Evolution of the Bovine TLR Gene Family and Member Associations with Mycobacterium avium Subspecies paratuberculosis Infection

Fisher, Colleen A.; Bhattarai, Eric K.; Osterstock, Jason B.; Dowd, Scot E.; Seabury, Paul M.; Vikram, Meenu; Whitlock, Robert H.; Schukken, Ynte H.; Schnabel, Robert D.; Taylor, Jeremy F.; Womack, James E.; Seabury, Christopher M.

Our methodological workflows resulted in the robust identification of SNPs with precise estimates of MAF for the bovine TLR genes (see methods), as evidenced by the regression of MAFs derived from the analysis of pyrosequencing data and allelespecific genotyping assays ( Figure 1 ). For these genes, our genotyping assays provide a 70 fold increase in marker density relative to the Illumina BovineSNP50 assay, which queries four SNPs either within (TLR6, TLR10) or proximal to (TLR7, TLR8) the targeted loci, and a greater than 3 fold increase in marker density relative to the new Illumina BovineHD assay (777K), which possesses an average marker interval density of approximately 1 SNP/3.5 kb. Notably, the new BovineHD assay includes 84 SNPs that are either within or proximal to (#2 Kb) the 10 Table 5 ). Validated polymorphisms, reconstructed haplotypes, and the tagSNPs/Indels identified in this study will directly facilitate the fine mapping of bovine health-related QTL [23] [24] [25] [26] [27] , while also enabling further evaluation of SNPs tentatively associated with differential susceptibility to Johne's disease (MAP infection) [19] [20] [21] [22] 46] (Table 5 ). While large numbers of tightly clustered SNPs are sometimes difficult to genotype, we endeavored to validate all Table S2 for SNP information). Node sizes are proportional to haplotype frequency, and all branch lengths are drawn to scale. Alphabetized letters at nodes represent the breed distribution of each haplotype (Table S4) . Notably, given the complexity of the network, only nodes representing$10 cattle are labeled (A-F), which collectively represents.93% of the cattle meeting the phase requirements (n = 524 cattle with best-pair probabilities$0.90). Median vectors are indicated as ''mv''. doi:10.1371/journal.pone.0027744.g004 detected variants by redesigning primers and manipulating PCR conditions for problematic markers. Accordingly, we successfully validated several SNPs for which assays had previously failed [30] , and we also validated the majority of the newly identified putative SNPs (pyrosequencing data) that were not associated with homopolymer repeats. Furthermore, some regions of TLR1 posed the greatest technical challenge due to sequence similarity with TLR6. For this reason, at least some DNA sequencing from medium-range PCR products designed to specifically amplify each locus is needed to exhaustively ascertain all possible variants spanning the TLR1-TLR6 gene cluster.