Objective
Pork meat quality is an economically important and complex trait for which determinants remain mostly unknown. Since meat quality measurements cannot be taken on a live animal it is an important trait where marker-assisted-selection could be applied. Recent studies have shown that a significant component of meat quality variation is genetic. However, only two major genes, which impact on pork meat quality, have been discovered to date, the 'Halothane' and 'RN' genes. Their discovery has led to the creation of DNA markers to select slaughter pigs with improved meat quality. In 2001, the EC funded the 'Quality Pork Genes' project, developed by PIC in association with several European institutions, aiming at ultimately to identify genes involved in meat quality traits. As part of this project, meat quality measurements and RNA, protein and also DNA samples will be collected on animals from divergent breeds with different meat quality characteristics. Association studies between these meat quality traits and gene expression differences between the divergent breeds will be performed in order to identify genes involved in meat quality variation. Using these resources, we plan to identify a large number of single nucleotide polymorphisms (SNPs). In this new project, SNPs present in ~400 genes expressed in pig muscle will be identified. The allele frequency of 100 of these SNPs will be then determined in breeds selected for the 'Quality Pork Genes' project. In the last phase, association studies between these SNPs and meat quality traits will be performed. New markers associated with variation in pig meat quality will be identified. These markers will be used to improve the quality of pork and pork products in marker-assisted-selection programs.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- natural sciencesbiological sciencesgeneticsnucleotides
- natural sciencesbiological sciencesgeneticsRNA
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Topic(s)
Data not availableCall for proposal
Data not availableFunding Scheme
BUR - Bursaries, grants, fellowshipsCoordinator
CB2 1QP CAMBRIDGE
United Kingdom