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Identifying genetic loci controlling neonatal passive transfer of immunity using a hybrid genotyping strategy
- Rohrer, G. A., Rempel, L. A., Miles, J. R., Keele, J. W., Wiedmann, R. T., Vallet, J. L.
- Animal genetics 2014 v.45 no.3 pp. 340
- DNA, ammonium sulfate, analysis of variance, animal models, colostrum, genome, genotyping, hybrids, immunity, loci, maternal effect, piglets, quantitative trait loci, selection methods, single nucleotide polymorphism, sires
- Colostrum intake is critical to a piglet's survival and can be measured by precipitating out the γ‐immunoglobulins from serum with ammonium sulfate (immunocrit). Genetic analysis of immunocrits on 5312 piglets indicated that the heritabilities (se) for direct and maternal effects were 0.13 (0.06) and 0.53 (0.08) respectively. To identify QTL for direct genetic effects, piglets with the highest and lowest immunocrits from 470 litters were selected. Six sets of DNA pools were created based on sire of the litter. These 12 DNA pools were applied to Illumina Porcine SNP60 BeadChips. Normalized X and Y values were analyzed. Three different SNP selection methods were used: deviation of the mean from high vs. low pools, the deviation adjusted for variance based on binomial theory and ANOVA. The 25 highest ranking SNPs were selected from each evaluation for further study along with 12 regions selected based on a five‐SNP window approach. Selected SNPs were individually genotyped in the 988 piglets included in pools as well as in 524 piglets that had intermediate immunocrits. Association analyses were conducted fitting an animal model using the estimated genetic parameters. Nineteen SNPs were nominally associated (P < 0.01) with immunocrit values, of which nine remained significant (P < 0.05) after Bonferroni correction, located in 16 genomic regions on 13 chromosomes. In conclusion, the pooling strategy reduced the cost to scan the genome by more than 80% and identified genomic regions associated with a piglet's ability to acquire γ‐immunoglobulin from colostrum. Each method to rank SNPs from the pooled analyses contributed unique validated markers, suggesting that multiple analyses will reveal more QTL than a single analysis.