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Exploring genome organization at QTLs for beef production traits at high resolution to identify candidate genes


Selective breeding of livestock has been very successful in increasing production in easily measure traits eg yields or growth rates and muscling. However, up to now there has been little selection for the more difficult to measure traits such as product q uality, efficiency of production or health. Genetic factors in conjunction with environmental variables can affect beef production at several levels, including simple growth and conformation traits, through to meat quality traits.Genome mapping programmes world-wide are beginning to identify chromosomal regions (Quantitative Trait Loci QTL) that harbour genes that are associated with particular aspects of meat quality, eg toughness, taste etc, but up to now few of theunderlying genes responsible for the var iation have been identified. This is in part because the QTL have only been mapped at low resolution and partly because few genes are mapped in the bovine genome to identify positional candidate trait genes.This project will develop a moderately large numb er of markers to explore the organisation of the bovine genome at chromosomal regions harbouring the beef related QTL. Initially public databases of the bovine genome will be examined todevelop new markers (microsatellites and SNPs). This information will be used to more precisely map the QTL for meat quality traits in structured populations (families) by linkage disequilibrium analysis. The markers will also be mapped on a radiationhybrid panel to improve comparative maps between cattle and other species. The refined QTL regions will then be explored, and refined further using animals in unstructured populations to define the linkage disequilibrium present in commercial cattlepopulations. The final phase of the project uses this information to identify cand idate genes that will be tested for association with variations in the beef traits. The application to commercial herds of SNP testing at the candidate genes will be of great interest.

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Roslin Institute
United Kingdom

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