Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

<p>Abstract</p> <p>Background</p> <p>Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.</p> <p>Methods</p> <p>Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.</p> <p>Results</p> <p>Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.</p> <p>Conclusions</p> <p>These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.</p

Tracing viral transmission and evolution of Bovine leukemia virus through long read Oxford nanopore sequencing of the proviral genome

Bovine leukemia virus (BLV) causes Enzootic Bovine Leukosis (EBL), a persistent life-long disease resulting in immune dysfunction and shortened lifespan in infected cattle, severely impacting the profitability of the US dairy industry. Our group has found that 94% of dairy farms in the United States are infected with BLV with an average in-herd prevalence of 46%. This is partly due to the lack of clinical presentation during the early stages of primary infection and the elusive nature of BLV transmission. This study sought to validate a near-complete genomic sequencing approach for reliability and accuracy before determining its efficacy in characterizing the sequence identity of BLV proviral genomes collected from a pilot study made up of 14 animals from one commercial dairy herd. These BLV-infected animals were comprised of seven adult dam/daughter pairs that tested positive by ELISA and qPCR. The results demonstrate sequence identity or divergence of the BLV genome from the same samples tested in two independent laboratories, suggesting both vertical and horizontal transmission in this dairy herd. This study supports the use of Oxford Nanopore sequencing for the identification of viral SNPs that can be used for retrospective genetic contact tracing of BLV transmission

Identification of BoLA Alleles Associated with BLV Proviral Load in US Beef Cows

Bovine leukemia virus (BLV) causes enzootic bovine leukosis, the most common neoplastic disease in cattle. Previous work estimates that 78% of US beef operations and 38% of US beef cattle are seropositive for BLV. Infection by BLV in a herd is an economic concern for producers as evidence suggests that it causes an increase in cost and a subsequent decrease in profit to producers. Studies investigating BLV in dairy cattle have noted disease resistance or susceptibility, measured by a proviral load (PVL) associated with specific alleles of the bovine leukocyte antigen (BoLA) DRB3 gene. This study aims to investigate the associations between BoLA DRB3 alleles and BLV PVL in beef cattle. Samples were collected from 157 Midwest beef cows. BoLA DRB3 alleles were identified and compared with BLV PVL. One BoLA DRB3 allele, *026:01, was found to be associated with high PVL in relation to the average of the sampled population. In contrast, two alleles, *033:01 and *002:01, were found to be associated with low PVL. This study provides evidence of a relationship between BoLA DRB3 alleles and BLV PVL in US beef cows

The phenylacetic acid catabolic pathway regulates antibiotic and oxidative stress responses in Acinetobacter

The opportunistic pathogen Acinetobacter baumannii is responsible for a wide range of infections that are becoming increasingly difficult to treat due to extremely high rates of multidrug resistance. Acinetobacter\u27s pathogenic potential is thought to rely on a persist and resist strategy that facilitates its remarkable ability to survive under a variety of harsh conditions. Th

Phenotypic Selection of Dairy Cattle Infected with Bovine Leukemia Virus Demonstrates Immunogenetic Resilience through NGS-Based Genotyping of BoLA MHC Class II Genes

Characterization of the bovine leukocyte antigen (BoLA) DRB3 gene has shown that specific alleles associate with susceptibility or resilience to the progression of bovine leukemia virus (BLV), measured by proviral load (PVL). Through surveillance of multi-farm BLV eradication field trials, we observed differential phenotypes within seropositive cows that persist from months to years. We sought to develop a multiplex next-generation sequencing workflow (NGS-SBT) capable of genotyping 384 samples per run to assess the relationship between BLV phenotype and two BoLA genes. We utilized longitudinal results from milk ELISA screening and subsequent blood collections on seropositive cows for PVL determination using a novel BLV proviral load multiplex qPCR assay to phenotype the cows. Repeated diagnostic observations defined two distinct phenotypes in our study population, ELISA-positive cows that do not harbor detectable levels of provirus and those who do have persistent proviral loads. In total, 565 cows from nine Midwest dairy farms were selected for NGS-SBT, with 558 cows: 168 BLV susceptible (ELISA-positive/PVL-positive) and 390 BLV resilient (ELISA-positive/PVL-negative) successfully genotyped. Three BoLA-DRB3 alleles, including one novel allele, were shown to associate with disease resilience, *009:02, *044:01, and *048:02 were found at rates of 97.5%, 86.5%, and 90.3%, respectively, within the phenotypically resilient population. Alternatively, DRB3*015:01 and *027:03, both known to associate with disease progression, were found at rates of 81.1% and 92.3%, respectively, within the susceptible population. This study helps solidify the immunogenetic relationship between BoLA-DRB3 alleles and BLV infection status of these two phenotypic groupings of US dairy cattle

Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome

Abstract Background Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal’s diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data. Results Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host’s metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift. Conclusion We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity

Epithelial Smad4 Deletion Up-Regulates Inflammation and Promotes Inflammation-Associated CancerSummary

Background & Aims: Chronic inflammation is a predisposing condition for colorectal cancer. Many studies to date have focused on proinflammatory signaling pathways in the colon. Understanding the mechanisms that suppress inflammation, particularly in epithelial cells, is critical for developing therapeutic interventions. Here, we explored the roles of transforming growth factor β (TGFβ) family signaling through SMAD4 in colonic epithelial cells. Methods: The Smad4 gene was deleted specifically in adult murine intestinal epithelium. Colitis was induced by 3 rounds of dextran sodium sulfate in drinking water, after which mice were observed for up to 3 months. Nontransformed mouse colonocyte cell lines and colonoid cultures and human colorectal cancer cell lines were analyzed for responses to TGFβ1 and bone morphogenetic protein 2. Results: Dextran sodium sulfate treatment was sufficient to drive carcinogenesis in mice lacking colonic Smad4 expression, with resulting tumors bearing striking resemblance to human colitis–associated carcinoma. Loss of SMAD4 protein was observed in 48% of human colitis–associated carcinoma samples as compared with 19% of sporadic colorectal carcinomas. Loss of Smad4 increased the expression of inflammatory mediators within nontransformed mouse colon epithelial cells in vivo. In vitro analysis of mouse and human colonic epithelial cell lines and organoids indicated that much of this regulation was cell autonomous. Furthermore, TGFβ signaling inhibited the epithelial inflammatory response to proinflammatory cytokines. Conclusions: TGFβ suppresses the expression of proinflammatory genes in the colon epithelium, and loss of its downstream mediator, SMAD4, is sufficient to initiate inflammation-driven colon cancer. Transcript profiling: GSE100082. Keywords: TGFβ, Colitis-Associated Carcinoma, Tumor Necrosis Facto