Rumen bacterial communities in forage-fed and grazing cattle continually adapt to a wide range of changing dietary composition, nutrient density, and environmental conditions. We hypothesized that very distinct community assemblages would develop between the fiber and liquid fractions of rumen contents in animals transitioned from bermudagrass hay diet to a grazed wheat diet. To address this hypothesis, we designed an experiment utilizing a 16S-based bTEFAP pyrosequencing technique to characterize and elucidate changes in bacterial diversity among the fiber and liquid rumen fractions and whole rumen contents of 14 (Angus x Hereford) ruminally cannulated steers sequentially fed bermudagrass hay (Cynodon dactylon; 34 days) and grazing wheat forage (28 days). Bermudagrass hay was a conserved C4 perennial grass lower in protein and higher in fiber (11% and 67%, respectively) content than grazed winter wheat (Triticum aestivum), a C3 annual grass with higher protein (20%) and a large (66%) soluble fraction.Significant differences in the OTU estimates (Chao1, Ace,and Rarefaction) were detected between fractions of both diets, with bermudagrass hay supporting greater diversity than wheat forage. Sequences were compared with a 16S database using BLASTn and assigned sequences to respective genera and genera-like units based on the similarity value to known sequences in the database. Predominant genera were Prevotella (up to 33%) and Rikenella-like (upto 28%) genera on the bermudagrass diet and Prevotella (upto 56%) genus on the wheat diet irrespective of the fractions. Principle component analyses accounted for over 95% of variation in 16S estimated bacterial community composition in all three fractions and clearly differentiated communities associated with each diet. Overall, bermudagrass hay diets clustered more clearly than wheat diets.These data are the first to explore bacterial diversity dynamics in a common population of animals in response to contrasting grass forage diets.

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Members of the Toll-like receptor (TLR) gene family occupy key roles in the mammalian innate immune system by functioning as sentries for the detection of invading pathogens, thereafter provoking host innate immune responses. We utilized a custom next-generation sequencing approach and allele-specific genotyping assays to detect and validate 280 biallelic variants across all 10 bovine TLR genes, including 71 nonsynonymous single nucleotide polymorphisms (SNPs) and one putative nonsense SNP. Bayesian haplotype reconstructions and median joining networks revealed haplotype sharing between Bos taurus taurus and Bos taurus indicus breeds at every locus, and specialized beef and dairy breeds could not be differentiated despite an average polymorphism density of 1 marker/158 bp. Collectively, 160 tagSNPs and two tag insertion-deletion mutations (indels) were sufficient to predict 100% of the variation at 280 variable sites for both Bos subspecies and their hybrids, whereas 118 tagSNPs and 1 tagIndel predictively captured 100% of the variation at 235 variable sites for B. t. taurus. Polyphen and SIFT analyses of amino acid (AA) replacements encoded by bovine TLR SNPs indicated that up to 32% of the AA substitutions were expected to impact protein function. Classical and newly developed tests of diversity provide strong support for balancing selection operating on TLR3 and TLR8, and purifying selection acting on TLR10. An investigation of the persistence and continuity of linkage disequilibrium (r2≥0.50) between adjacent variable sites also supported the presence of selection acting on TLR3 and TLR8. A case-control study employing validated variants from bovine TLR genes recognizing bacterial ligands revealed six SNPs potentially eliciting small effects on susceptibility to Mycobacterium avium spp paratuberculosis infection in dairy cattle. The results of this study will broadly impact domestic cattle research by providing the necessary foundation to explore several avenues of bovine translational genomics, and the potential for marker-assisted vaccination.

The objective of this study was to evaluate the efficacy of wellness trait genetic predictions in commercial herds of US Holstein cows from herds that do not contribute phenotypic information to the evaluation. Tissue samples for DNA extraction were collected from more than 3,400 randomly selected pregnant Holstein females in 11 herds and 2 age groups (69% nulliparous, 31% primiparous) approximately 30 to 60 d before their expected calving date. Lactation records from cows that calved between September 1, 2015, and December 31, 2015, were included in the analysis. Genomically enhanced predicted transmitting abilities for the wellness traits of retained placenta, metritis, ketosis, displaced abomasum, mastitis, and lameness were estimated by the Zoetis genetic evaluation and converted into standardized transmitting abilities. Mean reliabilities of the animals in the study ranged between 45 and 47% for each of the 6 traits. Animals were ranked by their standardized transmitting abilities within herd and age group then assigned to 1 of 4 groups of percentile-based genetic groups of equal size. Adverse health events, including retained placenta, metritis, ketosis, displaced abomasum, mastitis, and lameness, were collected from on-farm herd management software, and animal phenotype was coded as either healthy (0), diseased (1), or excluded for each of the 6 outcomes of interest. Statistical analysis was performed using a generalized linear mixed model with genetic group, age group, and lactation as fixed effects, whereas herd and animal nested within herd were set as random effects. Results of the analysis indicated that the wellness trait predictions were associated with differences in phenotypic disease incidence between the worst and best genetic groups. The difference between the worst and best genetic groups in recorded disease incidence was 2.9% for retained placenta, 10.8% for metritis, 1.1% for displaced abomasum, 1.7% for ketosis, 7.4% for mastitis, and 3.9% for lameness. Odds ratio estimates between the highest and lowest genetic groups ranged from 1.6 (lameness) to 17.1 (displaced abomasum) for the 6 traits analyzed. These results indicate that wellness trait information of young calves and heifers can be used to effectively predict meaningful differences in future health performance. Improving wellness traits through direct genetic selection presents a compelling opportunity for dairy producers to help reduce disease incidence and improve profitability when coupled with sound management practices.