Incorporation of genomic information in the study of meat quality in Santa Inês sheep
| Grant number: | 13/04504-3 |
| Support type: | Regular Research Grants |
| Duration: | June 01, 2013 - August 31, 2015 |
| Field of knowledge: | Agronomical Sciences - Animal Husbandry |
| Principal Investigator: | Gerson Barreto Mourão |
| Grantee: | Gerson Barreto Mourão |
| Home Institution: | Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil |
| Assoc. researchers: | Eduardo Francisquine Delgado ; Fabyano Fonseca e Silva ; Luis Fernando Batista Pinto ; Luiz Lehmann Coutinho |
Abstract
The sheep industry is a growing agricultural activities in Brazil, and although it, the country performs imports of sheep meat to supply the consumer market, because the supply of meat is still insufficient. The production of animals adapted to the tropical climate allows the reduction of costs, such as Santa Ines breed, which is the main breed created in Brazil, with excellent reproduction and adaptation traits. But, this breed needs improvement in carcass and meat quality traits, when compared to other breeds, which are important traits for acceptance by the market of meat. However, the improvment of quality of meat are difficult by classical breeding methods, with an option is the incorporation of molecular information for obtaining these genetic gain. Thus, will be performed the genotyping of 432 animals of Santa Inês breed using the Ovine chip SNP50 BeadChip, phenotyped for meat quality and carcass traits, which are: ribeye area, fat thickness, marbling score, temperature, pH, shear force, water losses by cooking, coloring, sarcomere length, myofibrillar fragmentation index, total content of lipids and fatty acid profile, which will be measured in the Longissimus dorsi muscle. The aims are study the genetic architecture of carcass and meat quality traits in sheep by identifying regions of the genome associated with these traits, compare different methods for predicting the effects of SNP markers and study the relationship multi-phenotypic between SNPs and between traits through multivariate analyzes. (AU)