The CreZOO (http://www.crezoo.org/) is the European virtual repository of Cre and other targeted conditional driver strains. These mice serve as tools for researchers to selectively ‘switch off’ gene expression in mouse models to examine gene function and disease pathology. CreZOO aims to capture and disseminate extant and new information on these Cre driver strains, such as genetic background and availability information, and details pertaining promoter, allele, inducibility and expression patterns, which are also presented. All transgenic strains carry detailed information according to MGI's official nomenclature, whereas their availability [e.g. live mice, cryopreserved embryos, sperm and embryonic stem (ES) cells] is clearly indicated with links to European and International databases and repositories (EMMA, MGI/IMSR, MMRRC, etc) and laboratories where the particular mouse strain is available together with the respective IDs. Each promoter/gene includes IDs and direct links to MGI, Entrez Gene, Ensembl, OMIM and RGD databases depending on their species origin, whereas allele information is presented with MGI IDs and active hyperlinks to redirect the user to the respective page in a new tab. The tissue/cell (special) and developmental (temporal) specificity expression patterns are clearly presented, whereas handling and genotyping details (in the form of documents or hyperlinks) together with all relevant publications are clearly presented with PMID(s) and direct PubMed links. CreZOO's design offers a user-friendly query interface and provides instant access to the list of conditional driver strains, promoters and inducibility details. Database access is free of charge and there are no registration requirements for data querying. CreZOO is being developed in the context of the CREATE consortium (http://www.creline.org/), a core of major European and international mouse database holders and research groups involved in conditional mutagenesis.

Database URL: http://www.crezoo.org/; alternative URL: http://www.e-mouse.org/

In this article, we describe the use of the BioMart data management system to provide integrated access to International Knockout Mouse Consortium (IKMC) data and other related mouse resources. The IKMC is currently mutating all mouse protein-coding genes in embryonic stem (ES) cells using gene targeting and gene trapping approaches. The BioMart portal allows researchers to identify and obtain IKMC knockout vectors, ES cells and mice for genes of interest. Gene annotation, expression, phenotype and disease data is also integrated from external BioMarts, allowing selection of IKMC products by a wide variety of criteria. These products are invaluable for researchers involved in the elucidation of gene function and the role of individual genes in human disease. Here, we describe these datasets in more detail and illustrate the functionality of the portal using several examples.

Database URL: http://www.knockoutmouse.org/mart

BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities.

Database URL: http://central.biomart.org.

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.

The International Knockout Mouse Consortium (IKMC) aims to mutate all protein-coding genes in the mouse using a combination of gene targeting and gene trapping in mouse embryonic stem (ES) cells and to make the generated resources readily available to the research community. The IKMC database and web portal (www.knockoutmouse.org) serves as the central public web site for IKMC data and facilitates the coordination and prioritization of work within the consortium. Researchers can access up-to-date information on IKMC knockout vectors, ES cells and mice for specific genes, and follow links to the respective repositories from which corresponding IKMC products can be ordered. Researchers can also use the web site to nominate genes for targeting, or to indicate that targeting of a gene should receive high priority. The IKMC database provides data to, and features extensive interconnections with, other community databases.

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources.

Database URL: http://www.casimir.org.uk/casimir_ddf

The laboratory mouse has become the organism of choice for discovering gene function and unravelling pathogenetic mechanisms of human diseases through the application of various functional genomic approaches. The resulting deluge of data has led to the deployment of numerous online resources and the concomitant need for formalized experimental descriptions, data standardization, database interoperability and integration, a need that has yet to be met. We present here the Mouse Resource Browser (MRB), a database of mouse databases that indexes 217 publicly available mouse resources under 22 categories and uses a standardised database description framework (the CASIMIR DDF) to provide information on their controlled vocabularies (ontologies and minimum information standards), and technical information on programmatic access and data availability. Focusing on interoperability and integration, MRB offers automatic generation of downloadable and re-distributable SOAP application-programming interfaces for resources that provide direct database access. MRB aims to provide useful information to both bench scientists, who can easily navigate and find all mouse related resources in one place, and bioinformaticians, who will be provided with interoperable resources containing data which can be mined and integrated.

Database URL: http://bioit.fleming.gr/mrb

Background

The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics.

Description

The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl.

Conclusions

Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.

XGAP, a software platform for the integration and analysis of genotype and phenotype data.

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.

Background

The integration of information present in many disparate biological databases represents a major challenge in biomedical research. To define the problems and needs, and to explore strategies for database integration in mouse functional genomics, we consulted the biologist user community and implemented solutions to two user-defined use-cases.

Results

We organised workshops, meetings and used a questionnaire to identify the needs of biologist database users in mouse functional genomics. As a result, two use-cases were developed that can be used to drive future designs or extensions of mouse databases. Here, we present the use-cases and describe some initial computational solutions for them. The application for the gene-centric use-case, "MUSIG-Gen" starts from a list of gene names and collects a wide range of data types from several distributed databases in a "shopping cart"-like manner. The iterative user-driven approach is a response to strongly articulated requests from users, especially those without computational biology backgrounds. The application for the phenotype-centric use-case, "MUSIG-Phen", is based on a similar concept and starting from phenotype descriptions retrieves information for associated genes.

Conclusion

The use-cases created, and their prototype software implementations should help to better define biologists' needs for database integration and may serve as a starting point for future bioinformatics solutions aimed at end-user biologists.

Ensembl (http://www.ensembl.org) integrates genomic information for a comprehensive set of chordate genomes with a particular focus on resources for human, mouse, rat, zebrafish and other high-value sequenced genomes. We provide complete gene annotations for all supported species in addition to specific resources that target genome variation, function and evolution. Ensembl data is accessible in a variety of formats including via our genome browser, API and BioMart. This year marks the tenth anniversary of Ensembl and in that time the project has grown with advances in genome technology. As of release 56 (September 2009), Ensembl supports 51 species including marmoset, pig, zebra finch, lizard, gorilla and wallaby, which were added in the past year. Major additions and improvements to Ensembl since our previous report include the incorporation of the human GRCh37 assembly, enhanced visualisation and data-mining options for the Ensembl regulatory features and continued development of our software infrastructure.

Following the technological advances that have enabled genome-wide analysis in most model organisms over the last decade, there has been unprecedented growth in genomic and post-genomic science with concomitant generation of an exponentially increasing volume of data and material resources. As a result, numerous repositories have been created to store and archive data, organisms and material, which are of substantial value to the whole community. Sustained access, facilitating re-use of these resources, is essential, not only for validation, but for re-analysis, testing of new hypotheses and developing new technologies/platforms. A common challenge for most data resources and biological repositories today is finding financial support for maintenance and development to best serve the scientific community. In this study we examine the problems that currently confront the data and resource infrastructure underlying the biomedical sciences. We discuss the financial sustainability issues and potential business models that could be adopted by biological resources and consider long term preservation issues within the context of mouse functional genomics efforts in Europe.

The laboratory mouse is the premier animal model for studying human disease and thousands of mutants have been identified or produced, most recently through gene-specific mutagenesis approaches. High throughput strategies by the International Knockout Mouse Consortium (IKMC) are producing mutants for all protein coding genes. Generating a knock-out line involves huge monetary and time costs so capture of both the data describing each mutant alongside archiving of the line for distribution to future researchers is critical. The European Mouse Mutant Archive (EMMA) is a leading international network infrastructure for archiving and worldwide provision of mouse mutant strains. It operates in collaboration with the other members of the Federation of International Mouse Resources (FIMRe), EMMA being the European component. Additionally EMMA is one of four repositories involved in the IKMC, and therefore the current figure of 1700 archived lines will rise markedly. The EMMA database gathers and curates extensive data on each line and presents it through a user-friendly website. A BioMart interface allows advanced searching including integrated querying with other resources e.g. Ensembl. Other resources are able to display EMMA data by accessing our Distributed Annotation System server. EMMA database access is publicly available at http://www.emmanet.org.

BioMart Central Portal (www.biomart.org) offers a one-stop shop solution to access a wide array of biological databases. These include major biomolecular sequence, pathway and annotation databases such as Ensembl, Uniprot, Reactome, HGNC, Wormbase and PRIDE; for a complete list, visit, http://www.biomart.org/biomart/martview. Moreover, the web server features seamless data federation making cross querying of these data sources in a user friendly and unified way. The web server not only provides access through a web interface (MartView), it also supports programmatic access through a Perl API as well as RESTful and SOAP oriented web services. The website is free and open to all users and there is no login requirement.

Background

Biologists need to perform complex queries, often across a variety of databases. Typically, each data resource provides an advanced query interface, each of which must be learnt by the biologist before they can begin to query them. Frequently, more than one data source is required and for high-throughput analysis, cutting and pasting results between websites is certainly very time consuming. Therefore, many groups rely on local bioinformatics support to process queries by accessing the resource's programmatic interfaces if they exist. This is not an efficient solution in terms of cost and time. Instead, it would be better if the biologist only had to learn one generic interface. BioMart provides such a solution.

Results

BioMart enables scientists to perform advanced querying of biological data sources through a single web interface. The power of the system comes from integrated querying of data sources regardless of their geographical locations. Once these queries have been defined, they may be automated with its "scripting at the click of a button" functionality. BioMart's capabilities are extended by integration with several widely used software packages such as BioConductor, DAS, Galaxy, Cytoscape, Taverna. In this paper, we describe all aspects of BioMart from a user's perspective and demonstrate how it can be used to solve real biological use cases such as SNP selection for candidate gene screening or annotation of microarray results.

Conclusion

BioMart is an easy to use, generic and scalable system and therefore, has become an integral part of large data resources including Ensembl, UniProt, HapMap, Wormbase, Gramene, Dictybase, PRIDE, MSD and Reactome. BioMart is freely accessible to use at .

Improved techniques for defining disease-gene location and evaluating the biological candidacy of regional transcripts will hasten disease-gene discovery.

Improved techniques for defining disease-gene location and evaluating the biological candidacy of regional transcripts will hasten disease-gene discovery.

Abstract

The ZNF198-FGFR1 fusion gene arises as a result of the t(8;13)(p11;q12) in the 8p11 myeloproliferative syndrome. To determine the transforming properties of this chimeric protein we transfected ZNF198-FGFR1 into the interleukin (IL)-3 dependent cell line Ba/F3. Growth factor independent subclones were obtained in which ZNF198-FGFR1, STAT1, and STAT5 were constitutively tyrosine phosphorylated, as determined by immunoprecipitation and Western blot analysis. To test the hypothesis that constitutive activation of ZNF198-FGFR1 tyrosine kinase activity is a result of self-association of the fusion protein, we in vitro transcribed and translated ZNF198-FGFR1 and a derivative construct, ZNF198-FGFR1 ΔC-myc, in which the C-terminal FGFR1 epitope was replaced by a c-myc tag. As expected, an anti-FGFR1 antibody immunoprecipitated ZNF198-FGFR1 but not ZNF198-FGFR1 ΔC-myc. However when both products were translated together, both were coimmunoprecipitated by anti-FGFR1 antisera. Similar results were obtained by using an anti-myc antibody and demonstrated a physical interaction between the two proteins. Analysis of COS-7 cells transfected with ZNF198-FGFR1 demonstrated that the fusion gene, in contrast to normal FGFR1, is located in the cytoplasm. We conclude that ZNF198-FGFR1 is a cytoplasmic protein that self-associates and has constitutive transformation activity. These data suggest that ZNF198-FGFR1 plays a primary role in the pathogenesis of the t(8;13) myeloproliferative syndrome and is the first report to implicate STAT proteins in FGFR1-mediated signaling.