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Background: Breast (mammary) cancers in human (BC) and canine (CMT) patients share clinical, pathological, and molecular similarities that suggest dogs may be a useful translational model. Many cancers, including BC, shed exosomes that contain microRNAs (miRs) into the microenvironment and circulation, and these may represent biomarkers of metastasis and tumor phenotype., Methods: Three normal canine mammary epithelial cell (CMEC) cultures and 5 CMT cell lines were grown in serum-free media. Exosomes were isolated from culture media by ultracentrifugation then profiled by transmission electron microscopy, dynamic light scattering, and Western blot. Exosomal small RNA was deep-sequenced on an Illumina HiSeq2500 sequencer and validated by qRT-PCR. In silico bioinformatic analysis was carried out to determine microRNA gene and pathway targets., Results: CMEC and CMT cell lines shed round, "cup-shaped" exosomes approximately 150-200 nm, and were immunopositive for exosomal marker CD9. Deep-sequencing averaged ~ 15 million reads/sample. Three hundred thirty-eight unique miRs were detected, with 145 having > ±1.5-fold difference between one or more CMT and CMEC samples. Gene ontology analysis revealed that the upregulated miRs in this exosomal population regulate a number of relevant oncogenic networks. Several miRNAs including miR-18a, miR-19a and miR-181a were predicted in silico to target the canine estrogen receptor (ESR1α)., Conclusions: CMEC and CMT cells shed exosomes in vitro that contain differentially expressed miRs. CMT exosomal RNA expresses a limited number of miRs that are up-regulated relative to CMEC, and these are predicted to target biologically relevant hormone receptors and oncogenic pathways. These results may inform future studies of circulating exosomes and the utility of miRs as biomarkers of breast cancer in women and dogs.

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus . Our results provide insight into pigment phenotypes in pythons.

Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

Objective: To evaluate the opinions of medical cannabis (MC) users on the effects of Cannabis indica vs. those of Cannabis sativa on conditions and symptoms through an online survey., Design: Survey of 95 non-randomly assigned MC users. A two-sided chi-square test followed by Bonferroni post hoc multiple comparison and Fisher exact test were used to determine correlations. The Cronbach α was used to determine internal consistency., Setting: Announcements on 13 MC websites with links to SurveyMonkey.com., Participants: Self-identified MC users., Intervention: Web survey., Outcome Measures: Species effects were compared regarding health symptoms, conditions, purpose, route, and trust in product label., Results: Trust in the purity, the route of administration, or the purpose (recreational vs. medicinal) did not differ between the two species. A preference for C. indica was statistically significant for pain management (p=0.001), helping with sedation (p=0.015), and sleep (p<0.001). C. sativa was preferred for euphoria (p<0.001) and enhancing energy (p=0.022). The conditions reaching statistical significance for C. indica preference were: nonmigraine headaches (p=0.042), glaucoma (p=0.036), neuropathy (p=0.024), spasticity (p=0.048), seizures (p=0.031), insomnia (p<0.001), and joint pain (p=0.048). For C. sativa, no conditions reached significance. The MC websites' descriptions of effects that agreed with the survey results are listed. Some conditions had very few respondents. The internal consistency/reliability (Cronbach α) was adequate for the condition scale but not for the symptom survey., Conclusion: In this anonymous Web survey, which had limitations, the two species had different effect associations on symptoms and conditions, possibly because of ingredient differences. Future surveys and subsequent prospective definitive trials are needed to confirm the findings.

Background: The feline genome is valuable to the veterinary and model organism genomics communities because the cat is an obligate carnivore and a model for endangered felids. The initial public release of the Felis catus genome assembly provided a framework for investigating the genomic basis of feline biology. However, the entire set of protein coding genes has not been elucidated., Results: We identified and characterized 1227 protein coding feline sequences, of which 913 map to public sequences and 314 are novel. These sequences have been deposited into NCBI's genbank database and complement public genomic resources by providing additional protein coding sequences that fill in some of the gaps in the feline genome assembly. Through functional and comparative genomic analyses, we gained an understanding of the role of these sequences in feline development, nutrition and health. Specifically, we identified 104 orthologs of human genes associated with Mendelian disorders. We detected negative selection within sequences with gene ontology annotations associated with intracellular trafficking, cytoskeleton and muscle functions. We detected relatively less negative selection on protein sequences encoding extracellular networks, apoptotic pathways and mitochondrial gene ontology annotations. Additionally, we characterized feline cDNA sequences that have mouse orthologs associated with clinical, nutritional and developmental phenotypes. Together, this analysis provides an overview of the value of our cDNA sequences and enhances our understanding of how the feline genome is similar to, and different from other mammalian genomes., Conclusions: The cDNA sequences reported here expand existing feline genomic resources by providing high-quality sequences annotated with comparative genomic information providing functional, clinical, nutritional and orthologous gene information.

Background: Papillomaviruses (PVs) are a group of small, non-encapsulated, species-specific DNA viruses that have been detected in a variety of mammalian and avian species including humans, canines and felines. PVs cause lesions in the skin and mucous membranes of the host and after persistent infection, a subset of PVs can cause tumors such as cervical malignancies and head and neck squamous cell carcinoma in humans. PVs from several species have been isolated and their genomes have been sequenced, thereby increasing our understanding of the mechanism of viral oncogenesis and allowing for the development of molecular assays for the detection of PV infection. In humans, molecular testing for PV DNA is used to identify patients with persistent infections at risk for developing cervical cancer. In felids, PVs have been isolated and sequenced from oral papillomatous lesions of several wild species including bobcats, Asian lions and snow leopards. Since a number of wild felids are endangered, PV associated disease is a concern and there is a need for molecular tools that can be used to further study papillomavirus in these species., Results: We used the sequence of the snow leopard papillomavirus UuPV1 to develop a PCR strategy to amplify viral DNA from samples obtained from captive animals. We designed primer pairs that flank the E6 and E7 viral oncogenes and amplify two DNA fragments encompassing these genes. We detected viral DNA for E6 and E7 in genomic DNA isolated from saliva, but not in paired blood samples from snow leopards. We verified the identity of these PCR products by restriction digest and DNA sequencing. The sequences of the PCR products were 100% identical to the published UuPV1 genome sequence., Conclusions: We developed a PCR assay to detect papillomavirus in snow leopards and amplified viral DNA encompassing the E6 and E7 oncogenes specifically in the saliva of animals. This assay could be utilized for the molecular investigation of papillomavirus in snow leopards using saliva, thereby allowing the detection of the virus in the anatomical site where oral papillomatous lesions develop during later stages of infection and disease development.

Problem-based learning (PBL) creates an atmosphere in which veterinary students must take responsibility for their own education. Unlike a traditional curriculum where students receive discipline-specific information by attending formal lectures, PBL is designed to elicit self-directed, student-centered learning such that each student determines (1) what he/she does not know (learning issues), (2) what he/she needs to learn, (3) how he/she will learn it, and (4) what resources he/she will use. One of the biggest challenges facing students in a PBL curriculum is efficient time management while pursuing learning issues. Bioinformatics resources, such as the PubMatrix literature-mining tool, allow access to tremendous amounts of information almost instantaneously. To accelerate student-centered learning it is necessary to include resources that enhance the rate at which students can process biomedical information. Unlike using the PubMed interface directly, the PubMatrix tool enables users to automate queries, allowing up to 1,000 distinct PubMed queries to be executed per single PubMatrix submission. Users may submit multiple PubMatrix queries per session, resulting in the ability to execute tens of thousands of PubMed queries in a single day. The intuitively organized results, which remain accessible from PubMatrix user accounts, enable students to rapidly assimilate and process hundreds of thousands of individual publication records as they relate to the student's specific learning issues and query terms. Subsequently, students can explore substantially more of the biomedical publication landscape per learning issue and spend a greater fraction of their time actively engaged in resolving their learning issues.

The size complexity of the human genome has been traditionally viewed as an obstacle that frustrates efforts aimed at identifying the genetic correlates of complex human phenotypes. As such complex phenotypes are attributed to the combined action of numerous genomic loci, attempts to identify the underlying multi-locus interactions may produce a combinatorial sum of false positives that drown out the real signal. Faced with such grim prospects for successfully identifying the genetic basis of complex phenotypes, many geneticists simply disregard epistatic interactions altogether. However, the emerging picture from systems biology is that the cellular programs encoded by the genome utilize nested signaling hierarchies to integrate a number of loosely coupled, semiautonomous, and functionally distinct genetic networks. The current view of these modules is that connections encoding inter-module signaling are relatively sparse, while the gene-to-gene (protein-to-protein) interactions within a particular module are typically denser. We believe that each of these modules is encoded by a finite set of discontinuous, sequence-specific, genomic intervals that are functionally linked to association rules, which correlate directly to features in the environment. Furthermore, because these environmental association rules have evolved incrementally over time, we explore theoretical models of cellular evolution to better understand the role of evolution in genomic complexity. Specifically, we present a conceptual framework for (1) reducing genomic complexity by partitioning the genome into subsets composed of functionally distinct genetic modules and (2) improving the selection of coding region SNPs, which results in an increased probability of identifying functionally relevant SNPs. Additionally, we introduce the notion of 'genomic closure,' which provides a quantitative measure of how functionally insulated a specific genetic module might be from the influence of the rest of the genome. We suggest that the development and use of theoretical models can provide insight into the nature of biological systems and may lead to significant improvements in computational algorithms designed to reduce the complexity of the human genome.

Both the prototypic tricyclic antidepressant imipramine (IMI) and the herbal product St John's wort (SJW) can be effective in the treatment of major depressive disorder. We studied hypothalamic gene expression in rats treated with SJW or IMI to test the hypothesis that chronic antidepressant treatment by various classes of drugs results in shared patterns of gene expression that may underlie their therapeutic effects. Individual hypothalami were hybridized to individual Affymetrix chips; we studied three arrays per group treatment. We constructed 95% confidence intervals for expression fold change for genes present in at least one treatment condition and we considered genes to be differentially expressed if they had a confidence interval excluding 1 (or -1) and had absolute difference in expression value of 10 or greater. SJW treatment differentially regulated 66 genes and expression sequence tags (ESTs) and IMI treatment differentially regulated 74 genes and ESTs. We found six common transcripts in response to both treatments. The likelihood of this occurring by chance is 1.14 x 10(-23). These transcripts are relevant to two molecular machines, namely the ribosomes and microtubules, and one cellular organelle, the mitochondria. Both treatments also affected different genes that are part of the same cell function processes, such as glycolytic pathways and synaptic function. We identified single-nucleotide polymorphisms in the human orthologs of genes regulated both treatments, as those genes may be novel candidates for pharmacogenetic studies. Our data support the hypothesis that chronic antidepressant treatment by drugs of various classes may result in a common, final pathway of changes in gene expression in a discrete brain region.