Tissue Tropism in Host Transcriptional Response to Members of the Bovine Respiratory Disease Complex.

Bovine respiratory disease (BRD) is the most common infectious disease of beef and dairy cattle and is characterized by a complex infectious etiology that includes a variety of viral and bacterial pathogens. We examined the global changes in mRNA abundance in healthy lung and lung lesions and in the lymphoid tissues bronchial lymph node, retropharyngeal lymph node, nasopharyngeal lymph node and pharyngeal tonsil collected at the peak of clinical disease from beef cattle experimentally challenged with either bovine respiratory syncytial virus, infectious bovine rhinotracheitis, bovine viral diarrhea virus, Mannheimia haemolytica or Mycoplasma bovis. We identified signatures of tissue-specific transcriptional responses indicative of tropism in the coordination of host's immune tissue responses to infection by viral or bacterial infections. Furthermore, our study shows that this tissue tropism in host transcriptional response to BRD pathogens results in the activation of different networks of response genes. The differential crosstalk among genes expressed in lymphoid tissues was predicted to be orchestrated by specific immune genes that act as 'key players' within expression networks. The results of this study serve as a basis for the development of innovative therapeutic strategies and for the selection of cattle with enhanced resistance to BRD

QTL-mapping and genomic prediction for bovine respiratory disease in U.S. Holsteins using sequence imputation and feature selection

Background: National genetic evaluations for disease resistance do not exist, precluding the genetic improvement of cattle for these traits. We imputed BovineHD genotypes to whole genome sequence for 2703 Holsteins that were cases or controls for Bovine Respiratory Disease and sampled from either California or New Mexico to construct and compare genomic prediction models. The sequence variation reference dataset comprised variants called for 1578 animals from Run 5 of the 1000 Bull Genomes Project, including 450 Holsteins and 29 animals sequenced from this study population. Genotypes for 9,282,726 variants with minor allele frequencies ?5 percent were imputed and used to obtain genomic predictions in GEMMA using a Bayesian Sparse Linear Mixed Model. Results: Variation explained by markers increased from 13.6 percent using BovineHD data to 14.4 percent using imputed whole genome sequence data and the resolution of genomic regions detected as harbouring QTL substantially increased. Explained variation in the analysis of the combined California and New Mexico data was less than when data for each state were separately analysed and the estimated genetic correlation between risk of Bovine Respiratory Disease in California and New Mexico Holsteins was - 0.36. Consequently, genomic predictions trained using the data from one state did not accurately predict disease risk in the other state. To determine if a prediction model could be developed with utility in both states, we selected variants within genomic regions harbouring: 1) genes involved in the normal immune response to infection by pathogens responsible for Bovine Respiratory Disease detected by RNA-Seq analysis, and/or 2) QTL identified in the association analysis of the imputed sequence variants. The model based on QTL selected variants is biased but when trained in one state generated BRD risk predictions with positive accuracies in the other state. Conclusions: We demonstrate the utility of sequence-based and biology-driven model development for genomic selection. Disease phenotypes cannot be routinely recorded in most livestock species and the observed phenotypes may vary in their genomic architecture due to variation in the pathogen composition across environments. Elucidation of trait biology and genetic architecture may guide the development of prediction models with utility across breeds and environments

Results of survey of stakeholders regarding knowledge of and attitudes towards feed intake, efficiency and genetic improvement concepts

Individual animal feed efficiency plays a key role in the profitability and sustainability of the US beef industry. During the growing and finishing phase of production, a 10% improvement in feed efficiency has a two-fold greater impact on profit than a 10% increase in rate of gain (Fox et al., 2001). The traits that beef producers routinely record are outputs which determine the value of product sold and not the inputs defining the cost of beef production. The inability to routinely measure feed intake and feed efficiency on large numbers of cattle has precluded the efficient application of selection despite moderate heritabilities (h2 = 0.16-0.46; Archer et al., 1999). Feed costs in calf feeding and yearling finishing systems account for approximately 66% and 77% of costs, respectively (Anderson et al., 2005).Feed costs account for approximately 65% of total beef production costs. Of the metabolizable energy required from conception to consumption of a beef animal, 72% is utilized during the cow-calf segment of production while 28% of calories are utilized in the calf growing and finishing phases of production (Ferrell and Jenkins, 1982). Of the calories consumed in the cow-calf segment, more than half are used for maintenance which presents a large selection target

High-speed signal switching with a monolithic integrated p-i-n/amp/switch on indium phosphide

Operation of an optoelectronic integrated circuit which includes two p-i-ns, preamplifiers, 2 x 2 crosspoint .switch, and output buffers has been demonstrated. These circuits have been fabricated in semi-insulating 1nP:Fe substrates by vapor phase epitaxy and ion implantation using a planar horizontally integrated technology. Signals modulated at 150 MHz are shown to be switched at 15 MHz, with the circuits capable of detecting and passing data modulated at - 1 GHz

Identifying Archaeological Bone via Non-Destructive ZooMS and the Materiality of Symbolic Expression: Examples from Iroquoian Bone Points.

Today, practical, functional and symbolic choices inform the selection of raw materials for worked objects. In cases where we can discern the origin of worked bone, tooth, ivory and antler objects in the past, we assume that similar choices are being made. However, morphological species identification of worked objects is often impossible due to the loss of identifying characteristics during manufacture. Here, we describe a novel non-destructive ZooMS (Zooarchaeology by Mass Spectrometry) method which was applied to bone points from Pre-Contact St. Lawrence Iroquoian village sites in southern Quebec, Canada. The traditional ZooMS technique requires destructive analysis of a sample, which can be problematic when dealing with artefacts. Here we instead extracted proteins from the plastic bags in which the points had been stored. ZooMS analysis revealed hitherto unexpected species, notably black bear (Ursus americanus) and human (Homo sapiens sapiens), used in point manufacture. These surprising results (confirmed through genomic sequencing) highlight the importance of advancing biomolecular research in artefact studies. Furthermore, they unexpectedly and exceptionally allow us to identify and explore the tangible, material traces of the symbolic relationship between bears and humans, central to past and present Iroquoian cosmology and mythology

Genome-Wide Polymorphism and Comparative Analyses in the White-Tailed Deer (Odocoileus virginianus): A Model for Conservation Genomics

The white-tailed deer (Odocoileus virginianus) represents one of the most successful and widely distributed large mammal species within North America, yet very little nucleotide sequence information is available. We utilized massively parallel pyrosequencing of a reduced representation library (RRL) and a random shotgun library (RSL) to generate a complete mitochondrial genome sequence and identify a large number of putative single nucleotide polymorphisms (SNPs) distributed throughout the white-tailed deer nuclear and mitochondrial genomes. A SNP validation study designed to test specific classes of putative SNPs provides evidence for as many as 10,476 genome-wide SNPs in the current dataset. Based on cytogenetic evidence for homology between cow (Bos taurus) and white-tailed deer chromosomes, we demonstrate that a divergent genome may be used for estimating the relative distribution and density of de novo sequence contigs as well as putative SNPs for species without draft genome assemblies. Our approach demonstrates that bioinformatic tools developed for model or agriculturally important species may be leveraged to support next-generation research programs for species of biological, ecological and evolutionary importance. We also provide a functional annotation analysis for the de novo sequence contigs assembled from white-tailed deer pyrosequencing reads, a mitochondrial phylogeny involving 13,722 nucleotide positions for 10 unique species of Cervidae, and a median joining haplotype network as a putative representation of mitochondrial evolution in O. virginianus. The results of this study are expected to provide a detailed template enabling genome-wide sequence-based studies of threatened, endangered or conservationally important non-model organisms