Identification of multiple transcription factor genes potentially involved in the development of electrosensory versus mechanosensory lateral line organs.

In electroreceptive jawed vertebrates, embryonic lateral line placodes give rise to electrosensory ampullary organs as well as mechanosensory neuromasts. Previous reports of shared gene expression suggest that conserved mechanisms underlie electroreceptor and mechanosensory hair cell development and that electroreceptors evolved as a transcriptionally related "sister cell type" to hair cells. We previously identified only one transcription factor gene, Neurod4, as ampullary organ-restricted in the developing lateral line system of a chondrostean ray-finned fish, the Mississippi paddlefish (Polyodon spathula). The other 16 transcription factor genes we previously validated in paddlefish were expressed in both ampullary organs and neuromasts. Here, we used our published lateral line organ-enriched gene-set (arising from differential bulk RNA-seq in late-larval paddlefish), together with a candidate gene approach, to identify 25 transcription factor genes expressed in the developing lateral line system of a more experimentally tractable chondrostean, the sterlet (Acipenser ruthenus, a small sturgeon), and/or that of paddlefish. Thirteen are expressed in both ampullary organs and neuromasts, consistent with conservation of molecular mechanisms. Seven are electrosensory-restricted on the head (Irx5, Irx3, Insm1, Sp5, Satb2, Mafa and Rorc), and five are the first-reported mechanosensory-restricted transcription factor genes (Foxg1, Sox8, Isl1, Hmx2 and Rorb). However, as previously reported, Sox8 is expressed in ampullary organs as well as neuromasts in a catshark (Scyliorhinus canicula), suggesting the existence of lineage-specific differences between cartilaginous and ray-finned fishes. Overall, our results support the hypothesis that ampullary organs and neuromasts develop via largely conserved transcriptional mechanisms, and identify multiple transcription factors potentially involved in the formation of electrosensory versus mechanosensory lateral line organs.

Help biocurators to maximize the reach of your data.

Curated scientific databases catalogue and amplify research findings to maximize their reach. Authors should write their papers with this in mind, ensuring that data are accurate, easy to extract, and presented in standardized formats.

COSMIC: a curated database of somatic variants and clinical data for cancer.

The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.

HumanMine: advanced data searching, analysis and cross-species comparison.

HumanMine (www.humanmine.org) is an integrated database of human genomics and proteomics data that provides a powerful interface to support sophisticated exploration and analysis of data compiled from experimental, computational and curated data sources. Built using the InterMine data integration platform, HumanMine includes genes, proteins, pathways, expression levels, Single nucleotide polymorphism (SNP), diseases and more, integrated into a single searchable database. HumanMine promotes integrative analysis, a powerful approach in modern biology that allows many sources of evidence to be analysed together. The data can be accessed through a user-friendly web interface as well as a powerful, scriptable web service Application programming interface (API) to allow programmatic access to data. The web interface includes a useful identifier resolution system, sophisticated query options and interactive results tables that enable powerful exploration of data, including data summaries, filtering, browsing and export. A set of graphical analysis tools provide a rich environment for data exploration including statistical enrichment of sets of genes or other biological entities. HumanMine can be used for integrative multistaged analysis that can lead to new insights and uncover previously unknown relationships. Database URL: https://www.humanmine.org.

Insights into olfactory ensheathing cell development from a laser-microdissection and transcriptome-profiling approach.

Olfactory ensheathing cells (OECs) are neural crest-derived glia that ensheath bundles of olfactory axons from their peripheral origins in the olfactory epithelium to their central targets in the olfactory bulb. We took an unbiased laser microdissection and differential RNA-seq approach, validated by in situ hybridization, to identify candidate molecular mechanisms underlying mouse OEC development and differences with the neural crest-derived Schwann cells developing on other peripheral nerves. We identified 25 novel markers for developing OECs in the olfactory mucosa and/or the olfactory nerve layer surrounding the olfactory bulb, of which 15 were OEC-specific (that is, not expressed by Schwann cells). One pan-OEC-specific gene, Ptprz1, encodes a receptor-like tyrosine phosphatase that blocks oligodendrocyte differentiation. Mutant analysis suggests Ptprz1 may also act as a brake on OEC differentiation, and that its loss disrupts olfactory axon targeting. Overall, our results provide new insights into OEC development and the diversification of neural crest-derived glia.

InterMineR: an R package for InterMine databases.

SUMMARY: InterMineR is a package designed to provide a flexible interface between the R programming environment and biological databases built using the InterMine platform. The package offers access to the flexible query builder and the library of term enrichment tools of the InterMine framework, as well as interoperability with other Bioconductor packages. This facilitates automation of data retrieval tasks as well as downstream analysis with existing statistical tools in the R environment. AVAILABILITY AND IMPLEMENTATION: InterMineR is free and open source, released under the LGPL licence and available from the Bioconductor project and Github (https://bioconductor.org/packages/release/bioc/html/InterMineR.html, https://github.com/intermine/interMineR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The InterMine Android app: Cross-organism genomic data in your pocket.

InterMine is a data integration and analysis software system that has been used to create both inter-connected and stand-alone biological databases for the analysis of large and complex biological data sets. Together, the InterMine databases provide access to extensive data across multiple organisms. To provide more convenient access to these data from Android mobile devices, we have developed the InterMine app, an application that can be run on any Android mobile phone or tablet. The InterMine app provides a single interface for data access, search and exploration of the InterMine databases. It can be used to retrieve information on genes and gene lists, and their relatives across species. Simple searches can be used to access a range of data about a specific gene, while links to the InterMine databases provide access to more detailed report pages and gene list analysis tools. The InterMine app thus facilitates rapid exploration of genes across multiple organisms and kinds of data.

Cross-organism analysis using InterMine.

InterMine is a data integration warehouse and analysis software system developed for large and complex biological data sets. Designed for integrative analysis, it can be accessed through a user-friendly web interface. For bioinformaticians, extensive web services as well as programming interfaces for most common scripting languages support access to all features. The web interface includes a useful identifier look-up system, and both simple and sophisticated search options. Interactive results tables enable exploration, and data can be filtered, summarized, and browsed. A set of graphical analysis tools provide a rich environment for data exploration including statistical enrichment of sets of genes or other entities. InterMine databases have been developed for the major model organisms, budding yeast, nematode worm, fruit fly, zebrafish, mouse, and rat together with a newly developed human database. Here, we describe how this has facilitated interoperation and development of cross-organism analysis tools and reports. InterMine as a data exploration and analysis tool is also described. All the InterMine-based systems described in this article are resources freely available to the scientific community.

InterMine: extensive web services for modern biology.

InterMine (www.intermine.org) is a biological data warehousing system providing extensive automatically generated and configurable RESTful web services that underpin the web interface and can be re-used in many other applications: to find and filter data; export it in a flexible and structured way; to upload, use, manipulate and analyze lists; to provide services for flexible retrieval of sequence segments, and for other statistical and analysis tools. Here we describe these features and discuss how they can be used separately or in combinations to support integrative and comparative analysis.

BioJS DAGViewer: A reusable JavaScript component for displaying directed graphs.

SUMMARY: The DAGViewer BioJS component is a reusable JavaScript component made available as part of the BioJS project and intended to be used to display graphs of structured data, with a particular emphasis on Directed Acyclic Graphs (DAGs). It enables users to embed representations of graphs of data, such as ontologies or phylogenetic trees, in hyper-text documents (HTML). This component is generic, since it is capable (given the appropriate configuration) of displaying any kind of data that is organised as a graph. The features of this component which are useful for examining and filtering large and complex graphs are described. AVAILABILITY: http://github.com/alexkalderimis/dag-viewer-biojs; http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.8303.

metabolicMine: an integrated genomics, genetics and proteomics data warehouse for common metabolic disease research.

Common metabolic and endocrine diseases such as diabetes affect millions of people worldwide and have a major health impact, frequently leading to complications and mortality. In a search for better prevention and treatment, there is ongoing research into the underlying molecular and genetic bases of these complex human diseases, as well as into the links with risk factors such as obesity. Although an increasing number of relevant genomic and proteomic data sets have become available, the quantity and diversity of the data make their efficient exploitation challenging. Here, we present metabolicMine, a data warehouse with a specific focus on the genomics, genetics and proteomics of common metabolic diseases. Developed in collaboration with leading UK metabolic disease groups, metabolicMine integrates data sets from a range of experiments and model organisms alongside tools for exploring them. The current version brings together information covering genes, proteins, orthologues, interactions, gene expression, pathways, ontologies, diseases, genome-wide association studies and single nucleotide polymorphisms. Although the emphasis is on human data, key data sets from mouse and rat are included. These are complemented by interoperation with the RatMine rat genomics database, with a corresponding mouse version under development by the Mouse Genome Informatics (MGI) group. The web interface contains a number of features including keyword search, a library of Search Forms, the QueryBuilder and list analysis tools. This provides researchers with many different ways to analyse, view and flexibly export data. Programming interfaces and automatic code generation in several languages are supported, and many of the features of the web interface are available through web services. The combination of diverse data sets integrated with analysis tools and a powerful query system makes metabolicMine a valuable research resource. The web interface makes it accessible to first-time users, whereas the Application Programming Interface (API) and web services provide convenient data access and tools for bioinformaticians. metabolicMine is freely available online at http://www.metabolicmine.org Database URL: http://www.metabolicmine.org.

InterMOD: integrated data and tools for the unification of model organism research.

Model organisms are widely used for understanding basic biology, and have significantly contributed to the study of human disease. In recent years, genomic analysis has provided extensive evidence of widespread conservation of gene sequence and function amongst eukaryotes, allowing insights from model organisms to help decipher gene function in a wider range of species. The InterMOD consortium is developing an infrastructure based around the InterMine data warehouse system to integrate genomic and functional data from a number of key model organisms, leading the way to improved cross-species research. So far including budding yeast, nematode worm, fruit fly, zebrafish, rat and mouse, the project has set up data warehouses, synchronized data models, and created analysis tools and links between data from different species. The project unites a number of major model organism databases, improving both the consistency and accessibility of comparative research, to the benefit of the wider scientific community.

InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data.

SUMMARY: InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. AVAILABILITY: Freely available from http://www.intermine.org under the LGPL license. CONTACT: g.micklem@gen.cam.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

modMine: flexible access to modENCODE data.

In an effort to comprehensively characterize the functional elements within the genomes of the important model organisms Drosophila melanogaster and Caenorhabditis elegans, the NHGRI model organism Encyclopaedia of DNA Elements (modENCODE) consortium has generated an enormous library of genomic data along with detailed, structured information on all aspects of the experiments. The modMine database (http://intermine.modencode.org) described here has been built by the modENCODE Data Coordination Center to allow the broader research community to (i) search for and download data sets of interest among the thousands generated by modENCODE; (ii) access the data in an integrated form together with non-modENCODE data sets; and (iii) facilitate fine-grained analysis of the above data. The sophisticated search features are possible because of the collection of extensive experimental metadata by the consortium. Interfaces are provided to allow both biologists and bioinformaticians to exploit these rich modENCODE data sets now available via modMine.

The modENCODE Data Coordination Center: lessons in harvesting comprehensive experimental details.

The model organism Encyclopedia of DNA Elements (modENCODE) project is a National Human Genome Research Institute (NHGRI) initiative designed to characterize the genomes of Drosophila melanogaster and Caenorhabditis elegans. A Data Coordination Center (DCC) was created to collect, store and catalog modENCODE data. An effective DCC must gather, organize and provide all primary, interpreted and analyzed data, and ensure the community is supplied with the knowledge of the experimental conditions, protocols and verification checks used to generate each primary data set. We present here the design principles of the modENCODE DCC, and describe the ramifications of collecting thorough and deep metadata for describing experiments, including the use of a wiki for capturing protocol and reagent information, and the BIR-TAB specification for linking biological samples to experimental results. modENCODE data can be found at http://www.modencode.org.

FlyMine: an integrated database for Drosophila and Anopheles genomics.

FlyMine is a data warehouse that addresses one of the important challenges of modern biology: how to integrate and make use of the diversity and volume of current biological data. Its main focus is genomic and proteomics data for Drosophila and other insects. It provides web access to integrated data at a number of different levels, from simple browsing to construction of complex queries, which can be executed on either single items or lists.

Whole-genome microarrays of fission yeast: characteristics, accuracy, reproducibility, and processing of array data.

BACKGROUND: The genome of the fission yeast Schizosaccharomyces pombe has recently been sequenced, setting the stage for the post-genomic era of this increasingly popular model organism. We have built fission yeast microarrays, optimised protocols to improve array performance, and carried out experiments to assess various characteristics of microarrays. RESULTS: We designed PCR primers to amplify specific probes (180-500 bp) for all known and predicted fission yeast genes, which are printed in duplicate onto separate regions of glass slides together with control elements (approximately 13,000 spots/slide). Fluorescence signal intensities depended on the size and intragenic position of the array elements, whereas the signal ratios were largely independent of element properties. Only the coding strand is covalently linked to the slides, and our array elements can discriminate transcriptional direction. The microarrays can distinguish sequences with up to 70% identity, above which cross-hybridisation contributes to the signal intensity. We tested the accuracy of signal ratios and measured the reproducibility of array data caused by biological and technical factors. Because the technical variability is lower, it is best to use samples prepared from independent biological experiments to obtain repeated measurements with swapping of fluorochromes to prevent dye bias. We also developed a script that discards unreliable data and performs a normalization to correct spatial artefacts. CONCLUSIONS: This paper provides data for several microarray properties that are rarely measured. The results define critical parameters for microarray design and experiments and provide a framework to optimise and interpret array data. Our arrays give reproducible and accurate expression ratios with high sensitivity. The scripts for primer design and initial data processing as well as primer sequences and detailed protocols are available from our website.

Global transcriptional responses of fission yeast to environmental stress.

We explored transcriptional responses of the fission yeast Schizosaccharomyces pombe to various environmental stresses. DNA microarrays were used to characterize changes in expression profiles of all known and predicted genes in response to five stress conditions: oxidative stress caused by hydrogen peroxide, heavy metal stress caused by cadmium, heat shock caused by temperature increase to 39 degrees C, osmotic stress caused by sorbitol, and DNA damage caused by the alkylating agent methylmethane sulfonate. We define a core environmental stress response (CESR) common to all, or most, stresses. There was a substantial overlap between CESR genes of fission yeast and the genes of budding yeast that are stereotypically regulated during stress. CESR genes were controlled primarily by the stress-activated mitogen-activated protein kinase Sty1p and the transcription factor Atf1p. S. pombe also activated gene expression programs more specialized for a given stress or a subset of stresses. In general, these "stress-specific" responses were less dependent on the Sty1p mitogen-activated protein kinase pathway and may involve specific regulatory factors. Promoter motifs associated with some of the groups of coregulated genes were identified. We compare and contrast global regulation of stress genes in fission and budding yeasts and discuss evolutionary implications.

The transcriptional program of meiosis and sporulation in fission yeast.

Sexual reproduction requires meiosis to produce haploid gametes, which in turn can fuse to regenerate a diploid organism. We have studied the transcriptional program that drives this developmental process in Schizosaccharomyces pombe using DNA microarrays. Here we show that hundreds of genes are regulated in successive waves of transcription that correlate with major biological events of meiosis and sporulation. Each wave is associated with specific promoter motifs. Clusters of neighboring genes (mostly close to telomeres) are co-expressed early in the process, which reflects a more global control of these genes. We find that two Atf-like transcription factors are essential for the expression of late genes and formation of spores, and identify dozens of potential Atf target genes. Comparison with the meiotic program of the distantly related Saccharomyces cerevisiae reveals an unexpectedly small shared meiotic transcriptome, suggesting that the transcriptional regulation of meiosis evolved independently in both species.