, A. (2016). Recent Developments in Genetic Evaluations. 2016-1.
1Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, ON, N1G 2W1 Canada
2Department of Animal Science, School of Agricultural and Veterinarian Sciences, Sao Paulo State University (UNESP), Jaboticabal - São Paulo, Brazil;
3Neogen Canada, Edmonton, Alberta, T6G 2P5, Canada;
4Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, T6G 2P5, Canada
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|Author:|| Angela Cánovas1,
Pablo Augusto de Souza Fonseca1, Maria Malane Magalhães
Muniz1,2, Alexandra Livernois1, Shadi Nayeri1,
University of Guelph
Lúcia Galvão Albuquerque2, Sao Paulo State University (UNESP)
Michelle Miller3, Gordon Vander Voort3, Neogen Canada, Edmonton, Alberta
Graham Plastow4, University of Alberta
|Creation Date:||27 March 2020|
|Last Reviewed:||27 March 2020|