Expression Atlas update--a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments.

Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of 'baseline' expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful 'contrasts', i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user

GEORAC: an RNA-seq Atlas Constructor for the Gene Expression Omnibus

The meteoric rise of next-generation sequencing technologies over the past 15 years has resulted in a voluminous amount of data generated by modern biological and clinical studies. RNA sequencing, colloquially referred to as RNA-Seq, is a next-generation approach capable of surveying and quantifying whole organism transcriptomes. RNA-Seq methods are valued over microarray assays for their ability to avoid cross-hybridization signal noise, to quantify gene or transcript expression without assay-specific upper limits, to natively provide single-nucleotide genomic resolution, and to allow for de novo transcriptome assemblies. Many thousands of RNA-Seq studies have been published over the past seven years, and a significant area of bioinformatics research has focused on the creation of atlases that aggregate RNA-Seq results. These atlases are crucially useful for surveying trends in gene expression across published studies, for inspecting potentially contentious claims made by novel or prior work, and for synthesizing future research directions. The Expression Atlas currently serves as the canonical example for an RNA-Seq atlas and presents results from over 3,000 studies across numerous model research organisms. An issue with the Expression Atlas is that it forcibly applies a uniform secondary re-analysis pipeline to each RNA-Seq study incorporated within its database; this approach presents a conceptual challenge to studies whose results have been generated and published using established, well-tested workflows. Thus, there exists a critical need to provide for construction of RNA-Seq atlases that precisely reflect original results presented within the literature, and the primary objective of this dissertation is to provide a workflow that allows for transparent, reproducible construction of RNA-Seq atlases from study meta- and expression data housed within the National Center for Biomedical Information’s Gene Expression Omnibus (GEO). The challenge of this goal is exacerbated by the highly flexible design of GEO, which allows researchers to define novel metadata attributes and values at will and to submit expression results in virtually any format. Following an introductory background into modern genomics and RNA-Seq, the second chapter of this work presents GEOMP, a metadata parser and relational database constructor for the Gene Expression Omnibus. The subsequent third chapter describes GEOMP2, an in-place augmentation of GEOMP that provides further atomization and loading of sample-specific characteristics tags; this chapter significantly presents results from a pilot study surveying bioinformatics methods reproducibility across the zebrafish, mouse, and human research communities using metadata parsed and output by GEOMP2. Chapter four details GEORGET, a pipeline designed to rehabilitate, translate, and load expression data pulled from GEO into the relational database store constructed by GEOMP2. Chapter five concludes with discussion of future directions needed to expand and improve upon the current GEORAC workflow and the associated methods reproducibility study

A genomic analysis and transcriptomic atlas of gene expression in Psoroptes ovis reveals feeding- and stage-specific patterns of allergen expression

Background: Psoroptic mange, caused by infestation with the ectoparasitic mite, Psoroptes ovis, is highly contagious, resulting in intense pruritus and represents a major welfare and economic concern for the livestock industry Worldwide. Control relies on injectable endectocides and organophosphate dips, but concerns over residues, environmental contamination, and the development of resistance threaten the sustainability of this approach, highlighting interest in alternative control methods. However, development of vaccines and identification of chemotherapeutic targets is hampered by the lack of P. ovis transcriptomic and genomic resources. Results: Building on the recent publication of the P. ovis draft genome, here we present a genomic analysis and transcriptomic atlas of gene expression in P. ovis revealing feeding- and stage-specific patterns of gene expression, including novel multigene families and allergens. Network-based clustering revealed 14 gene clusters demonstrating either single- or multi-stage specific gene expression patterns, with 3075 female-specific, 890 male-specific and 112, 217 and 526 transcripts showing larval, protonymph and tritonymph specific-expression, respectively. Detailed analysis of P. ovis allergens revealed stage-specific patterns of allergen gene expression, many of which were also enriched in "fed" mites and tritonymphs, highlighting an important feeding-related allergenicity in this developmental stage. Pair-wise analysis of differential expression between life-cycle stages identified patterns of sex-biased gene expression and also identified novel P. ovis multigene families including known allergens and novel genes with high levels of stage-specific expression. Conclusions: The genomic and transcriptomic atlas described here represents a unique resource for the acarid-research community, whilst the OrcAE platform makes this freely available, facilitating further community-led curation of the draft P. ovis genome

Ortho2ExpressMatrix—a web server that interprets cross-species gene expression data by gene family information

<p>Abstract</p> <p>Background</p> <p>The study of gene families is pivotal for the understanding of gene evolution across different organisms and such phylogenetic background is often used to infer biochemical functions of genes. Modern high-throughput experiments offer the possibility to analyze the entire transcriptome of an organism; however, it is often difficult to deduct functional information from that data.</p> <p>Results</p> <p>To improve functional interpretation of gene expression we introduce Ortho2ExpressMatrix, a novel tool that integrates complex gene family information, computed from sequence similarity, with comparative gene expression profiles of two pre-selected biological objects: gene families are displayed with two-dimensional matrices. Parameters of the tool are object type (two organisms, two individuals, two tissues, etc.), type of computational gene family inference, experimental meta-data, microarray platform, gene annotation level and genome build. Family information in Ortho2ExpressMatrix bases on computationally different protein family approaches such as EnsemblCompara, InParanoid, SYSTERS and Ensembl Family. Currently, respective all-against-all associations are available for five species: human, mouse, worm, fruit fly and yeast. Additionally, microRNA expression can be examined with respect to miRBase or TargetScan families. The visualization, which is typical for Ortho2ExpressMatrix, is performed as matrix view that displays functional traits of genes (differential expression) as well as sequence similarity of protein family members (BLAST e-values) in colour codes. Such translations are intended to facilitate the user's perception of the research object.</p> <p>Conclusions</p> <p>Ortho2ExpressMatrix integrates gene family information with genome-wide expression data in order to enhance functional interpretation of high-throughput analyses on diseases, environmental factors, or genetic modification or compound treatment experiments. The tool explores differential gene expression in the light of orthology, paralogy and structure of gene families up to the point of ambiguity analyses. Results can be used for filtering and prioritization in functional genomic, biomedical and systems biology applications. The web server is freely accessible at <url>http://bioinf-data.charite.de/o2em/cgi-bin/o2em.pl</url>.</p

WormBase 2012: more genomes, more data, new website

Since its release in 2000, WormBase (http://www.wormbase.org) has grown from a small resource focusing on a single species and serving a dedicated research community, to one now spanning 15 species essential to the broader biomedical and agricultural research fields. To enhance the rate of curation, we have automated the identification of key data in the scientific literature and use similar methodology for data extraction. To ease access to the data, we are collaborating with journals to link entities in research publications to their report pages at WormBase. To facilitate discovery, we have added new views of the data, integrated large-scale datasets and expanded descriptions of models for human disease. Finally, we have introduced a dramatic overhaul of the WormBase website for public beta testing. Designed to balance complexity and usability, the new site is species-agnostic, highly customizable, and interactive. Casual users and developers alike will be able to leverage the public RESTful application programming interface (API) to generate custom data mining solutions and extensions to the site. We report on the growth of our database and on our work in keeping pace with the growing demand for data, efforts to anticipate the requirements of users and new collaborations with the larger science community

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3′-UTR GeneChips), genome-wide protein–DNA binding assays and protein–protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions

Gramene 2016: comparative plant genomics and pathway resources

Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to approximately 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials

Tomato Functional Genomics Database: a comprehensive resource and analysis package for tomato functional genomics

Tomato Functional Genomics Database (TFGD) provides a comprehensive resource to store, query, mine, analyze, visualize and integrate large-scale tomato functional genomics data sets. The database is functionally expanded from the previously described Tomato Expression Database by including metabolite profiles as well as large-scale tomato small RNA (sRNA) data sets. Computational pipelines have been developed to process microarray, metabolite and sRNA data sets archived in the database, respectively, and TFGD provides downloads of all the analyzed results. TFGD is also designed to enable users to easily retrieve biologically important information through a set of efficient query interfaces and analysis tools, including improved array probe annotations as well as tools to identify co-expressed genes, significantly affected biological processes and biochemical pathways from gene expression data sets and miRNA targets, and to integrate transcript and metabolite profiles, and sRNA and mRNA sequences. The suite of tools and interfaces in TFGD allow intelligent data mining of recently released and continually expanding large-scale tomato functional genomics data sets. TFGD is available at http://ted.bti.cornell.edu