Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/15/2014
Publication Date: 4/23/2014
Citation: Pereira, A.G., Utsunomiya, Y.T., Sonstegard, T.S., Castilli, C., Garcia, J.F. 2014. Genome-Wide scans for carcass and meat traits in nellore cattle. BARC Poster Day, Poster 34, pp. 46. Interpretive Summary:
Technical Abstract: Beef cattle industry is one of the main highlights of Brazilian agribusiness, however the standardization of meat products is still an issue. The lack of standardization of quality characteristics as fat thickness and tenderness, and the burden and time spent on collecting and evaluating large number of phenotypes, justifies the generation of knowledge on the mechanisms involved in the manifestation of qualitative and quantitative characteristics related carcass quality from animals produced in tropical production environments. Using genomic-based tools (SNP chips), it is possible to identify predictors of quality and gain a better understanding of muscle development and growth with implications on the improvement of quantitative and qualitative characteristics of meat. Quantitative and qualitative characteristics of beef carcasses were measured from 400 Nellore cattle raised on pasture until 18 months of age (550 kg to slaughter). Phenotypic measures included meat pH, marbling, rib eye area and fat thickness obtained from the 12th and 13th ribs on the left side of the animal. Evaluations of water hole capacity, cooking loss, color for L*, a* and b* parameters and shear force were obtained from longissimus dorsi muscle steaks taken from 10th, 11th and 12th ribs under three different aging times (7, 14 and 21 days). DNA isolates from these meat samples were genotyped with the Illumina BovineHD BeadChip (786,798 markers). Marker scores were trimmed according to thresholds for quality control and genetic stratification. These data will be analyzed using genome wide association methods to identify genomic regions for further investigation by next generation sequencing to find the causative variation affecting meat quality traits.