Submitted to: Animal Genetics International Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: May 3, 2006
Publication Date: August 10, 2006
Repository URL: http://www.isag.org.uk/society/conferences.asp
Citation: Kuehn, L.A., Rohrer, G.A., Nonneman, D.J., Thallman, R.M., Leymaster, K.A. 2006. Detection of single nucleotide polymorphisms on porcine chromosome 7 associated with ultrasonic backfat in a segregating Meishan x White Cross population using a model with polygenic effects. (Abstract) Animal Genetics International Conference Proceedings. p. 104. Abstract #E353. Technical Abstract: Multiple genome scans have indicated the presence of QTL for backfat deposition on porcine chromosome 7 (SSC7). The objective in this study was to determine if genotypes of 14 SNP positioned between 50 and 69 cM were associated with variation in ultrasonic measures of backfat. Genotypic and phenotypic data were collected on 298 gilts, evenly split between the F8 and F10 generations of the USMARC Meishan resource population and 4 and 6 generations after the herd was closed and random-mated (¼ Meishan composition). Backfat phenotypes were recorded from three locations along the back using an A-mode Renco Lean-Meter probe at approximately 210 and 235 days of age in generations 4 and 6, respectively. Gilts were also genotyped for a TBG SNP thought to influence backfat. The three ultrasound measures were averaged for the SNP analysis. Regressors for additive, dominant, and imprinting effects of each SNP were calculated using genotypic probabilities derived by allelic peeling algorithms in GenoProb. The association model included fixed effects of scan date and TBG genotype, covariates of weight and SNP regressors, and random additive polygenic effects to account for genetic similarities between animals not explained by known genotypes. Variance components for polygenic effects and error were estimated using MTDFREML. Each SNP was fitted separately due to potential multicollinearity between regressions of closely linked markers. Power to detect imprinting effects was weak so it was eliminated from the model. Across all analyses, TBG genotype was significant (P<0.05) with an additive effect of approximately 1.1 mm of backfat. Additive effects (P<0.05) between 0.7 and 1.1 mm of backfat were observed for markers 13438.1h, 11807.1h, and 17281.1h at locations 50.1, 63.0 and 63.0 cM, respectively. These associations likely represent the same causative mutation; no significant effects were detected if these SNP were fitted simultaneously because the total effect was partitioned across markers. Genetic improvement programs for lean yield could benefit from inclusion of these marker haplotypes.