Date Full Report Received


Date Abstract Report Received



Primary Investigator:

Scientists working to better understand the underlying genetic control of pork quality traits; typically take very detailed measurements on animals in experimental herds, often called populations. These measurements typically are more informative than what could be gathered in commercial herds or high throughput packing plants.  The results from experimental work provide a broad overview of where within the DNA of animals there are genes influencing important pork quality traits.  However often the results reported from these experimental populations do not consistently report the same chromosomal regions that influence pork quality traits. Furthermore the regions identified are too broad so to find molecular markers that are very close to the genes controlling the traits of interest.  For this project three experimental populations (1 from Michigan State University (MSU) and 2 from the U.S. Meat Animal Research Center (MARC)) that had similar meat quality data collected from the loin or longissimus muscle were pooled.  The objective was to determine similar chromosomal locations across populations that were influencing these pork quality traits and identify the molecular markers that were significantly associated with the traits of interest. Each population was genotyped with Single Nucleotide Polymorphic (SNP) molecular markers.  One population from MARC had 60,000 SNP markers genotyped for each animal.  The second MARC and the MSU populations had 60,000 SNP markers genotyped on a subset of animals while the remainder were genotyped with approximately 9,000 SNP markers.  This subset of markers was used to impute the 60,000 SNP genotypes with high accuracy (97%).  Imputation is a mathematical procedure that uses the natural association of SNP markers that are very close together to predict the genotype of markers not directly genotyped.   Ultimately each population had 60,000 SNP markers available for analysis.  For pH taken 24 hours after slaughter, the combined analysis showed significant associations within a narrow region on swine chromosome 15 near the gene region of PRKAG3,which has been shown to significantly influence meat quality.  In addition the combined analysis showed significant associations of SNP associations with shear force on swine chromosomes 2 and 15.  The SNP associations on chromosome 2 are near the µ-calpain gene which has been shown to influence tenderness.  Overall this project demonstrates that a larger number of markers can be predicted through imputation when only a smaller number of molecular markers have been genotyped.  Thus reducing the genotyping cost.  These imputed genotypes can be successfully used in pooling the results across populations to identify markers within relatively narrow chromosomal regions that significantly associate with pork quality traits.

The results of this project have these key findings;

• Imputation can be used to determine higher density SNP genotypes from lower density SNP genotypes thus reducing genotyping costs with only minor reductions in accuracy.

• Meta-analysis can be used to combine the results of multiple whole-genome association studies which will improve the understanding of important QTLs across populations.

• A significant QTL associated with ultimate pH was determined on SSC15 which will influence pork quality.

• There were two QTLs determined for shear force with one on SSC2 and the other on SSC15. These QTL will impact tenderness.