Search

We report an update of the Hymenoptera Genome Database (HGD; http://HymenopteraGenome.org), a genomic database of hymenopteran insect species. The number of species represented in HGD has nearly tripled, with fifty-eight hymenopteran species, including twenty bees, twenty-three ants, eleven wasps and four sawflies. With a reorganized website, HGD continues to provide the HymenopteraMine genomic data mining warehouse and JBrowse/Apollo genome browsers integrated with BLAST. We have computed Gene Ontology (GO) annotations for all species, greatly enhancing the GO annotation data gathered from UniProt with more than a ten-fold increase in the number of GO-annotated genes. We have also generated orthology datasets that encompass all HGD species and provide orthologue clusters for fourteen taxonomic groups. The new GO annotation and orthology data are available for searching in HymenopteraMine, and as bulk file downloads.

Background High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook. Results We describe the MultiOmics Explainer, a new tool within the Pathway Tools software suite that leverages what is known about an organism’s metabolic and regulatory network to suggest explanations for the results of omics experiments. Querying a database such as EcoCyc, the MultiOmics Explainer searches the organism’s network of metabolic reactions, transporters, cofactors, enzyme substrate-level activation and inhibition relationships, and transcriptional and translational regulation relationships to identify paths of influence among input genes, proteins and metabolites. Results are presented in a combined metabolic and regulatory diagram. We present several examples of explanations generated for associations found in the Escherichia coli literature. Conclusions The MultiOmics Explainer is a valuable tool that helps researchers understand and interpret the results of their omics experiments in the context of what is known about an organism’s metabolic and regulatory network. It showcases the rich set of computational inferences that can be drawn from a database such as EcoCyc that encodes a diverse range of biological interactions. Electronic supplementary material The online version of this article (10.1186/s12859-019-2971-6) contains supplementary material, which is available to authorized users.

Taxonomic and functional research of microorganisms has increasingly relied upon genome-based data and methods. As the depository of the Global Catalogue of Microorganisms (GCM) 10K prokaryotic type strain sequencing project, Global Catalogue of Type Strain (gcType) has published 1049 type strain genomes sequenced by the GCM 10K project which are preserved in global culture collections with a valid published status. Additionally, the information provided through gcType includes >12 000 publicly available type strain genome sequences from GenBank incorporated using quality control criteria and standard data annotation pipelines to form a high-quality reference database. This database integrates type strain sequences with their phenotypic information to facilitate phenotypic and genotypic analyses. Multiple formats of cross-genome searches and interactive interfaces have allowed extensive exploration of the database's resources. In this study, we describe web-based data analysis pipelines for genomic analyses and genome-based taxonomy, which could serve as a one-stop platform for the identification of prokaryotic species. The number of type strain genomes that are published will continue to increase as the GCM 10K project increases its collaboration with culture collections worldwide. Data of this project is shared with the International Nucleotide Sequence Database Collaboration. Access to gcType is free at http://gctype.wdcm.org/.

Pseudocohnilembus persalinus, a unicellular ciliated protozoan, is one of commonest facultative pathogens. We sequenced the macronuclear genome of P. persalinus in 2015, which provided new insights into its pathogenicity. Here, we present the P. persalinus genome database (PPGD) ( http://ciliates.ihb.ac.cn/database/home/#pp ), the first genome database for the scuticociliatosis pathogens. PPGD integrates P. persalinus macronuclear genomic and transcriptomic data, including genome sequence, transcript, gene expression data, and gene annotation, as well as relevant information on its biology, morphology and taxonomy. The database also provides functions for visualizing, analyzing, and downloading the data. PPGD is a useful resource for studying scuticociliates or scuticociliatosis. We will continue to update the PPGD by integrating more data and aim to integrate the PPGD with other ciliate databases to build a comprehensive ciliate genome database.

The ginseng (Panax ginseng C.A. Meyer) is a perennial herbaceous plant that has been used in traditional oriental medicine for thousands of years. Ginsenosides, which have significant pharmacological effects on human health, are the foremost bioactive constituents in this plant. Having realized the importance of this plant to humans, an integrated omics resource becomes indispensable to facilitate genomic research, molecular breeding and pharmacological study of this herb. The first draft genome sequences of P. ginseng cultivar “Chunpoong” were reported recently. Here, using the draft genome, transcriptome, and functional annotation datasets of P. ginseng, we have constructed the Ginseng Genome Database http://ginsengdb.snu.ac.kr /, the first open-access platform to provide comprehensive genomic resources of P. ginseng. The current version of this database provides the most up-to-date draft genome sequence (of approximately 3000 Mbp of scaffold sequences) along with the structural and functional annotations for 59,352 genes and digital expression of genes based on transcriptome data from different tissues, growth stages and treatments. In addition, tools for visualization and the genomic data from various analyses are provided. All data in the database were manually curated and integrated within a user-friendly query page. This database provides valuable resources for a range of research fields related to P. ginseng and other species belonging to the Apiales order as well as for plant research communities in general. Ginseng genome database can be accessed at http://ginsengdb.snu.ac.kr /.

Applying next-generation sequencing (NGS) technologies to species of agricultural interest has the potential to accelerate the understanding and exploration of genetic resources. The storage, availability and maintenance of huge quantities of NGS-generated data remains a major challenge. The PeachVar-DB portal, available at http://hpc-bioinformatics.cineca.it/peach, is an open-source catalog of genetic variants present in peach (Prunus persica L. Batsch) and wild-related species of Prunus genera, annotated from 146 samples publicly released on the Sequence Read Archive (SRA). We designed a user-friendly web-based interface of the database, providing search tools to retrieve single nucleotide polymorphism (SNP) and InDel variants, along with useful statistics and information. PeachVar-DB results are linked to the Genome Database for Rosaceae (GDR) and the Phytozome database to allow easy access to other external useful plant-oriented resources. In order to extend the genetic diversity covered by the PeachVar-DB further, and to allow increasingly powerful comparative analysis, we will progressively integrate newly released data.

Euplotes, a ciliated protozoan, is a useful unicellular model organism. Studies on Euplotes have provided excellent insights into various basic biological principles. We have recently sequenced the macronuclear genome of the common freshwater species Euplotes octocarinatus to provide novel insights into Euplotes genetics and molecular biology. In this study, we present the E. octocarinatus Genome Database (EOGD), a functional annotation and analysis platform for the global study of the Euplotes genome. EOGD includes macronuclear genomic and transcriptomic data, predicted gene models, coding sequences, protein sequences, and functional annotations. The GBrowser and BLAST tools are embedded in EOGD to enable the search, visualization and analysis of E. octocarinatus genomic and transcriptomic data. EOGD is a useful resource for the research community, particularly for researchers who conduct genome-scale analysis and molecular biology studies of Euplotes or other ciliates. EOGD will be continuously updated to integrate more datasets and analytical tools. EOGD is freely available at http://ciliates.ihb.ac.cn/database/home/#eo .

Studying Candida biology requires access to genomic sequence data in conjunction with experimental information that together provide functional context to genes and proteins, and aid in interpreting newly generated experimental data. The Candida Genome Database (CGD) curates the Candida literature, and integrates functional information about Candida genes and their products with a set of analysis tools that facilitate searching for sets of genes and exploring their biological roles. This chapter describes how the various types of information available at CGD can be searched, retrieved, and analyzed. Starting with the guided tour of the CGD Home page and Locus Summary page, this unit shows how to navigate the various assemblies of the C. albicans genome, how to use Gene Ontology tools to make sense of large-scale data, and how to access the microarray data archived at CGD, as well as visualize high-throughput sequencing data through the use of JBrowse.

The effectiveness of lantibiotics against MDR pathogens and the progression of agents MU1140, NAI-107, NVB302 and duramycin into pre-clinical and clinical trials have highlighted their potential in the fight against bacterial resistance. The number of known lantibiotics and knowledge of their biosynthetic pathways has increased in recent years due to higher quality genomic data being delivered by next generation sequencing technologies combined with the development of specific genome mining tools, enabling the prediction of lantibiotic clusters. Areas covered: In this review, the author describes how the increase of high quality genomic data has increased the discovery of novel lantibiotics. Expert opinion: Novel apparatus such as the iChip enabling the isolation of uncultable bacteria will undoubtedly increase the identification rate of novel antimicrobial peptides including lantibiotics. The ability to then assess the lantibiotic clusters via recombinant production or synthesis using a high throughput method is one of the next challenges for developing these agents into the clinical environment.

The Israeli National and Ethnic Mutation database ( http://server.goldenhelix.org/israeli ) was launched in September 2006 on the ETHNOS software to include clinically relevant genomic variants reported among Jewish and Arab Israeli patients. In 2016, the database was reviewed and corrected according to ClinVar ( https://www.ncbi.nlm.nih.gov/clinvar ) and ExAC ( http://exac.broadinstitute.org ) database entries. The present article summarizes some key aspects from the development and continuous update of the database over a 10-year period, which could serve as a paradigm of successful database curation for other similar resources. In September 2016, there were 2444 entries in the database, 890 among Jews, 1376 among Israeli Arabs, and 178 entries among Palestinian Arabs, corresponding to an ~4× data content increase compared to when originally launched. While the Israeli Arab population is much smaller than the Jewish population, the number of pathogenic variants causing recessive disorders reported in the database is higher among Arabs (934) than among Jews (648). Nevertheless, the number of pathogenic variants classified as founder mutations in the database is smaller among Arabs (175) than among Jews (192). In 2016, the entire database content was compared to that of other databases such as ClinVar and ExAC. We show that a significant difference in the percentage of pathogenic variants from the Israeli genetic database that were present in ExAC was observed between the Jewish population (31.8%) and the Israeli Arab population (20.6%). The Israeli genetic database was launched in 2006 on the ETHNOS software and is available online ever since. It allows querying the database according to the disorder and the ethnicity; however, many other features are not available, in particular the possibility to search according to the name of the gene. In addition, due to the technical limitations of the previous ETHNOS software, new features and data are not included in the present online version of the database and upgrade is currently ongoing.

The Candida Genome Database (CGD, http://www.candidagenome.org/) is a freely available online resource that provides gene, protein and sequence information for multiple Candida species, along with web-based tools for accessing, analyzing and exploring these data. The goal of CGD is to facilitate and accelerate research into Candida pathogenesis and biology. The CGD Web site is organized around Locus pages, which display information collected about individual genes. Locus pages have multiple tabs for accessing different types of information; the default Summary tab provides an overview of the gene name, aliases, phenotype and Gene Ontology curation, whereas other tabs display more in-depth information, including protein product details for coding genes, notes on changes to the sequence or structure of the gene and a comprehensive reference list. Here, in this update to previous NAR Database articles featuring CGD, we describe a new tab that we have added to the Locus page, entitled the Homology Information tab, which displays phylogeny and gene similarity information for each locus.

Modern biomedical research depends critically on access to databases that house and disseminate genetic, genomic, molecular, and cell biological knowledge. Even as the explosion of available genome sequences and associated genome-scale data continues apace, the sustainability of professionally maintained biological databases is under threat due to policy changes by major funding agencies. Here, we focus on model organism databases to demonstrate the myriad ways in which biological databases not only act as repositories but actively facilitate advances in research. We present data that show that reducing financial support to model organism databases could prove to be not just scientifically, but also economically, unsound.

Integration of multiple genomic maps provides a higher density of markers and greater genome coverage, which not only facilitates the identification and positioning of QTLs and candidate genes, but it also provides a basic structure for the genome sequence assembly. However, the diversity in markers and populations used in individual mapping studies limits the ability to fully integrate the available data. By concentrating on marker orders rather than marker distances, published map data could be used to produce a comprehensive reference map (CRM) that includes a majority of known markers with optimally estimated order of those markers across the genome. In this study, a tetraploid cotton genome-wide CRM was constructed from 28 public cotton genetic maps. The initial CRM contained 7,424 markers and represented over 93% of the combined mapping information from the 28 individual maps. The current output is stored and displayed through CottonDB (http://www.cottondb.org), the public cotton genome database.

The Candida Genome Database (CGD, http://www.candidagenome.org/) provides online access to genomic sequence data and manually curated functional information about genes and proteins of the human pathogen Candida albicans. Herein, we describe two recently added features, Candida Biochemical Pathways and the Textpresso full-text literature search tool. The Biochemical Pathways tool provides visualization of metabolic pathways and analysis tools that facilitate interpretation of experimental data, including results of large-scale experiments, in the context of Candida metabolism. Textpresso for Candida allows searching through the full-text of Candida-specific literature, including clinical and epidemiological studies.

The international ImMunoGeneTics information system® (IMGT) (http://imgt.cines.fr), created in 1989, by the Laboratoire d'ImmunoGenetique Moleculaire LIGM (Universite Montpellier II and CNRS) at Montpellier, France, is a high-quality integrated knowledge resource specializing in the immunoglobulins (IGs), T cell receptors (TRs), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune systems (RPI) that belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT includes several sequence databases (IMGT/LIGM-DB, IMGT/PRIMER-DB, IMGT/PROTEIN-DB and IMGT/MHC-DB), one genome database (IMGT/GENE-DB) and one three-dimensional (3D) structure database (IMGT/3Dstructure-DB), Web resources comprising 8000 HTML pages (IMGT Marie-Paule page), and interactive tools. IMGT data are expertly annotated according to the rules of the IMGT Scientific chart, based on the IMGT-ONTOLOGY concepts. IMGT tools are particularly useful for the analysis of the IG and TR repertoires in normal physiological and pathological situations. IMGT is used in medical research (autoimmune diseases, infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research, biotechnology related to antibody engineering (phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (clonalities, detection and follow up of residual diseases) and therapeutical approaches (graft, immunotherapy and vaccinology). IMGT is freely available at http://imgt.cines.fr.

T1DBase (http://T1DBase.org) [Smink et al. (2005) Nucleic Acids Res. 33, D544-D549; Burren et al. (2004) Hum. Genomics, 1, 98-109] is a public website and database that supports the type 1 diabetes (T1D) research community. T1DBase provides a consolidated T1D-oriented view of the complex data world that now confronts medical researchers and enables scientists to navigate from information they know to information that is new to them. Overview pages for genes and markers summarize information for these elements. The Gene Dossier summarizes information for a list of genes. GBrowse [Stein et al. (2002) Genome Res. 10, 1599-1610] displays genes and other features in their genomic context, and Cytoscape [Shannon et al. (2003) Genome Res. 13, 2498-2504] shows genes in the context of interacting proteins and genes. The Beta Cell Gene Atlas shows gene expression in beta cells, islets, and related cell types and lines, and the Tissue Expression Viewer shows expression across other tissues. The Microarray Viewer shows expression from more than 20 array experiments. The Beta Cell Gene Expression Bank contains manually curated gene and pathway annotations for genes expressed in beta cells. T1DMart is a query tool for markers and genotypes. PosterPages are 'home pages' about specific topics or datasets. The key challenge, now and in the future, is to provide powerful informatics capabilities to T1D scientists in a form they can use to enhance their research., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

FREE ACCESS This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited; International audience; Objective: AppleBreed DataBase (DB) aims to store genotypic and phenotypic data from multiple pedigree verified plant populations (crosses, breeding selections and commercial cultivars) so that they are easily accessible for geneticists and breeders. It will help in elucidating the genetics of economically important traits, in identifying molecular markers associated with agronomic traits, in allele mining and in choosing the best parental cultivars for breeding. It also provides high traceability of data over generations, years and localities. AppleBreed DB could serve as a generic database design for other perennial crops with long economic lifespans, long juvenile periods and clonal propagation. Results: AppleBreed DB is organized as a relational database. The core element is the GENOTYPE entity, which has two sub-classes at the physical level: TREE and DNA-SAMPLE. This approach facilitates all links between plant material, phenotypic and molecular data. The entities TREE, DNA-SAMPLE, PHENOTYPE and MOLECULAR DATA allow multi-annual observations to be stored as individual samples of individual trees, even if the nature of these observations differs greatly (e.g. molecular data on parts of the apple genome, physico-chemical measurements of fruit quality traits, and evaluation of disease resistance). AppleBreed DB also includes synonyms for cultivars and pedigrees. Finally, it can be loaded and explored through the web, and comes with tools to present basic statistical overviews and with validation procedures for phenotypic and marker data to certify data quality. AppleBreed DB was developed initially as a tool for scientists involved in apple genetics within the framework of the European project, ‘High-quality Disease Resistance in Apples for Sustainable Agriculture’ (HiDRAS), but it is also applicable to many other perennial crops

The Candida Genome Database (CGD, http://www.candidagenome.org/) contains a curated collection of genomic information and community resources for researchers who are interested in the molecular biology of the opportunistic pathogen Candida albicans. With the recent release of a new assembly of the C.albicans genome, Assembly 20, C.albicans genomics has entered a new era. Although the C.albicans genome assembly continues to undergo refinement, multiple assemblies and gene nomenclatures will remain in widespread use by the research community. CGD has now taken on the responsibility of maintaining the most up-to-date version of the genome sequence by providing the data from this new assembly alongside the data from the previous assemblies, as well as any future corrections and refinements. In this database update, we describe the sequence information available for C.albicans, the sequence information contained in CGD, and the tools for sequence retrieval, analysis and comparison that CGD provides. CGD is freely accessible at http://www.candidagenome.org/ and CGD curators may be contacted by email at ude.drofnats.emoneg@rotaruc-adidnac.

CandidaDB is accessible at http://genolist.pasteur.fr/CandidaDB.; International audience; CandidaDB is a database dedicated to the genome of the most prevalent systemic fungal pathogen of humans, Candida albicans. CandidaDB is based on an annotation of the Stanford Genome Technology Center C.albicans genome sequence data by the European Galar Fungail Consortium. CandidaDB Release 2.0 (June 2004) contains information pertaining to Assembly 19 of the genome of C.albicans strain SC5314. The current release contains 6244 annotated entries corresponding to 130 tRNA genes and 5917 protein-coding genes. For these, it provides tentative functional assignments along with numerous pre-run analyses that can assist the researcher in the evaluation of gene function for the purpose of specific or large-scale analysis. CandidaDB is based on GenoList, a generic relational data schema and a World Wide Web interface that has been adapted to the handling of eukaryotic genomes. The interface allows users to browse easily through genome data and retrieve information. CandidaDB also provides more elaborate tools, such as pattern searching, that are tightly connected to the overall browsing system. As the C.albicans genome is diploid and still incompletely assembled, CandidaDB provides tools to browse the genome by individual supercontigs and to examine information about allelic sequences obtained from complementary contigs. CandidaDB is accessible at http://genolist.pasteur.fr/CandidaDB.

The international ImMunoGeneTics information system (IMGT; http://imgt.cines.fr), is a high quality integrated information system specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC), and related proteins of the immune system (RPI) of human and other vertebrates, created in 1989, by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM; Université Montpellier II and CNRS) at Montpellier, France. IMGT provides a common access to standardized data which include nucleotide and protein sequences, oligonucleotide primers, gene maps, genetic polymorphisms, specificities, 2D and 3D structures. IMGT consists of several sequence databases (IMGT/LIGM-DB, IMGT/MHC-DB, IMGT/PRIMER-DB), one genome database (IMGT/GENE-DB) and one 3D structure database (IMGT/3Dstructure-DB), interactive tools for sequence analysis (IMGT/V-QUEST, IMGT/JunctionAnalysis, IMGT/PhyloGene, IMGT/Allele-Align), for genome analysis (IMGT/GeneSearch, IMGT/GeneView, IMGT/LocusView) and for 3D structure analysis (IMGT/StructuralQuery), and Web resources ("IMGT Marie-Paule page") comprising 8000 HTML pages. IMGT other accesses include SRS, FTP, search by BLAST, etc. By its high quality and its easy data distribution, IMGT has important implications in medical research (repertoire in autoimmune diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research, genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries) and therapeutical approaches (grafts, immunotherapy). IMGT is freely available at http://imgt.cines.fr.

BackgroundHaemophilus influenzae (H. Influenzae) is the causative agent of pneumonia, bacteraemia and meningitis. The organism is responsible for large number of deaths in both developed and developing countries. Even-though the first bacterial genome to be sequenced was that of H. Influenzae, there is no exclusive database dedicated for H. Influenzae. This prompted us to develop the Haemophilus influenzae Genome Database (HIGDB). MethodsAll data of HIGDB are stored and managed in MySQL database. The HIGDB is hosted on Solaris server and developed using PERL modules. Ajax and JavaScript are used for the interface development. ResultsThe HIGDB contains detailed information on 42,741 proteins, 18,077 genes including 10 whole genome sequences and also 284 three dimensional structures of proteins of H. influenzae. In addition, the database provides "Motif search" and "GBrowse". The HIGDB is freely accessible through the URL: http://bioserver1.physics.iisc.ernet.in/HIGDB/. DiscussionThe HIGDB will be a single point access for bacteriological, clinical, genomic and proteomic information of H. influenzae. The database can also be used to identify DNA motifs within H. influenzae genomes and to compare gene or protein sequences of a particular strain with other strains of H. influenzae. The HIGDB act as a single access point source for Haemophilus influenzae genomes.It provides a dynamic interface to execute varied searches for genes and proteins.The database facilitates the comparative study of H. influenzae genomes.It allows dynamic viewing of the genomic content of H. influenzae strains.It aids in the identification of DNA motifs within H. influenzae genomes.

The RGD Pathway Portal provides pathway annotations for rat, human and mouse genes and pathway diagrams and suites, all interconnected via the pathway ontology. Diagram pages present the diagram and description, with diagram objects linked to additional resources. A newly-developed dual-functionality web application composes the diagram page. Curators input the description, diagram, references and additional pathway objects. The application combines these with tables of rat, human and mouse pathway genes, including genetic information, analysis tool and reference links, and disease, phenotype and other pathway annotations to pathway genes. The application increases the information content of diagram pages while expediting publication.

The PEDANT genome database (http://pedant.gsf.de) contains pre-computed bioinformatics analyses of publicly available genomes. Its main mission is to provide robust automatic annotation of the vast majority of amino acid sequences, which have not been subjected to in-depth manual curation by human experts in high-quality protein sequence databases. By design PEDANT annotation is genome-oriented, making it possible to explore genomic context of gene products, and evaluate functional and structural content of genomes using a category-based query mechanism. At present, the PEDANT database contains exhaustive annotation of over 1,240,000 proteins from 270 eubacterial, 23 archeal and 41 eukaryotic genomes.

Microcystis aeruginosa is a cyanobacterium that can form harmful algal blooms (HABs) producing toxic secondary metabolites. We provide here draft genome information of four strains of this freshwater cyanobacterium that was obtained by the Next Generation Sequencing approach to provide a better understanding of molecular mechanisms at the physiological and ecological levels. After gene assembly, genes of each strain were identified and annotated, and a genome database and G-browser of M. aeruginosa were subsequently constructed. Such genome information resources will enable us to obtain useful information for molecular ecological studies with a better understanding of modulating mechanisms of environmental factors associated with blooming.

Background: The University of California, Santa Cruz (UCSC) genome database is among the most used sources of genomic annotation in human and other organisms. The database offers an excellent web-based graphical user interface (the UCSC genome browser) and several means for programmatic queries. A simple application programming interface (API) in a scripting language aimed at the biologist was however not yet available. Here, we present the Ruby UCSC API, a library to access the UCSC genome database using Ruby. Results: The API is designed as a BioRuby plug-in and built on the ActiveRecord 3 framework for the object-relational mapping, making writing SQL statements unnecessary. The current version of the API supports databases of all organisms in the UCSC genome database including human, mammals, vertebrates, deuterostomes, insects, nematodes, and yeast. The API uses the bin index—if available—when querying for genomic intervals. The API also supports genomic sequence queries using locally downloaded *.2bit files that are not stored in the official MySQL database. The API is implemented in pure Ruby and is therefore available in different environments and with different Ruby interpreters (including JRuby). Conclusions: Assisted by the straightforward object-oriented design of Ruby and ActiveRecord, the Ruby UCSC API will facilitate biologists to query the UCSC genome database programmatically. The API is available through the RubyGem system. Source code and documentation are available at https://github.com/misshie/bioruby-ucsc-api/ under the Ruby license. Feedback and help is provided via the website at http://rubyucscapi.userecho.com/., BMC Bioinformatics, 13, 240; 2012

When funding for Tetrahymena Genome Database (TGD) ended in 2006, no further updates were made to this important community resource and the main database was taken offline in 2008. We have restored and updated this important resource for use by the Tetrahymena research community. We have also retooled the TGD website (now TGD Wiki) to allow members of the community to directly update the information presented for each gene, including gene names, descriptions and Gene Ontology annotations, from a web browser. Maintenance of genome annotations by the authors generating and publishing primary data, rather than dedicated scientific curators, is a viable alternative for the upkeep of genomes, particularly for organisms with smaller research communities. By combining simple, intuitive displays with the powerful search functions made possible by its underlying relational database, TGD Wiki has been designed to maximize participation by bench scientists in the development of their community bioinformatics resource. Database URL: http://ciliate.org

A genetic association study is a complicated process that involves collecting phenotypic data, generating genotypic data, analyzing associations between genotypic and phenotypic data, and interpreting genetic biomarkers identified. SNPTrack is an integrated bioinformatics system developed by the US Food and Drug Administration (FDA) to support the review and analysis of pharmacogenetics data resulting from FDA research or submitted by sponsors. The system integrates data management, analysis, and interpretation in a single platform for genetic association studies. Specifically, it stores genotyping data and single-nucleotide polymorphism (SNP) annotations along with study design data in an Oracle database. It also integrates popular genetic analysis tools, such as PLINK and Haploview. SNPTrack provides genetic analysis capabilities and captures analysis results in its database as SNP lists that can be cross-linked for biological interpretation to gene/protein annotations, Gene Ontology, and pathway analysis data. With SNPTrack, users can do the entire stream of bioinformatics jobs for genetic association studies. SNPTrack is freely available to the public at http://www.fda.gov/ScienceResearch/BioinformaticsTools/SNPTrack/default.htm.

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

CandidaDB: http://genodb.pasteur.fr/CandidaDB; International audience; CandidaDB (http://genodb.pasteur.fr/CandidaDB) was established in 2002 to provide the first genomic database for the human fungal pathogen Candida albicans. The availability of an increasing number of fully or partially completed genome sequences of related fungal species has opened the path for comparative genomics and prompted us to migrate CandidaDB into a multi-genome database. The new version of CandidaDB houses the latest versions of the genomes of C. albicans strains SC5314 and WO-1 along with six genome sequences from species closely related to C. albicans that all belong to the CTG clade of Saccharomycotina-Candida tropicalis, Candida (Clavispora) lusitaniae, Candida (Pichia) guillermondii, Lodderomyces elongisporus, Debaryomyces hansenii, Pichia stipitis-and the reference Saccharomyces cerevisiae genome. CandidaDB includes sequences coding for 54 170 proteins with annotations collected from other databases, enriched with illustrations of structural features and functional domains and data of comparative analyses. In order to take advantage of the integration of multiple genomes in a unique database, new tools using pre-calculated or user-defined comparisons have been implemented that allow rapid access to comparative analysis at the genomic scale.

The Candida Genome Database (CGD; http://www.candidagenome.org) is a resource for information about the Candida albicans genomic sequence and the molecular biology of its encoded gene products. CGD collects and organizes data from the biological literature concerning C. albicans, and provides tools for viewing, searching, analysing, and downloading these data. CGD also serves as an organizing centre for the C. albicans research community, providing a gene-name registry, contact information, and research community news. This article describes the information contained in CGD and how to access it, either from the perspective of a bench scientist interested in the function of one or a few genes, or from the perspective of a biologist or bioinformatician interpreting large-scale functional genomic datasets.

The identification of genes underlying human genetic disorders requires the combination of data related to cytogenetic localization, phenotypes and expression patterns, to generate a list of candidate genes. In the field of human genetics, it is normal to perform this combination analysis by hand. We report on GeneSeeker (http://www.cmbi.ru.nl/GeneSeeker/), a web server that gathers and combines data from a series of databases. All database searches are performed via the web interfaces provided with the original databases, guaranteeing that the most recent data are queried, and obviating data warehousing. GeneSeeker makes the same selection of candidate genes as the human geneticists would have performed, and thus reducing the time-consuming process to a few minutes. GeneSeeker is particularly well suited for syndromes in which the disease gene displays altered expression patterns in the affected tissue(s).

EcoCyc is an organism-specific pathway/genome database that describes the metabolic and signal-transduction pathways of Escherichia coli, its enzymes, its transport proteins and its mechanisms of transcriptional control of gene expression. EcoCyc is queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. EcoCyc is available at http://ecocyc.org/.

Manual extraction of information from the biomedical literature—or biocuration—is the central methodology used to construct many biological databases. For example, the UniProt protein database, the EcoCyc Escherichia coli database and the Candida Genome Database (CGD) are all based on biocuration. Biological databases are used extensively by life science researchers, as online encyclopedias, as aids in the interpretation of new experimental data and as golden standards for the development of new bioinformatics algorithms. Although manual curation has been assumed to be highly accurate, we are aware of only one previous study of biocuration accuracy. We assessed the accuracy of EcoCyc and CGD by manually selecting curated assertions within randomly chosen EcoCyc and CGD gene pages and by then validating that the data found in the referenced publications supported those assertions. A database assertion is considered to be in error if that assertion could not be found in the publication cited for that assertion. We identified 10 errors in the 633 facts that we validated across the two databases, for an overall error rate of 1.58%, and individual error rates of 1.82% for CGD and 1.40% for EcoCyc. These data suggest that manual curation of the experimental literature by Ph.D-level scientists is highly accurate. Database URL: http://ecocyc.org/, http://www.candidagenome.org//

Bamboo, as one of the most important non-timber forest products and fastest-growing plants in the world, represents the only major lineage of grasses that is native to forests. Recent success on the first high-quality draft genome sequence of moso bamboo (Phyllostachys edulis) provides new insights on bamboo genetics and evolution. To further extend our understanding on bamboo genome and facilitate future studies on the basis of previous achievements, here we have developed BambooGDB, a bamboo genome database with functional annotation and analysis platform. The de novo sequencing data, together with the full-length complementary DNA and RNA-seq data of moso bamboo composed the main contents of this database. Based on these sequence data, a comprehensively functional annotation for bamboo genome was made. Besides, an analytical platform composed of comparative genomic analysis, protein-protein interactions network, pathway analysis and visualization of genomic data was also constructed. As discovery tools to understand and identify biological mechanisms of bamboo, the platform can be used as a systematic framework for helping and designing experiments for further validation. Moreover, diverse and powerful search tools and a convenient browser were incorporated to facilitate the navigation of these data. As far as we know, this is the first genome database for bamboo. Through integrating high-throughput sequencing data, a full functional annotation and several analysis modules, BambooGDB aims to provide worldwide researchers with a central genomic resource and an extensible analysis platform for bamboo genome. BambooGDB is freely available at http://www.bamboogdb.org/. Database URL: http://www.bamboogdb.org.

This unit concentrates on the data contained within two human genome databasesGDB (Genome Database) and OMIM (Online Mendelian Inheritance in Man)and includes discussion of different methods for submitting and accessing data. An understanding of electronic mail, FTP, and the use of a World Wide Web (WWW) navigational tool such as Netscape or Internet Explorer is a prerequisite for utilizing the information in this unit.

Summary: Genetic linkage mapping enables the study of genome organization and the association of heritable traits with regions of sequenced genomes. Comparative genetic mapping is particularly powerful as it allows translation of information between related genomes and gives an insight into genome evolution. A common tool for the storage, comparison and visualization of genetic maps is CMap. However, current visualization in CMap is limited to the comparison of adjacent aligned maps. To overcome this limitation, we have developed CMap3D, a tool to compare multiple genetic maps in three-dimensional space. CMap3D is based on a client/server model ensuring operability with current CMap data repositories. This tool can be applied to any species where genetic map information is available and enables rapid, direct comparison between multiple aligned maps. Availability and Implementation: The software is a stand-alone application written in Processing and Java. Binaries are available for Windows, OSX and Linux, and require Sun Microsystems Java Runtime Environment 1.6 or later. The software is freely available for non-commercial use from http://flora.acpfg.com.au/ Contact: dave.edwards@uq.edu.au

Summary: As the genome sequences of multiple strains of a given bacterial species are obtained, more generalized bacterial genome databases may be complemented by databases that are focused on providing more information geared for a distinct bacterial phylogenetic group and its associated research community. The Burkholderia Genome Database represents a model for such a database, providing a powerful, user-friendly search and comparative analysis interface that contains features not found in other genome databases. It contains continually updated, curated and tracked information about Burkholderia cepacia complex genome annotations, plus other Burkholderia species genomes for comparison, providing a high-quality resource for its targeted cystic fibrosis research community. Availability: http://www.burkholderia.com. Source code: GNU GPL. Contact: brinkman@sfu.ca.

Background The yak (Bos grunniens) is a long-haired bovine that lives at high altitudes and is an important source of milk, meat, fiber and fuel. The recent sequencing, assembly and annotation of its genome are expected to further our understanding of the means by which it has adapted to life at high altitudes and its ecologically important traits. Description The Yak Genome Database (YGD) is an internet-based resource that provides access to genomic sequence data and predicted functional information concerning the genes and proteins of Bos grunniens. The curated data stored in the YGD includes genome sequences, predicted genes and associated annotations, non-coding RNA sequences, transposable elements, single nucleotide variants, and three-way whole-genome alignments between human, cattle and yak. YGD offers useful searching and data mining tools, including the ability to search for genes by name or using function keywords as well as GBrowse genome browsers and/or BLAST servers, which can be used to visualize genome regions and identify similar sequences. Sequence data from the YGD can also be downloaded to perform local searches. Conclusions A new yak genome database (YGD) has been developed to facilitate studies on high-altitude adaption and bovine genomics. The database will be continuously updated to incorporate new information such as transcriptome data and population resequencing data. The YGD can be accessed at http://me.lzu.edu.cn/yak.

Background: The Genome Database of the Latvian Population (LGDB) is a national biobank that collects, maintains, and processes health information, data, and biospecimens collected from representatives of the Latvian population. These specimens serve as a foundation for epidemiological research and prophylactic and therapeutic purposes. Methods: Participant recruitment and biomaterial and data processing were performed according to specifically designed standard protocols, taking into consideration international quality requirements. Legal and ethical aspects, including broad informed consent and personal data protection, were applied according to legal norms of the Republic of Latvia. Results: Since its start in 2006, the LGDB is comprised of biosamples and associated phenotypic and clinical information from over 31,504 participants, constituting approximately 1.5% of the Latvian population. The LGDB represents a mixed-design biobank and includes participants from the general population as well as disease-based cohorts. The standard set of biosamples stored in the LGDB consists of DNA, plasma, serum, and white blood cells; in some cohorts, these samples are complemented by cancer biopsies and microbiome and urine samples. The LGDB acts as a core structure for the Latvian Biomedical Research and Study Centre (BMC), representing the national node of Latvia in Biobanking and BioMolecular resources Research Infrastructure – European Research Infrastructure Consortium (BBMRI-ERIC). Conclusions: The development of the LGDB has enabled resources for biomedical research and promoted genetic testing in Latvia. Further challenges of the LGDB are the enrichment and harmonization of collected biosamples and data, the follow-up of selected participant groups, and continued networking and participation in collaboration projects.

GeneDB (http://www.genedb.org/) is a genome database for prokaryotic and eukaryotic organisms. The resource provides a portal through which data generated by the Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute and other collaborating sequencing centres can be made publicly available. It combines data from finished and ongoing genome and expressed sequence tag (EST) projects with curated annotation, that can be searched, sorted and downloaded, using a single web based resource. The current release stores 11 datasets of which six are curated and maintained by biologists, who review and incorporate information from the scientific literature, public databases and the respective research communities.

Background Soil salinity is a significant factor that impairs plant growth and agricultural productivity, and numerous efforts are underway to enhance salt tolerance of economically important plants. Populus species are widely cultivated for diverse uses. Especially, they grow in different habitats, from salty soil to mesophytic environment, and are therefore used as a model genus for elucidating physiological and molecular mechanisms of stress tolerance in woody plants. Description The Salinity Tolerant Poplar Database (STPD) is an integrative database for salt-tolerant poplar genome biology. Currently the STPD contains Populus euphratica genome and its related genetic resources. P. euphratica, with a preference of the salty habitats, has become a valuable genetic resource for the exploitation of tolerance characteristics in trees. This database contains curated data including genomic sequence, genes and gene functional information, non-coding RNA sequences, transposable elements, simple sequence repeats and single nucleotide polymorphisms information of P. euphratica, gene expression data between P. euphratica and Populus tomentosa, and whole-genome alignments between Populus trichocarpa, P. euphratica and Salix suchowensis. The STPD provides useful searching and data mining tools, including GBrowse genome browser, BLAST servers and genome alignments viewer, which can be used to browse genome regions, identify similar sequences and visualize genome alignments. Datasets within the STPD can also be downloaded to perform local searches. Conclusions A new Salinity Tolerant Poplar Database has been developed to assist studies of salt tolerance in trees and poplar genomics. The database will be continuously updated to incorporate new genome-wide data of related poplar species. This database will serve as an infrastructure for researches on the molecular function of genes, comparative genomics, and evolution in closely related species as well as promote advances in molecular breeding within Populus. The STPD can be accessed at http://me.lzu.edu.cn/stpd/.