Genome-wide association studies reveal susceptibility loci for digital dermatitis in Holstein cattle

Digital dermatitis (DD) causes lameness in dairy cattle. To detect quantitative trait loci (QTL) associated with DD, genome-wide association studies (GWAS) were performed using high density single nucleotide polymorphism (SNP) genotypes and binary case/control, quantitative (average number of FW per hoof trimming record), and recurrent (cases with  2 DD episodes vs. controls) phenotypes from cows across four dairies (controls n = 129 vs. FW n = 85). Linear mixed model (LMM) and random forest (RF) approaches identified top SNPs, which were used as predictors in Bayesian regression models to assess SNP predictive value. The LMM and RF analyses identified a QTL on BTA1 for the binary phenotype and on BTA2 for the quantitative phenotype. The binary and recurrent LMM GWASs also detected a QTL on BTA2 that was at a different position than the QTL from the quantitative phenotype analysis. The QTL on BTA1 lacked apparent candidate genes, whereas both QTL on BTA2 included genes associated with immune response and wound healing. Although larger sample sizes are necessary to reaffirm these small effect loci amidst a strong environmental effect, the sample cohort used in this study was sufficient for estimating SNP effects with high predictive value. Whole blood was collected from 222 cows (cases n = 90, controls n = 132) from the coccygeal vein in the tail. Blood samples were centrifuged, and genomic DNA was extracted from the resulting buffy coat layer using the QIAGEN QIAamp DNA Blood Mini Kit . DNA samples were genotyped on the Illumina BovineHD BeadChip, and Illumina’s GenCall algorithm was used to call genotypes. Of the 222 samples, six were removed during quality filtering (cases n = 3, controls n = 3), leaving 216 cows for analysis (cases n = 87, controls n = 129). Of the 87 cases, 24 had recurrent FW episodes and were used in the GWAS of controls vs. recurrent FW cases.