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Visualizing spatial assay data in anatomical images is vital for understanding biological processes in cell, tissue, and organ organizations. Technologies requiring this functionality include traditional one-at-a-time assays, and bulk and single-cell omics experiments, including RNA-seq and proteomics. The spatialHeatmap software provides a series of powerful new methods for these needs, and allows users to work with adequately formatted anatomical images from public collections or custom images. It colors the spatial features (e.g. tissues) annotated in the images according to the measured or predicted abundance levels of biomolecules (e.g. mRNAs) using a color key. This core functionality of the package is called a spatial heatmap plot. Single-cell data can be co-visualized in composite plots that combine spatial heatmaps with embedding plots of high-dimensional data. The resulting spatial context information is essential for gaining insights into the tissue-level organization of single-cell data, or vice versa. Additional core functionalities include the automated identification of biomolecules with spatially selective abundance patterns and clusters of biomolecules sharing similar abundance profiles. To appeal to both non-expert and computational users, spatialHeatmap provides a graphical and a command-line interface, respectively. It is distributed as a free, open-source Bioconductor package (https://bioconductor.org/packages/spatialHeatmap) that users can install on personal computers, shared servers, or cloud systems.

The MYC oncogenic transcription factor is acetylated by the p300 and GCN5 histone acetyltransferases. The significance of MYC acetylation and the functions of specific acetylated lysine (AcK) residues have remained unclear. Here, we show that the major p300-acetylated K148(149) and K157(158) sites in human (or mouse) MYC and the main GCN5-acetylated K323 residue are reversibly acetylated in various malignant and nonmalignant cells. Oncogenic overexpression of MYC enhances its acetylation and alters the regulation of site-specific acetylation by proteasome and deacetylase inhibitors. Acetylation of MYC at different K residues differentially affects its stability in a cell type-dependent manner. Lysine-to-arginine substitutions indicate that although none of the AcK residues is required for MYC stimulation of adherent cell proliferation, individual AcK sites have gene-specific functions controlling select MYC-regulated processes in cell adhesion, contact inhibition, apoptosis, and/or metabolism and are required for the malignant cell transformation activity of MYC. Each AcK site is required for anchorage-independent growth of MYC-overexpressing cells in vitro, and both the AcK148(149) and AcK157(158) residues are also important for the tumorigenic activity of MYC transformed cells in vivo. The MYC AcK site-specific signaling pathways identified may offer new avenues for selective therapeutic targeting of MYC oncogenic activities.

The health benefits of switching from tobacco to electronic cigarettes (ECs) are neither confirmed nor well characterized. To address this problem, we used RNA-seq analysis to compare the nasal epithelium transcriptome from the following groups (n = 3 for each group): (1) former smokers who completely switched to second generation ECs for at least 6 months, (2) current tobacco cigarette smokers (CS), and (3) non-smokers (NS). Group three included one former cigarette smoker. The nasal epithelial biopsies from the EC users vs. NS had a higher number of differentially expressed genes (DEGs) than biopsies from the CS vs. NS and CS vs. EC sets (1817 DEGs total for the EC vs. NS, 407 DEGs for the CS vs. NS, and 116 DEGs for the CS vs. EC comparison). In the EC vs. NS comparison, enriched gene ontology terms for the downregulated DEGs included cilium assembly and organization, whereas gene ontologies for upregulated DEGs included immune response, keratinization, and NADPH oxidase. Similarly, ontologies for cilium movement were enriched in the downregulated DEGs for the CS vs. NS group. Reactome pathway analysis gave similar results and also identified keratinization and cornified envelope in the upregulated DEGs in the EC vs. NS comparison. In the CS vs. NS comparison, the enriched Reactome pathways for upregulated DEGs included biological oxidations and several metabolic processes. Regulator effects identified for the EC vs. NS comparison were inflammatory response, cell movement of phagocytes and degranulation of phagocytes. Disease Ontology Sematic Enrichment analysis identified lung disease, mouth disease, periodontal disease and pulmonary fibrosis in the EC vs. NS comparison. Squamous metaplasia associated markers, keratin 10, keratin 13 and involucrin, were increased in the EC vs. NS comparison. Our transcriptomic analysis showed that gene expression profiles associated with EC use are not equivalent to those from non-smokers. EC use may interfere with airway epithelium recovery by promoting increased oxidative stress, inhibition of ciliogenesis, and maintaining an inflammatory response. These transcriptomic alterations may contribute to the progression of diseases with chronic EC use.

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.

Aging is the dominant risk factor for most chronic diseases. Development of antiaging interventions offers the promise of preventing many such illnesses simultaneously. Cellular stress resistance is an evolutionarily conserved feature of longevity. Here, we identify compounds that induced resistance to the superoxide generator paraquat (PQ), the heavy metal cadmium (Cd), and the DNA alkylator methyl methanesulfonate (MMS). Some rescue compounds conferred resistance to a single stressor, while others provoked multiplex resistance. Induction of stress resistance in fibroblasts was predictive of longevity extension in a published large-scale longevity screen in Caenorhabditis elegans, although not in testing performed in worms and flies with a more restricted set of compounds. Transcriptomic analysis and genetic studies implicated Nrf2/SKN-1 signaling in stress resistance provided by two protective compounds, cardamonin and AEG 3482. Small molecules identified in this work may represent attractive tools to elucidate mechanisms of stress resistance in mammalian cells.

HOXA Transcript Antisense RNA, Myeloid-Specific 1 (HOTAIRM1) is a conserved long non-coding RNA (lncRNA) involved in myeloid and neural differentiation that is deregulated in acute myeloid leukemia and other cancers. Previous studies focused on the nuclear unspliced HOTAIRM1 transcript, however cytoplasmic splice variants exist whose roles have remained unknown. Here, we report novel functions of HOTAIRM1 in the kidney. HOTAIRM1 transcripts are induced during renal lineage differentiation of embryonic stem cells and required for expression of specific renal differentiation genes. We show that the major HOTAIRM1 transcript in differentiated cells is the spliced cytoplasmic HM1-3 isoform and that HM1-3 is downregulated in >90% of clear cell renal cell carcinomas (ccRCCs). Knockdown of HM1-3 in renal cells deregulates hypoxia-responsive and angiogenic genes, including ANGPTL4. Furthermore, HOTAIRM1 transcripts are downregulated by hypoxia-mimetic stress and knockdown of the cytoplasmic HM1-3 isoform in normoxic cells post-transcriptionally induces Hypoxia-Inducible Factor 1α (HIF1α) protein, a key activator of ANGPTL4. Our results demonstrate the pervasive downregulation of the specific HOTAIRM1 cytoplasmic isoform HM1-3 in ccRCC and suggest possible roles of HOTAIRM1 in kidney differentiation and suppression of HIF1-dependent angiogenic pathways.

Interventions meant to promote longevity and healthy aging have often been designed or observed to modulate very specific gene or protein targets. If there are naturally occurring genetic variants in such a target that affect longevity as well as the molecular function of that target (eg, the variants influence the expression of the target, acting as expression quantitative trait loci or eQTLs), this could support a causal relationship between the pharmacologic modulation of the target and longevity and thereby validate the target at some level. We considered the gene targets of many pharmacologic interventions hypothesized to enhance human longevity and explored how many variants there are in those targets that affect gene function (eg, as expression quantitative trait loci). We also determined whether variants in genes associated with longevity-related phenotypes affect gene function or are in linkage disequilibrium with variants that do, and whether pharmacologic studies point to compounds exhibiting activity against those genes. Our results are somewhat ambiguous, suggesting that integrating genetic association study results with functional genomic and pharmacologic studies is necessary to shed light on genetically mediated targets for longevity-enhancing drugs. Such integration will require more sophisticated data sets, phenotypic definitions, and bioinformatics approaches to be useful.

ImportanceNo previous studies have shown that acute inhalation of thirdhand smoke (THS) activates stress and survival pathways in the human nasal epithelium.ObjectiveTo evaluate gene expression in the nasal epithelium of nonsmoking women following acute inhalation of clean air and THS.Design, setting, and participantsNasal epithelium samples were obtained from participants in a randomized clinical trial (2011-2015) on the health effects of inhaled THS. In a crossover design, participants were exposed, head only, to THS and to conditioned, filtered air in a laboratory setting. The order of exposures was randomized and exposures were separated by at least 21 days. Ribonucleic acid was obtained from a subset of 4 healthy, nonsmoking women.ExposuresBy chance, women in the subset were randomized to receive clean air exposure first and THS exposure second. Exposures lasted 3 hours.Main outcomes and measuresDifferentially expressed genes were identified using RNA sequencing with a false-discovery rate less than 0.1.ResultsParticipants were 4 healthy, nonsmoking women aged 27 to 49 years (mean [SD] age, 42 [10.2] years) with no chronic diseases. A total of 389 differentially expressed genes were identified in nasal epithelium exposed to THS, while only 2 genes, which were not studied further, were affected by clean air. Enriched gene ontology terms associated with stress-induced mitochondrial hyperfusion were identified, such as respiratory electron transport chain (q = 2.84 × 10-3) and mitochondrial inner membrane (q = 7.21 × 10-6). Reactome pathway analysis identified terms associated with upregulation of DNA repair mechanisms, such as nucleotide excision repair (q = 1.05 × 10-2). Enrichment analyses using ingenuity pathway analysis identified canonical pathways related to stress-induced mitochondrial hyperfusion (eg, increased oxidative phosphorylation) (P = .001), oxidative stress (eg, glutathione depletion phase II reactions) (P = .04), and cell survival (z score = 5.026).Conclusions and relevanceThis study found that acute inhalation of THS caused cell stress that led to the activation of survival pathways. Some responses were consistent with stress-induced mitochondrial hyperfusion and similar to those demonstrated previously in vitro. These data may be valuable to physicians treating patients exposed to THS and may aid in formulating regulations for the remediation of THS-contaminated environments.

Extensive genome-wide analyses of deregulated gene expression have now been performed for many types of cancer. However, most studies have focused on deregulation at the gene-level, which may overlook the alterations of specific transcripts for a given gene. Clear cell renal cell carcinoma (ccRCC) is one of the best-characterized and most pervasive renal cancers, and ccRCCs are well-documented to have aberrant RNA processing. In the present study, we examine the extent of aberrant isoform-specific RNA expression by reporting a comprehensive transcript-level analysis, using the new kallisto-sleuth-RATs pipeline, investigating coding and non-coding differential transcript expression in ccRCC. We analyzed 50 ccRCC tumors and their matched normal samples from The Cancer Genome Altas datasets. We identified 7,339 differentially expressed transcripts and 94 genes exhibiting differential transcript isoform usage in ccRCC. Additionally, transcript-level coexpression network analyses identified vasculature development and the tricarboxylic acid cycle as the most significantly deregulated networks correlating with ccRCC progression. These analyses uncovered several uncharacterized transcripts, including lncRNAs FGD5-AS1 and AL035661.1, as potential regulators of the tricarboxylic acid cycle associated with ccRCC progression. As ccRCC still presents treatment challenges, our results provide a new resource of potential therapeutics targets and highlight the importance of exploring alternative methodologies in transcriptome-wide studies.

The potato aphid, Macrosiphum euphorbiae, is an important agricultural pest that causes economic losses to potato and tomato production. To establish the transcriptome for this aphid, RNA-Seq libraries constructed from aphids maintained on tomato plants were used in Illumina sequencing generating 52.6 million 75-105 bp paired-end reads. The reads were assembled using Velvet/Oases software with SEED preprocessing resulting in 22,137 contigs with an N50 value of 2,003bp. After removal of contigs from tomato host origin, 20,254 contigs were annotated using BLASTx searches against the non-redundant protein database from the National Center for Biotechnology Information (NCBI) as well as IntereProScan. This identified matches for 74% of the potato aphid contigs. The highest ranking hits for over 12,700 contigs were against the related pea aphid, Acyrthosiphon pisum. Gene Ontology (GO) was used to classify the identified M. euphorbiae contigs into biological process, cellular component and molecular function. Among the contigs, sequences of microbial origin were identified. Sixty five contigs were from the aphid bacterial obligate endosymbiont Buchnera aphidicola origin and two contigs had amino acid similarities to viruses. The latter two were named Macrosiphum euphorbiae virus 2 (MeV-2) and Macrosiphum euphorbiae virus 3 (MeV-3). The highest sequence identity to MeV-2 had the Dysaphis plantaginea densovirus, while to MeV-3 is the Hubei sobemo-like virus 49. Characterization of MeV-2 and MeV-3 indicated that both are transmitted vertically from adult aphids to nymphs. MeV-2 peptides were detected in the aphid saliva and only MeV-2 and not MeV-3 nucleic acids were detected inside tomato leaves exposed to virus-infected aphids. However, MeV-2 nucleic acids did not persist in tomato leaf tissues, after clearing the plants from aphids, indicating that MeV-2 is likely an aphid virus.

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Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p

The mosquito Aedes aegypti is a major vector of numerous viral diseases, because it requires a blood meal to facilitate egg development. The fat body, a counterpart of mammalian liver and adipose tissues, is the metabolic center, playing a key role in reproduction. Therefore, understanding of regulatory networks controlling its functions is critical, and the role of microRNAs (miRNAs) in the process is largely unknown. We aimed to explore miRNA expression and potential targets in the female fat body of Ae. aegypti, as well as their changes postblood meal (PBM). Small RNA library analysis revealed five unique miRNA patterns sequentially expressed at five sampled time points, likely responding to, and affecting, waves of upstream hormonal signals and gene expression in the same period. To link miRNA identities with downstream targets, transcriptome-wide mRNA 3' UTR interaction sites were experimentally determined at 72 h posteclosion and 24 h PBM through Argonaute 1 cross-linking and immunoprecipitation followed by high-throughput sequencing. Several target sites were validated by means of in vitro luciferase assays with wild-type and mutated 3' UTRs for six miRNA families. With established transgenic lines, consistent results were observed with spatiotemporal knockdown of miR-8 and luciferase assays. We further investigated miRNAs potentially regulating various physiological processes based on Clusters of Orthologous Groups functional categories. Hence, the present work comprehensively elucidated miRNA expression and target dynamics in the female mosquito fat body, providing a solid foundation for future functional studies of miRNA regulation during the gonadotrophic cycle.

This study presents an analysis of the small molecule bioactivity profiles across large quantities of diverse protein families represented in PubChem BioAssay. We compared the bioactivity profiles of FDA approved drugs to non-FDA approved compounds, and report several distinct patterns characteristic of the approved drugs. We found that a large fraction of the previously reported higher target promiscuity among FDA approved compounds, compared to non-FDA approved bioactives, was frequently due to cross-reactivity within rather than across protein families. We identified 804 potentially novel protein target candidates for FDA approved drugs, as well as 901 potentially novel target candidates with active non-FDA approved compounds, but no FDA approved drugs with activity against these targets. We also identified 486348 potentially novel compounds active against the same targets as FDA approved drugs, as well as 153402 potentially novel compounds active against targets without active FDA approved drugs. By quantifying the agreement among replicated screens, we estimated that more than half of these novel outcomes are reproducible. Using biclustering, we identified many dense clusters of FDA approved drugs with enriched activity against a common set of protein targets. We also report the distribution of compound promiscuity using a Bayesian statistical model, and report the sensitivity and specificity of two common methods for identifying promiscuous compounds. Aggregator assays exhibited greater accuracy in identifying highly promiscuous compounds, while PAINS substructures were able to identify a much larger set of "middle range" promiscuous compounds. Additionally, we report a large number of promiscuous compounds not identified as aggregators or PAINS. In summary, the results of this study represent a rich reference for selecting novel drug and target protein candidates, as well as for eliminating candidate compounds with unselective activities.

UNLABELLED: Primary infection with varicella-zoster virus (VZV), a neurotropic alphaherpesvirus, results in varicella. VZV establishes latency in the sensory ganglia and can reactivate later in life to cause herpes zoster. The relationship between VZV and its host during acute infection in the sensory ganglia is not well understood due to limited access to clinical specimens. Intrabronchial inoculation of rhesus macaques with simian varicella virus (SVV) recapitulates the hallmarks of VZV infection in humans. We leveraged this animal model to characterize the host-pathogen interactions in the ganglia during both acute and latent infection by measuring both viral and host transcriptomes on days postinfection (dpi) 3, 7, 10, 14, and 100. SVV DNA and transcripts were detected in sensory ganglia 3 dpi, before the appearance of rash. CD4 and CD8 T cells were also detected in the sensory ganglia 3 dpi. Moreover, lung-resident T cells isolated from the same animals 3 dpi also harbored SVV DNA and transcripts, suggesting that T cells may be responsible for trafficking SVV to the ganglia. Transcriptome sequencing (RNA-Seq) analysis showed that cessation of viral transcription 7 dpi coincides with a robust antiviral innate immune response in the ganglia. Interestingly, a significant number of genes that play a critical role in nervous system development and function remained downregulated into latency. These studies provide novel insights into host-pathogen interactions in the sensory ganglia during acute varicella and demonstrate that SVV infection results in profound and sustained changes in neuronal gene expression. IMPORTANCE: Many aspects of VZV infection of sensory ganglia remain poorly understood, due to limited access to human specimens and the fact that VZV is strictly a human virus. Infection of rhesus macaques with simian varicella virus (SVV), a homolog of VZV, provides a robust model of the human disease. Using this model, we show that SVV reaches the ganglia early after infection, most likely by T cells, and that the induction of a robust innate immune response correlates with cessation of virus transcription. We also report significant changes in the expression of genes that play an important role in neuronal function. Importantly, these changes persist long after viral replication ceases. Given the homology between SVV and VZV, and the genetic and physiological similarities between rhesus macaques and humans, our results provide novel insight into the interactions between VZV and its human host and explain some of the neurological consequences of VZV infection.

Varicella Zoster Virus (VZV) is the causative agent of varicella and herpes zoster. Although it is well established that VZV is transmitted via the respiratory route, the host-pathogen interactions during acute VZV infection in the lungs remain poorly understood due to limited access to clinical samples. To address these gaps in our knowledge, we leveraged a nonhuman primate model of VZV infection where rhesus macaques are intrabronchially challenged with the closely related Simian Varicella Virus (SVV). Acute infection is characterized by immune infiltration of the lung airways, a significant up-regulation of genes involved in antiviral-immunity, and a down-regulation of genes involved in lung development. This is followed by a decrease in viral loads and increased expression of genes associated with cell cycle and tissue repair. These data provide the first characterization of the host response required to control varicella virus replication in the lung and provide insight into mechanisms by which VZV infection can cause lung injury in an immune competent host.

BackgroundNext-generation sequencing (NGS) has revolutionized how research is carried out in many areas of biology and medicine. However, the analysis of NGS data remains a major obstacle to the efficient utilization of the technology, as it requires complex multi-step processing of big data demanding considerable computational expertise from users. While substantial effort has been invested on the development of software dedicated to the individual analysis steps of NGS experiments, insufficient resources are currently available for integrating the individual software components within the widely used R/Bioconductor environment into automated workflows capable of running the analysis of most types of NGS applications from start-to-finish in a time-efficient and reproducible manner.ResultsTo address this need, we have developed the R/Bioconductor package systemPipeR. It is an extensible environment for both building and running end-to-end analysis workflows with automated report generation for a wide range of NGS applications. Its unique features include a uniform workflow interface across different NGS applications, automated report generation, and support for running both R and command-line software on local computers and computer clusters. A flexible sample annotation infrastructure efficiently handles complex sample sets and experimental designs. To simplify the analysis of widely used NGS applications, the package provides pre-configured workflows and reporting templates for RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Additional workflow templates will be provided in the future.ConclusionssystemPipeR accelerates the extraction of reproducible analysis results from NGS experiments. By combining the capabilities of many R/Bioconductor and command-line tools, it makes efficient use of existing software resources without limiting the user to a set of predefined methods or environments. systemPipeR is freely available for all common operating systems from Bioconductor ( http://bioconductor.org/packages/devel/systemPipeR ).

Despite a large and rapidly growing body of small molecule bioactivity screens available in the public domain, systematic leverage of the data to assess target druggability and compound selectivity has been confounded by a lack of suitable cross-target analysis software. We have developed bioassayR, a computational tool that enables simultaneous analysis of thousands of bioassay experiments performed over a diverse set of compounds and biological targets. Unique features include support for large-scale cross-target analyses of both public and custom bioassays, generation of high throughput screening fingerprints (HTSFPs), and an optional preloaded database that provides access to a substantial portion of publicly available bioactivity data. bioassayR is implemented as an open-source R/Bioconductor package available from https://bioconductor.org/packages/bioassayR/ .

A virus with a large genome was identified in the transcriptome of the potato aphid (Macrosiphum euphorbiae) and was named Macrosiphum euphorbiae virus 1 (MeV-1). The MeV-1 genome is 22 780 nt in size, including 3' and 5' non-coding regions, with a single large ORF encoding a putative polyprotein of 7333 aa. The C-terminal region of the predicted MeV-1 polyprotein contained sequences with similarities to helicase, methyltransferase and RNA-dependent RNA polymerase (RdRp) motifs, while the N-terminal region lacked any motifs including structural proteins. Phylogenetic analysis of the helicase placed MeV-1 close to pestiviruses, while the RdRp region placed it close to pestiviruses and flaviviruses, suggesting MeV-1 has a positive-polarity ssRNA genome and is a member of the family Flaviviridae. Since the MeV-1 genome is predicted to contain a methyltransferase, a gene present typically in flaviviruses but not pestiviruses, MeV-1 is likely a member of the genus Flavivirus. MeV-1 was present in nymphal and adult stages of the aphid, aphid saliva and plant tissues fed upon by aphids. However, the virus was unable to multiply and spread in tomato plants. In addition, dsRNA, the replication intermediate of RNA viruses, was isolated from virus-infected M. euphorbiae and not from tomato plants infested with the aphid. Furthermore, nymphs laid without exposure to infected plants harboured the virus, indicating that MeV-1 is an aphid-infecting virus likely transmitted transovarially. The virus was present in M. euphorbiae populations from Europe but not from North America and was absent in all other aphid species tested.

The arthropod-specific juvenile hormone (JH) controls numerous essential functions. Its involvement in gene activation is known to be mediated by the transcription factor Methoprene-tolerant (Met), which turns on JH-controlled genes by directly binding to E-box-like motifs in their regulatory regions. However, it remains unclear how JH represses genes. We used the Aedes aegypti female mosquito, in which JH is necessary for reproductive maturation, to show that a repressor, Hairy, is required for the gene-repressive action of JH and Met. The RNA interference (RNAi) screen for Met and Hairy in the Aedes female fat body revealed a large cohort of Met- and Hairy-corepressed genes. Analysis of selected genes from this cohort demonstrated that they are repressed by JH, but RNAi of either Met or Hairy renders JH ineffective in repressing these genes in an in vitro fat-body culture assay. Moreover, this JH action was prevented by the addition of the translational inhibitor cycloheximide (CHX) to the culture, indicating the existence of an indirect regulatory hierarchy. The lack of Hairy protein in the CHX-treated tissue was verified using immunoblot analysis, and the upstream regions of Met/Hairy-corepressed genes were shown to contain common binding motifs that interact with Hairy. Groucho (gro) RNAi silencing phenocopied the effect of Hairy RNAi knockdown, indicating that it is involved in the JH/Met/Hairy hierarchy. Finally, the requirement of Hairy and Gro for gene repression was confirmed in a cell transfection assay. Thus, our study has established that Hairy and its cofactor Gro mediate the repressive function of JH and Met.

Several lines of evidence indicate that chronic alcohol use disorder leads to increased susceptibility to several viral and bacterial infections, whereas moderate alcohol consumption decreases the incidence of colds and improves immune responses to some pathogens. In line with these observations, we recently showed that heavy ethanol intake (average blood ethanol concentrations > 80 mg/dl) suppressed, whereas moderate alcohol consumption (blood ethanol concentrations < 50 mg/dl) enhanced, T and B cell responses to modified vaccinia Ankara vaccination in a nonhuman primate model of voluntary ethanol consumption. To uncover the molecular basis for impaired immunity with heavy alcohol consumption and enhanced immune response with moderate alcohol consumption, we performed a transcriptome analysis using PBMCs isolated on day 7 post-modified vaccinia Ankara vaccination, the earliest time point at which we detected differences in T cell and Ab responses. Overall, chronic heavy alcohol consumption reduced the expression of immune genes involved in response to infection and wound healing and increased the expression of genes associated with the development of lung inflammatory disease and cancer. In contrast, chronic moderate alcohol consumption upregulated the expression of genes involved in immune response and reduced the expression of genes involved in cancer. To uncover mechanisms underlying the alterations in PBMC transcriptomes, we profiled the expression of microRNAs within the same samples. Chronic heavy ethanol consumption altered the levels of several microRNAs involved in cancer and immunity and known to regulate the expression of mRNAs differentially expressed in our data set.

BackgroundNext-generation sequencing (NGS) has revolutionized how research is carried out in many areas of biology and medicine. However, the analysis of NGS data remains a major obstacle to the efficient utilization of the technology, as it requires complex multi-step processing of big data demanding considerable computational expertise from users. While substantial effort has been invested on the development of software dedicated to the individual analysis steps of NGS experiments, insufficient resources are currently available for integrating the individual software components within the widely used R/Bioconductor environment into automated workflows capable of running the analysis of most types of NGS applications from start-to-finish in a time-efficient and reproducible manner.ResultsTo address this need, we have developed the R/Bioconductor package systemPipeR. It is an extensible environment for both building and running end-to-end analysis workflows with automated report generation for a wide range of NGS applications. Its unique features include a uniform workflow interface across different NGS applications, automated report generation, and support for running both R and command-line software on local computers and computer clusters. A flexible sample annotation infrastructure efficiently handles complex sample sets and experimental designs. To simplify the analysis of widely used NGS applications, the package provides pre-configured workflows and reporting templates for RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Additional workflow templates will be provided in the future.ConclusionssystemPipeR accelerates the extraction of reproducible analysis results from NGS experiments. By combining the capabilities of many R/Bioconductor and command-line tools, it makes efficient use of existing software resources without limiting the user to a set of predefined methods or environments. systemPipeR is freely available for all common operating systems from Bioconductor ( http://bioconductor.org/packages/devel/systemPipeR ).

In multicellular organisms, development, growth and reproduction require coordinated expression of numerous functional and regulatory genes. Insects, in addition to being the most speciose animal group with enormous biological and economical significance, represent outstanding model organisms for studying regulation of synchronized gene expression due to their rapid development and reproduction. Disease-transmitting female mosquitoes have adapted uniquely for ingestion and utilization of the huge blood meal required for swift reproductive events to complete egg development within a 72-h period. We investigated the network of regulatory factors mediating sequential gene expression in the fat body, a multifunctional organ analogous to the vertebrate liver and adipose tissue, of the female Aedes aegypti mosquito. Transcriptomic and bioinformatics analyses revealed that ~7500 transcripts are differentially expressed in four sequential waves during the 72-h reproductive period. A combination of RNA-interference gene-silencing and in-vitro organ culture identified the major regulators for each of these waves. Amino acids (AAs) regulate the first wave of gene activation between 3 h and 12 h post-blood meal (PBM). During the second wave, between 12 h and 36 h, most genes are highly upregulated by a synergistic action of AAs, 20-hydroxyecdysone (20E) and the Ecdysone-Receptor (EcR). Between 36 h and 48 h, the third wave of gene activation-regulated mainly by HR3-occurs. Juvenile Hormone (JH) and its receptor Methoprene-Tolerant (Met) are major regulators for the final wave between 48 h and 72 h. Each of these key regulators also has repressive effects on one or more gene sets. Our study provides a better understanding of the complexity of the regulatory mechanisms related to temporal coordination of gene expression during reproduction. We have detected the novel function of 20E/EcR responsible for transcriptional repression. This study also reveals the previously unidentified large-scale effects of HR3 and JH/Met on transcriptional regulation during the termination of vitellogenesis and remodeling of the fat body.

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.

MotivationDe novo assemblies of genomes remain one of the most challenging applications in next-generation sequencing. Usually, their results are incomplete and fragmented into hundreds of contigs. Repeats in genomes and sequencing errors are the main reasons for these complications. With the rapidly growing number of sequenced genomes, it is now feasible to improve assemblies by guiding them with genomes from related species.ResultsHere we introduce AlignGraph, an algorithm for extending and joining de novo-assembled contigs or scaffolds guided by closely related reference genomes. It aligns paired-end (PE) reads and preassembled contigs or scaffolds to a close reference. From the obtained alignments, it builds a novel data structure, called the PE multipositional de Bruijn graph. The incorporated positional information from the alignments and PE reads allows us to extend the initial assemblies, while avoiding incorrect extensions and early terminations. In our performance tests, AlignGraph was able to substantially improve the contigs and scaffolds from several assemblers. For instance, 28.7-62.3% of the contigs of Arabidopsis thaliana and human could be extended, resulting in improvements of common assembly metrics, such as an increase of the N50 of the extendable contigs by 89.9-94.5% and 80.3-165.8%, respectively. In another test, AlignGraph was able to improve the assembly of a published genome (Arabidopsis strain Landsberg) by increasing the N50 of its extendable scaffolds by 86.6%. These results demonstrate AlignGraph's efficiency in improving genome assemblies by taking advantage of closely related references.Availability and implementationThe AlignGraph software can be downloaded for free from this site: https://github.com/baoe/AlignGraph.

Translational regulation contributes to plasticity in metabolism and growth that enables plants to survive in a dynamic environment. Here, we used the precise mapping of ribosome footprints (RFs) on mRNAs to investigate translational regulation under control and sublethal hypoxia stress conditions in seedlings of Arabidopsis thaliana. Ribosomes were obtained by differential centrifugation or immunopurification and were digested with RNase I to generate footprint fragments that were deep-sequenced. Comparison of RF number and position on genic regions with fragmented total and polysomal mRNA illuminated numerous aspects of posttranscriptional and translational control under both growth conditions. When seedlings were oxygen-deprived, the frequency of ribosomes at the start codon was reduced, consistent with a global decline in initiation of translation. Hypoxia-up-regulated gene transcripts increased in polysome complexes during the stress, but the number of ribosomes per transcript relative to normoxic conditions was not enhanced. On the other hand, many mRNAs with limited change in steady-state abundance had significantly fewer ribosomes but with an overall similar distribution under hypoxia, consistent with restriction of initiation rather than elongation of translation. RF profiling also exposed the inhibitory effect of upstream ORFs on the translation of downstream protein-coding regions under normoxia, which was further modulated by hypoxia. The data document translation of alternatively spliced mRNAs and expose ribosome association with some noncoding RNAs. Altogether, we present an experimental approach that illuminates prevalent and nuanced regulation of protein synthesis under optimal and energy-limiting conditions.

Infection with yellow fever virus (YFV), an explosively replicating flavivirus, results in viral hemorrhagic disease characterized by cardiovascular shock and multi-organ failure. Unvaccinated populations experience 20 to 50% fatality. Few studies have examined the pathophysiological changes that occur in humans during YFV infection due to the sporadic nature and remote locations of outbreaks. Rhesus macaques are highly susceptible to YFV infection, providing a robust animal model to investigate host-pathogen interactions. In this study, we characterized disease progression as well as alterations in immune system homeostasis, cytokine production and gene expression in rhesus macaques infected with the virulent YFV strain DakH1279 (YFV-DakH1279). Following infection, YFV-DakH1279 replicated to high titers resulting in viscerotropic disease with ∼72% mortality. Data presented in this manuscript demonstrate for the first time that lethal YFV infection results in profound lymphopenia that precedes the hallmark changes in liver enzymes and that although tissue damage was noted in liver, kidneys, and lymphoid tissues, viral antigen was only detected in the liver. These observations suggest that additional tissue damage could be due to indirect effects of viral replication. Indeed, circulating levels of several cytokines peaked shortly before euthanasia. Our study also includes the first description of YFV-DakH1279-induced changes in gene expression within peripheral blood mononuclear cells 3 days post-infection prior to any clinical signs. These data show that infection with wild type YFV-DakH1279 or live-attenuated vaccine strain YFV-17D, resulted in 765 and 46 differentially expressed genes (DEGs), respectively. DEGs detected after YFV-17D infection were mostly associated with innate immunity, whereas YFV-DakH1279 infection resulted in dysregulation of genes associated with the development of immune response, ion metabolism, and apoptosis. Therefore, WT-YFV infection is associated with significant changes in gene expression that are detectable before the onset of clinical symptoms and may influence disease progression and outcome of infection.

Wounding due to mechanical injury or insect feeding causes a wide array of damage to plant cells including cell disruption, desiccation, metabolite oxidation, and disruption of primary metabolism. In response, plants regulate a variety of genes and metabolic pathways to cope with injury. Tomato (Solanum lycopersicum) is a model for wound signaling but few studies have examined the comprehensive gene expression profiles in response to injury. A cross-species microarray approach using the TIGR potato 10-K cDNA array was analyzed for large-scale temporal (early and late) and spatial (locally and systemically) responses to mechanical wounding in tomato leaves. These analyses demonstrated that tomato regulates many primary and secondary metabolic pathways and this regulation is dependent on both timing and location. To determine if LAP-A, a known modulator of wound signaling, influences gene expression beyond the core of late wound-response genes, changes in RNAs from healthy and wounded Leucine aminopeptidase A-silenced (LapA-SI) and wild-type (WT) leaves were examined. While most of the changes in gene expression after wounding in LapA-SI leaves were similar to WT, overall responses were delayed in the LapA-SI leaves. Moreover, two pathogenesis-related 1 (PR-1c and PR-1a2) and two dehydrin (TAS14 and Dhn3) genes were negatively regulated by LAP-A. Collectively, this study has shown that tomato wound responses are complex and that LAP-A's role in modulation of wound responses extends beyond the well described late-wound gene core.

MotivationSimilarity clustering of next-generation sequences (NGS) is an important computational problem to study the population sizes of DNA/RNA molecules and to reduce the redundancies in NGS data. Currently, most sequence clustering algorithms are limited by their speed and scalability, and thus cannot handle data with tens of millions of reads.ResultsHere, we introduce SEED-an efficient algorithm for clustering very large NGS sets. It joins sequences into clusters that can differ by up to three mismatches and three overhanging residues from their virtual center. It is based on a modified spaced seed method, called block spaced seeds. Its clustering component operates on the hash tables by first identifying virtual center sequences and then finding all their neighboring sequences that meet the similarity parameters. SEED can cluster 100 million short read sequences in

BackgroundProfile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is the difficulty to pinpoint their much shorter functional sub-features, such as catalytically relevant sequence motifs in enzymes or ligand binding signatures of receptor proteins.ResultsTo identify these conserved motifs efficiently, we propose a method for extracting the most information-rich regions in protein families from their profile HMMs. The method was used here to predict a comprehensive set of sub-HMMs from the Pfam domain database. Cross-validations with the PROSITE and CSA databases confirmed the efficiency of the method in predicting most of the known functionally relevant motifs and residues. At the same time, 46,768 novel conserved regions could be predicted. The data set also allowed us to link at least 461 Pfam domains of known and unknown function by their common sub-HMMs. Finally, the sub-HMM method showed very promising results as an alternative search method for identifying proteins that share only short sequence similarities.ConclusionsSub-HMMs extend the application spectrum of profile HMMs to motif discovery. Their most interesting utility is the identification of the functionally relevant residues in proteins of known and unknown function. Additionally, sub-HMMs can be used for highly localized sequence similarity searches that focus on shorter conserved features rather than entire domains or global similarities. The motif data generated by this study is a valuable knowledge resource for characterizing protein functions in the future.

MotivationSimilarity searching and clustering of chemical compounds by structural similarities are important computational approaches for identifying drug-like small molecules. Most algorithms available for these tasks are limited by their speed and scalability, and cannot handle today's large compound databases with several million entries.ResultsIn this article, we introduce a new algorithm for accelerated similarity searching and clustering of very large compound sets using embedding and indexing (EI) techniques. First, we present EI-Search as a general purpose similarity search method for finding objects with similar features in large databases and apply it here to searching and clustering of large compound sets. The method embeds the compounds in a high-dimensional Euclidean space and searches this space using an efficient index-aware nearest neighbor search method based on locality sensitive hashing (LSH). Second, to cluster large compound sets, we introduce the EI-Clustering algorithm that combines the EI-Search method with Jarvis-Patrick clustering. Both methods were tested on three large datasets with sizes ranging from about 260 000 to over 19 million compounds. In comparison to sequential search methods, the EI-Search method was 40-200 times faster, while maintaining comparable recall rates. The EI-Clustering method allowed us to significantly reduce the CPU time required to cluster these large compound libraries from several months to only a few days.AvailabilitySoftware implementations and online services have been developed based on the methods introduced in this study. The online services provide access to the generated clustering results and ultra-fast similarity searching of the PubChem Compound database with subsecond response time.

MotivationSoftware applications for structural similarity searching and clustering of small molecules play an important role in drug discovery and chemical genomics. Here, we present the first open-source compound mining framework for the popular statistical programming environment R. The integration with a powerful statistical environment maximizes the flexibility, expandability and programmability of the provided analysis functions.ResultsWe discuss the algorithms and compound mining utilities provided by the R package ChemmineR. It contains functions for structural similarity searching, clustering of compound libraries with a wide spectrum of classification algorithms and various utilities for managing complex compound data. It also offers a wide range of visualization functions for compound clusters and chemical structures. The package is well integrated with the online ChemMine environment and allows bidirectional communications between the two services.AvailabilityChemmineR is freely available as an R package from the ChemMine project site: http://bioweb.ucr.edu/ChemMineV2/chemminer

MotivationThe prediction of biologically active compounds is of great importance for high-throughput screening (HTS) approaches in drug discovery and chemical genomics. Many computational methods in this area focus on measuring the structural similarities between chemical structures. However, traditional similarity measures are often too rigid or consider only global similarities between structures. The maximum common substructure (MCS) approach provides a more promising and flexible alternative for predicting bioactive compounds.ResultsIn this article, a new backtracking algorithm for MCS is proposed and compared to global similarity measurements. Our algorithm provides high flexibility in the matching process, and it is very efficient in identifying local structural similarities. To predict and cluster biologically active compounds more efficiently, the concept of basis compounds is proposed that enables researchers to easily combine the MCS-based and traditional similarity measures with modern machine learning techniques. Support vector machines (SVMs) are used to test how the MCS-based similarity measure and the basis compound vectorization method perform on two empirically tested datasets. The test results show that MCS complements the well-known atom pair descriptor-based similarity measure. By combining these two measures, our SVM-based model predicts the biological activities of chemical compounds with higher specificity and sensitivity.Supplementary informationSupplementary data are available at Bioinformatics online.

BackgroundReversible modification of proteins through the attachment of ubiquitin or ubiquitin-like modifiers is an essential post-translational regulatory mechanism in eukaryotes. The conjugation of ubiquitin or ubiquitin-like proteins has been demonstrated to play roles in growth, adaptation and homeostasis in all eukaryotes, with perturbation of ubiquitin-mediated systems associated with the pathogenesis of many human diseases, including cancer and neurodegenerative disorders.Methodology/principal findingsHere we describe the use of an HMM search of functional Pfam domains found in the key components of the ubiquitin-mediated pathway necessary to activate and reversibly modify target proteins in eight apicomplexan parasitic protozoa for which complete or late-stage genome projects exist. In parallel, the same search was conducted on five model organisms, single-celled and metazoans, to generate data to validate both the search parameters employed and aid paralog classification in Apicomplexa. For each of the 13 species investigated, a set of proteins predicted to be involved in the ubiquitylation pathway has been identified and demonstrates increasing component members of the ubiquitylation pathway correlating with organism and genome complexity. Sequence homology and domain architecture analyses facilitated prediction of apicomplexan-specific protein function, particularly those involved in regulating cell division during these parasite's complex life cycles.Conclusions/significanceThis study provides a comprehensive analysis of proteins predicted to be involved in the apicomplexan ubiquitin-mediated pathway. Given the importance of such pathway in a wide variety of cellular processes, our data is a key step in elucidating the biological networks that, in part, direct the pathogenicity of these parasites resulting in a massive impact on global health. Moreover, apicomplexan-specific adaptations of the ubiquitylation pathway may represent new therapeutic targets for much needed drugs against apicomplexan parasites.

Background: In spite of large intergenic spaces in plant and animal genomes, 7% to 30% of genes in the genomes encode overlapping cis-natural antisense transcripts (cis-NATs). The widespread occurrence of cis-NATs suggests an evolutionary advantage for this type of genomic arrangement. Experimental evidence for the regulation of two cis-NAT gene pairs by natural antisense transcripts-generated small interfering RNAs (nat-siRNAs) via the RNA interference (RNAi) pathway has been reported in Arabidopsis. However, the extent of siRNA-mediated regulation of cis-NAT genes is still unclear in any genome.Results: The hallmarks of RNAi regulation of NATs are 1) inverse regulation of two genes in a cis-NAT pair by environmental and developmental cues and 2) generation of siRNAs by cis-NAT genes. We examined Arabidopsis transcript profiling data from public microarray databases to identify cis-NAT pairs whose sense and antisense transcripts show opposite expression changes. A subset of the cis-NAT genes displayed negatively correlated expression profiles as well as inverse differential expression changes under at least one of the examined developmental stages or treatment conditions. By searching the Arabidopsis Small RNA Project (ASRP) and Massively Parallel Signature Sequencing (MPSS) small RNA databases as well as our stress-treated small RNA dataset, we found small RNAs that matched at least one gene in 646 pairs out of 1008 (64%) protein-coding cis-NAT pairs, which suggests that siRNAs may regulate the expression of many cis-NAT genes. 209 putative siRNAs have the potential to target more than one gene and half of these small RNAs could target multiple members of a gene family. Furthermore, the majority of the putative siRNAs within the overlapping regions tend to target only one transcript of a given NAT pair, which is consistent with our previous finding on salt- and bacteria-induced nat-siRNAs. In addition, we found that genes encoding plastid- or mitochondrion-targeted proteins are over-represented in the Arabidopsis cis-NATs and that 19% of sense and antisense partner genes of cis-NATs share at least one common Gene Ontology term, which suggests that they encode proteins with possible functional connection.Conclusion: The negatively correlated expression patterns of sense and antisense genes as well as the presence of siRNAs in many of the cis-NATs suggest that siRNA regulation of cis-NATs via the RNAi pathway is an important gene regulatory mechanism for at least a subgroup of cis-NATs in Arabidopsis.