Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE

Ecological adaptation determines functional mammalian olfactory subgenomes

The ability to smell is governed by the largest gene family in mammalian genomes, the olfactory receptor (OR) genes. Although these genes are well annotated in the finished human and mouse genomes, we still do not understand which receptors bind specific odorants or how they fully function. Previous comparative studies have been taxonomically limited and mostly focused on the percentage of OR pseudogenes within species. No study has investigated the adaptive changes of functional OR gene families across phylogenetically and ecologically diverse mammals. To determine the extent to which OR gene repertoires have been influenced by habitat, sensory specialization, and other ecological traits, to better understand the functional importance of specific OR gene families and thus the odorants they bind, we compared the functional OR gene repertoires from 50 mammalian genomes. We amplified more than 2000 OR genes in aquatic, semi-aquatic, and flying mammals and coupled these data with 48,000 OR genes from mostly terrestrial mammals, extracted from genomic projects. Phylogenomic, Bayesian assignment, and principle component analyses partitioned species by ecotype (aquatic, semi-aquatic, terrestrial, flying) rather than phylogenetic relatedness, and identified OR families important for each habitat. Functional OR gene repertoires were reduced independently in the multiple origins of aquatic mammals and were significantly divergent in bats. We reject recent neutralist views of olfactory subgenome evolution and correlate specific OR gene families with physiological requirements, a preliminary step toward unraveling the relationship between specific odors and respective OR gene families.

H-InvDB in 2009: extended database and data mining resources for human genes and transcripts

We report the extended database and data mining resources newly released in the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). H-InvDB is a comprehensive annotation resource of human genes and transcripts, and consists of two main views and six sub-databases. The latest release of H-InvDB (release 6.2) provides the annotation for 219,765 human transcripts in 43,159 human gene clusters based on human full-length cDNAs and mRNAs. H-InvDB now provides several new annotation features, such as mapping of microarray probes, new gene models, relation to known ncRNAs and information from the Glycogene database. H-InvDB also provides useful data mining resources-'Navigation search', 'H-InvDB Enrichment Analysis Tool (HEAT)' and web service APIs. 'Navigation search' is an extended search system that enables complicated searches by combining 16 different search options. HEAT is a data mining tool for automatically identifying features specific to a given human gene set. HEAT searches for H-InvDB annotations that are significantly enriched in a user-defined gene set, as compared with the entire H-InvDB representative transcripts. H-InvDB now has web service APIs of SOAP and REST to allow the use of H-InvDB data in programs, providing the users extended data accessibility.

GIFtS: annotation landscape analysis with GeneCards

BACKGROUND

Gene annotation is a pivotal component in computational genomics, encompassing prediction of gene function, expression analysis, and sequence scrutiny. Hence, quantitative measures of the annotation landscape constitute a pertinent bioinformatics tool. GeneCards is a gene-centric compendium of rich annotative information for over 50,000 human gene entries, building upon 68 data sources, including Gene Ontology (GO), pathways, interactions, phenotypes, publications and many more.

RESULTS

We present the GeneCards Inferred Functionality Score (GIFtS) which allows a quantitative assessment of a gene's annotation status, by exploiting the unique wealth and diversity of GeneCards information. The GIFtS tool, linked from the GeneCards home page, facilitates browsing the human genome by searching for the annotation level of a specified gene, retrieving a list of genes within a specified range of GIFtS value, obtaining random genes with a specific GIFtS value, and experimenting with the GIFtS weighting algorithm for a variety of annotation categories. The bimodal shape of the GIFtS distribution suggests a division of the human gene repertoire into two main groups: the high-GIFtS peak consists almost entirely of protein-coding genes; the low-GIFtS peak consists of genes from all of the categories. Cluster analysis of GIFtS annotation vectors provides the classification of gene groups by detailed positioning in the annotation arena. GIFtS also provide measures which enable the evaluation of the databases that serve as GeneCards sources. An inverse correlation is found (for GIFtS>25) between the number of genes annotated by each source, and the average GIFtS value of genes associated with that source. Three typical source prototypes are revealed by their GIFtS distribution: genome-wide sources, sources comprising mainly highly annotated genes, and sources comprising mainly poorly annotated genes. The degree of accumulated knowledge for a given gene measured by GIFtS was correlated (for GIFtS>30) with the number of publications for a gene, and with the seniority of this entry in the HGNC database.

CONCLUSION

GIFtS can be a valuable tool for computational procedures which analyze lists of large set of genes resulting from wet-lab or computational research. GIFtS may also assist the scientific community with identification of groups of uncharacterized genes for diverse applications, such as delineation of novel functions and charting unexplored areas of the human genome.

Candidate genes involved in neural plasticity and the risk for attention-deficit hyperactivity disorder: a meta-analysis of 8 common variants

BACKGROUND

Attention-deficit hyperactivity disorder (ADHD) is an important psychiatric condition in terms of its prevalence and impact on quality of life. It has one of the highest heritabilities found in psychiatric disorders. A number of association studies exploring several candidate genes in different populations around the world have been carried out. The objective of the present study was to carry out a meta-analysis for 8 common variants located in 5 top candidate genes for ADHD (BDNF, HTR1B, SLC6A2, SLC6A4 and SNAP25); these genes are known to be involved in synaptic transmission and plasticity.

METHODS

We performed a search for published genetic association studies that analyzed the candidate polymorphisms in different populations, and we applied state-of-the-art meta-analytical procedures to obtain pooled odds ratios (ORs) and to evaluate potential basis of heterogeneity. We included 75 genetic association studies in these meta-analyses.

RESULTS

A major part of the previously postulated associations were nonconsistent in the pooled odds ratios. We observed a weak significant association with a single nucleotide polymorphism (SNP) located in the 3' UTR region of the SNAP25 gene (rs3746544, T allele, OR 1.15, 95% confidence interval 1.01-1.31, p = 0.028, I(2) = 0%). In addition to the low coverage of genetic variability given by these variants, phenotypic heterogeneity between samples (ADHD subtypes, comorbidities) and genetic background may explain these differences.

LIMITATIONS

Limitations of our study include the retrospective nature of our meta-analysis with the incorporation of study-level data from published articles.

CONCLUSION

To our knowledge, the present study is the largest meta-analysis carried out for ADHD genetics; previously proposed cumulative associations with common polymorphisms in SLC6A4 and HTR1B genes were not supported. We identified a weak consistent association with a common SNP in the SNAP25 gene, a molecule that is known to be central for synaptic transmission and plasticity mechanisms.

Changes in red cell ion transport, reduced intratumoral neovascularization, and some mild motor function abnormalities accompany targeted disruption of the Mouse Kell gene (Kel)

Kell (ECE-3), a highly polymorphic blood group glycoprotein, displays more than 30 antigens that produce allo-antibodies and, on red blood cells (RBCs), is complexed through a single disulfide bond with the integral membrane protein, XK. XK is a putative membrane transporter whose absence results in a late onset form of neuromuscular abnormalities known as the McLeod syndrome. Although Kell glycoprotein is known to be an endothelin-3-converting enzyme, the full extent of its physiological function is unknown. To study the functions of Kell glycoprotein, we undertook targeted disruption of the murine Kel gene by homologous recombination. RBCs from Kel(-/-) mice lacked Kell glycoprotein, Kell/XK complex, and endothelin-3-converting enzyme activity and had reduced levels of XK. XK mRNA levels in spleen, brain, and testis were unchanged. In Kel(-/-) mice RBC Gardos channel activity was increased and the normal enhancement by endothelin-3 was blunted. Analysis of the microvessels of tumors produced from LL2 cells indicated that the central portion of tumors from wild-type mice were populated with many mature blood vessels, but that vessels in tumors from Kel(-/-) mice were fewer and smaller. The absence of Kell glycoprotein mildly affected some motor activities identified by foot splay on the drop tests. The targeted disruption of Kel in mouse enabled us to identify phenotypes that would not be easily detected in humans lacking Kell glycoprotein. In this regard, the Kell knockout mouse provides a good animal model for the study of normal and/or pathophysiological functions of Kell glycoprotein.

WhichGenes: a web-based tool for gathering, building, storing and exporting gene sets with application in gene set enrichment analysis

WhichGenes is a web-based interactive gene set building tool offering a very simple interface to extract always-updated gene lists from multiple databases and unstructured biological data sources. While the user can specify new gene sets of interest by following a simple four-step wizard, the tool is able to run several queries in parallel. Every time a new set is generated, it is automatically added to the private gene-set cart and the user is notified by an e-mail containing a direct link to the new set stored in the server. WhichGenes provides functionalities to edit, delete and rename existing sets as well as the capability of generating new ones by combining previous existing sets (intersection, union and difference operators). The user can export his sets configuring the output format and selecting among multiple gene identifiers. In addition to the user-friendly environment, WhichGenes allows programmers to access its functionalities in a programmatic way through a Representational State Transfer web service. WhichGenes front-end is freely available at http://www.whichgenes.org/, WhichGenes API is accessible at http://www.whichgenes.org/api/.

Update on the olfactory receptor (OR) gene superfamily

The olfactory receptor gene (OR) superfamily is the largest in the human genome. The superfamily contains 390 putatively functional genes and 465 pseudogenes arranged into 18 gene families and 300 subfamilies. Even members within the same subfamily are often located on different chromosomes. OR genes are located on all autosomes except chromosome 20, plus the X chromosome but not the Y chromosome. The gene:pseudogene ratio is lowest in human, higher in chimpanzee and highest in rat and mouse -- most likely reflecting the greater need of olfaction for survival in the rodent than in the human. The OR genes undergo allelic exclusion, each sensory neurone expressing usually only one odourant receptor allele; the mechanism by which this phenomenon is regulated is not yet understood. The nomenclature system (based on evolutionary divergence of genes into families and subfamilies of the OR gene superfamily) has been designed similarly to that originally used for the CYP gene superfamily.

Protein kinase C intervention: the state of play

Intervention in protein kinase C (PKC) has a chequered history, partly because of the poor selectivity of many inhibitors and partly a reflection of the sometimes antagonistic action of related PKC isoforms. Recent advances in targeting PKC isoforms have come from structural work on isolated kinase domains that have provided opportunities to drive selectivity through structure-based avenues. The promise of isoform selective inhibitors and the rationale for their development are discussed in the broader context of the PKC inhibitor arsenal.

GOAPhAR: An Integrative Discovery Tool for Annotation, Pathway Analysis

We have developed the web based tool GOAPhAR (Gene Ontology, Annotations and Pathways for Array Research), that integrates information from disparate sources regarding gene annotations, protein annotations, identifiers associated with probe sets, functional pathways, protein interactions, Gene Ontology, publicly available microarray datasets and tools for statistically validating clusters in microarray data. Genes of interest can be input as Affymetrix probe identifiers, Genbank, or Unigene identifiers for human, mouse or rat genomes. Results are provided in a user friendly interface with hyperlinks to the sources of information.

GeneDistiller--distilling candidate genes from linkage intervals

BACKGROUND

Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic solutions on the other hand usually focus on certain models, remain "black boxes" and do not offer the same degree of flexibility.

METHODOLOGY

We have developed a web-based application that combines the advantages of both approaches. Information from various data sources such as gene-phenotype associations, gene expression patterns and protein-protein interactions was integrated into a central database. Researchers can select which information for the genes within a candidate interval or for single genes shall be displayed. Genes can also interactively be filtered, sorted and prioritised according to criteria derived from the background knowledge and preconception of the disease under scrutiny.

CONCLUSIONS

GeneDistiller provides knowledge-driven, fully interactive and intuitive access to multiple data sources. It displays maximum relevant information, while saving the user from drowning in the flood of data. A typical query takes less than two seconds, thus allowing an interactive and explorative approach to the hunt for the candidate gene.

ACCESS

GeneDistiller can be freely accessed at http://www.genedistiller.org.

EMAAS: an extensible grid-based rich internet application for microarray data analysis and management

Background

Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management.

Results

EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms.

Conclusion

EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume.

G2Cdb: the Genes to Cognition database

Neuroscience databases linking genes, proteins, (patho)physiology, anatomy and behaviour across species will be valuable in a broad range of studies of the nervous system. G2Cdb is such a neuroscience database aiming to present a global view of the role of synapse proteins in physiology and disease. G2Cdb warehouses sets of genes and proteins experimentally elucidated by proteomic mass spectroscopy of signalling complexes and proteins biochemically isolated from mammalian synapse preparations, giving an experimentally validated definition of the constituents of the mammalian synapse. Using automated text-mining and expert (human) curation we have systematically extracted information from published neurobiological studies in the fields of synaptic signalling electrophysiology and behaviour in knockout and other transgenic mice. We have also surveyed the human genetics literature for associations to disease caused by mutations in synaptic genes. The synapse proteome datasets that G2Cdb provides offer a basis for future work in synapse biology and provide useful information on brain diseases. They have been integrated in a such way that investigators can rapidly query whether a gene or protein is found in brain-signalling complex(es), has a phenotype in rodent models or whether mutations are associated with a human disease. G2Cdb can be freely accessed at http://www.genes2cognition.org.

MiMiR--an integrated platform for microarray data sharing, mining and analysis

Background

Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data.

Results

A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package.

Conclusion

The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks

The Comparative Toxicogenomics Database (CTD) is a curated database that promotes understanding about the effects of environmental chemicals on human health. Biocurators at CTD manually curate chemical–gene interactions, chemical–disease relationships and gene–disease relationships from the literature. This strategy allows data to be integrated to construct chemical–gene–disease networks. CTD is unique in numerous respects: curation focuses on environmental chemicals; interactions are manually curated; interactions are constructed using controlled vocabularies and hierarchies; additional gene attributes (such as Gene Ontology, taxonomy and KEGG pathways) are integrated; data can be viewed from the perspective of a chemical, gene or disease; results and batch queries can be downloaded and saved; and most importantly, CTD acts as both a knowledgebase (by reporting data) and a discovery tool (by generating novel inferences). Over 116 000 interactions between 3900 chemicals and 13 300 genes have been curated from 270 species, and 5900 gene–disease and 2500 chemical–disease direct relationships have been captured. By integrating these data, 350 000 gene–disease relationships and 77 000 chemical–disease relationships can be inferred. This wealth of chemical–gene–disease information yields testable hypotheses for understanding the effects of environmental chemicals on human health. CTD is freely available at http://ctd.mdibl.org.

Tissue- and cell-specific alternative splicing of NFIC

Alternative splicing is an important mechanism for increasing genetic complexity leading to multiple transcripts from single genes and gene regulation through alternative promoters. Splicing often leads to unique tissue-specific patterns of mRNAs with specific biological functions. Nuclear factor I-C (NFI-C), a member of the NFI gene family, is expressed in numerous tissues including brain, liver, spleen and heart. However, the unique dental phenotype of Nfic(-/-) mice lacking molar roots demonstrates a critical role for this transcription factor in root formation. In humans, the NFI-C gene is alternatively spliced producing 4 isoforms. However, different spliced variants have not been studied in association with tissue specificity. The main objective of this study is to identify the NFI-C isoforms expressed in dental cells/tissues, comparing them to the spliced variants in nondental cells/tissues and to analyze their relative expression levels in various cell types. Using bioinformatics, we analyzed the NFI-C gene structure, identifying 2 potential alternative promoters driving expression of selective mRNA transcripts. Our studies show the expression of 3 NFI-C transcripts with the overall splicing pattern conserved between dental and nondental cells tested. Furthermore, by quantitative real-time PCR analysis, we found that although the relative levels of these transcripts were similar in dental and nondental cells, significant differences were observed within the dental cells tested. These are the first studies to analyze the expression of NFI-C isoforms in dental versus nondental cells/tissues, finding subtle cell-/tissue-specific expression patterns that could explain the dental phenotype of Nfic(-/-) mice.

Using bioinformatics tools for the sequence analysis of immunoglobulins and T cell receptors

The huge potential repertoire of 10(12) immunoglobulins and 10(12) T cell receptors per individual results from complex mechanisms of combinatorial diversity between the variable (V), diversity (D), and junction (J) genes, nucleotide deletions and insertions (N-diversity) at the junctions and, for the immunoglobulins, somatic hypermutations. The accurate analysis of rearranged immunoglobulin and T cell receptor sequences, and the annotation of the junctions, therefore represent a huge challenge. The IMGT Scientific chart rules, based on the IMGT-ONTOLOGY concepts, were the prerequisites for the implementation of the IMGT/V-QUEST and IMGT/JunctionAnalysis tools. IMGT/V-QUEST analyzes germline V and rearranged V-J or V-D-J nucleotide sequences. IMGT/JunctionAnalysis is the first tool that automatically analyzes the complex junctions in detail. These interactive tools are easy to use and freely available on the Web (http://imgt.cines.fr), either separately or integrated.

The UCSC Genome Browser

The University of California Santa Cruz (UCSC) Genome Browser (genome.ucsc.edu) is a popular Web-based tool for quickly displaying a requested portion of a genome at any scale, accompanied by a series of aligned annotation "tracks". The annotations-generated by the UCSC Genome Bioinformatics Group and external collaborators-display gene predictions, mRNA and expressed sequence tag alignments, simple nucleotide polymorphisms, expression and regulatory data, and pairwise and multiple-species comparative genomics data. All information relevant to a region is presented in one window, facilitating biological analysis and interpretation. The database tables underlying the Genome Browser tracks can be viewed, downloaded, and manipulated using another Web-based application, the UCSC Table Browser. Users can upload personal data as custom annotation tracks in both browsers for research or educational use. This unit describes how to use the Genome Browser and Table Browser for genome analysis, download the underlying database tables, and create and display custom annotation tracks.

Web-based resources for clinical bioinformatics

In the post-Human Genome Project era, awareness of the resources available through the internet is essential to both molecular biologists and clinicians. An overview of the main databases and analytical tools described in this chapter is important to understand the principles upon which hypotheses are generated, experiments are based and conclusions reached. Similarly, an introduction to the terminology of these resources often facilitates their use and adoption into practice. This chapter covers database resources such as NCBI/ Entrez, Ensembl and UCSC as well as analytical tools for sequence alignment, promoter analysis and molecular interactions.

The HGNC Database in 2008: a resource for the human genome

The HUGO Gene Nomenclature Committee (HGNC) aims to assign a unique and ideally meaningful name and symbol to every human gene. The HGNC database currently comprises over 24 000 public records containing approved human gene nomenclature and associated gene information. Following our recent relocation to the European Bioinformatics Institute our homepage can now be found at http://www.genenames.org, with direct links to the searchable HGNC database and other related database resources, such as the HCOP orthology search tool and manually curated gene family webpages.

Computational selection and prioritization of candidate genes for fetal alcohol syndrome

Background

Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although in utero alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach.

Results

10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes.

Conclusion

This analysis highlighted a list of strong candidate genes from the TGF-β, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis.

Functional profiling of microarray experiments using text-mining derived bioentities

MOTIVATION

The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.

Differences in (-)citronellal binding to various odorant receptors

To test the hypothesis that olfactory receptors (ORs) recognize different molecular features of odor molecules termed "odotypes", we studied receptor-ligand interactions of two human and two mouse ORs, recognizing (-)citronellal. Structurally similar receptors provide identical binding pockets (OLFR43, OR1A1, and OR1A2), and have comparable EC(50) values. Other ORs with lower sequence identity bind (-)citronellal in a different way, leading to different EC(50) values.

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.

TRED: a transcriptional regulatory element database, new entries and other development

Transcriptional factors (TFs) and many of their target genes are involved in gene regulation at the level of transcription. To decipher gene regulatory networks (GRNs) we require a comprehensive and accurate knowledge of transcriptional regulatory elements. TRED (http://rulai.cshl.edu/TRED) was designed as a resource for gene regulation and function studies. It collects mammalian cis- and trans-regulatory elements together with experimental evidence. All the regulatory elements were mapped on to the assembled genomes. In this new release, we included a total of 36 TF families involved in cancer. Accordingly, the number of target promoters and genes for TF families has increased dramatically. There are 11,660 target genes (7479 in human, 2691 in mouse and 1490 in rat) and 14,908 target promoters (10,225 in human, 2985 in mouse and 1698 in rat). Additionally, we constructed GRNs for each TF family by connecting the TF-target gene pairs. Such interaction data between TFs and their target genes will assist detailed functional studies and help to obtain a panoramic view of the GRNs for cancer research.

The UCSC genome browser database: update 2007

The University of California, Santa Cruz Genome Browser Database contains, as of September 2006, sequence and annotation data for the genomes of 13 vertebrate and 19 invertebrate species. The Genome Browser displays a wide variety of annotations at all scales from the single nucleotide level up to a full chromosome and includes assembly data, genes and gene predictions, mRNA and EST alignments, and comparative genomics, regulation, expression and variation data. The database is optimized for fast interactive performance with web tools that provide powerful visualization and querying capabilities for mining the data. In the past year, 22 new assemblies and several new sets of human variation annotation have been released. New features include VisiGene, a fully integrated in situ hybridization image browser; phyloGif, for drawing evolutionary tree diagrams; a redesigned Custom Track feature; an expanded SNP annotation track; and many new display options. The Genome Browser, other tools, downloadable data files and links to documentation and other information can be found at .

Microarray-based analysis of microbial community RNAs by whole-community RNA amplification

A new approach, termed whole-community RNA amplification (WCRA), was developed to provide sufficient amounts of mRNAs from environmental samples for microarray analysis. This method employs fusion primers (six to nine random nucleotides with an attached T7 promoter) for the first-strand synthesis. The shortest primer (T7N6S) gave the best results in terms of the yield and representativeness of amplification. About 1,200- to 1,800-fold amplification was obtained with amounts of the RNA templates ranging from 10 to 100 ng, and very representative detection was obtained with 50 to 100 ng total RNA. Evaluation with a Shewanella oneidensis Deltafur strain revealed that the amplification method which we developed could preserve the original abundance relationships of mRNAs. In addition, to determine whether representative detection of RNAs can be achieved with mixed community samples, amplification biases were evaluated with a mixture containing equal quantities of RNAs (100 ng each) from four bacterial species, and representative amplification was also obtained. Finally, the method which we developed was applied to the active microbial populations in a denitrifying fluidized bed reactor used for denitrification of contaminated groundwater and ethanol-stimulated groundwater samples for uranium reduction. The genes expressed were consistent with the expected functions of the bioreactor and groundwater system, suggesting that this approach is useful for analyzing the functional activities of microbial communities. This is one of the first demonstrations that microarray-based technology can be used to successfully detect the activities of microbial communities from real environmental samples in a high-throughput fashion.

Expoldb: expression linked polymorphism database with inbuilt tools for analysis of expression and simple repeats

BACKGROUND

Quantitative variation in gene expression has been proposed to underlie phenotypic variation among human individuals. A facilitating step towards understanding the basis for gene expression variability is associating genome wide transcription patterns with potential cis modifiers of gene expression.

DESCRIPTION

EXPOLDB, a novel Database, is a new effort addressing this need by providing information on gene expression levels variability across individuals, as well as the presence and features of potentially polymorphic (TG/CA)n repeats. EXPOLDB thus enables associating transcription levels with the presence and length of (TG/CA)n repeats. One of the unique features of this database is the display of expression data for 5 pairs of monozygotic twins, which allows identification of genes whose variability in expression, are influenced by non-genetic factors including environment. In addition to queries by gene name, EXPOLDB allows for queries by a pathway name. Users can also upload their list of HGNC (HUGO (The Human Genome Organisation) Gene Nomenclature Committee) symbols for interrogating expression patterns. The online application 'SimRep' can be used to find simple repeats in a given nucleotide sequence. To help illustrate primary applications, case examples of Housekeeping genes and the RUNX gene family, as well as one example of glycolytic pathway genes are provided.

CONCLUSION

The uniqueness of EXPOLDB is in facilitating the association of genome wide transcription variations with the presence and type of polymorphic repeats while offering the feature for identifying genes whose expression variability are influenced by non genetic factors including environment. In addition, the database allows comprehensive querying including functional information on biochemical pathways of the human genes. EXPOLDB can be accessed at http://expoldb.igib.res.in/expol.

Les récepteurs des molécules odorantes et le codage olfactif

The first step of olfactory detection involves interactions between odorant molecules and neuronal protein receptors. Odour coding results from the combinatory activation of a set of receptors and rests on their clonal expression and olfactory neurone connexion, which lead to formation of a specific sensory map in the cortex. This system, sufficient to discriminate myriads of odorants with a mere 350 different receptors, allows humans to smell molecules that are not natural (new cooking flavours, synthetic chemicals...). The extreme olfactory genome diversity explains the absence of odour semantics. Olfactory receptors are also involved in cellular chemotaxis.

Comparative gene expression analysis reveals a characteristic molecular profile of the superior olivary complex

The superior olivary complex (SOC) is a very conspicuous structure in the mammalian auditory brainstem. It represents the first binaural processing center and is important for sound localization in the azimuth and in feedback regulation of cochlear function. In order to define molecular determinants of the SOC, which are of potential functional relevance, we have performed a comprehensive analysis of its transcriptome by serial analysis of gene expression in adult rats. Here, we performed a detailed analysis of the SOC's gene expression profile compared to that of two other neural tissues, the striatum and the hippocampus, and with extraocular muscle tissue. This tested the hypothesis that SOC-specific or significantly upregulated transcripts provide candidates for the specific function of auditory neurons. Thirty-three genes were significantly upregulated in the SOC when compared to the two other neural tissues. Thirteen encoded proteins involved in neurotransmission, including action potential propagation, exocytosis, and myelination; five genes are important for the energy metabolism, and five transcripts are unknown or poorly characterized and have yet to be described in the nervous system. The comparison of functional gene classes indicates that the SOC has the highest energy demand of the three neural tissues, yet protein turnover is apparently not increased. This suggests a high energy demand for fueling auditory neurotransmission. Such a demand may have implications on auditory-specific tasks and relate to central auditory processing disorders. Ultimately, these data provide new avenues to foster investigations of auditory function and to advance molecular physiology in the central auditory system.

The HUGO Gene Nomenclature Database, 2006 updates

The HUGO Gene Nomenclature Committee (HGNC) aims to give every human gene a unique and ideally meaningful name and symbol. The HGNC database, previously known as Genew, contains over 22 000 public records with approved human gene nomenclature and associated information. The database has undergone major improvements throughout the last year, is publicly available for online searching at and has a new custom downloads interface at .

Inconsistencies between human genetic cytolocations and those derived using genomic sequence

One result of the publishing of the human genome sequence is the ability to define objects through their position on the consensus sequence. While this has simplified the process of creating order maps for genes on a chromosome, it has created discrepancies between the published cytolocations of human genes, as presented through genetic references, and those locations derived computationally from the genomic sequence. For the 6,830 records with HUGO gene symbols shared between the online version of Mendelian Inheritance in Man and Ensembl, 18% of the records have a discrepancy of at least one cytogenetic band between the datasets. Discordance between data sets at this frequency would have a significant impact on the utility of datasets created by the amalgamation of numerous biological databases.

IMGT, the international ImMunoGeneTics information system: a standardized approach for immunogenetics and immunoinformatics

IMGT, the international ImMunoGeneTics information system http://imgt.cines.fr, was created in 1989 by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM) (Université Montpellier II and CNRS) at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) of any species which belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT consists of five databases, ten on-line tools and more than 8,000 HTML pages of Web resources. IMGT provides a common access to standardized data from genome, genetics, proteome and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY comprises six main concepts: IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, ORIENTATION and OBTENTION. Based on these concepts, the controlled vocabulary and the annotation rules necessary for the immunogenetics data identification, classification, description and numbering and for the management of IMGT knowledge are defined in the IMGT Scientific chart. IMGT is the international reference in immunogenetics and immunoinformatics for medical research (repertoire analysis of the IG antibody sites and of the TR recognition sites in autoimmune and infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires in farm and wild life species), 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, chimeric, humanized and human antibodies), diagnostics (detection and follow up of residual diseases) and therapeutical approaches (grafts, immunotherapy, vaccinology). IMGT is freely available at http://imgt.cines.fr.

GeneSeeker: extraction and integration of human disease-related information from web-based genetic databases

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 (), 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).

IMGT/GENE-DB: a comprehensive database for human and mouse immunoglobulin and T cell receptor genes

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation. IMGT/GENE-DB is freely available at http://imgt.cines.fr.

SIEGE: Smoking Induced Epithelial Gene Expression Database

The SIEGE (Smoking Induced Epithelial Gene Expression) database is a clinical resource for compiling and analyzing gene expression data from epithelial cells of the human intra-thoracic airway. This database supports a translational research study whose goal is to profile the changes in airway gene expression that are induced by cigarette smoke. RNA is isolated from airway epithelium obtained at bronchoscopy from current-, former- and never-smoker subjects, and hybridized to Affymetrix HG-U133A Genechips, which measure the level of expression of ∼22 500 human transcripts. The microarray data generated along with relevant patient information is uploaded to SIEGE by study administrators using the database's web interface, found at http://pulm.bumc.bu.edu/siegeDB. PERL-coded scripts integrated with SIEGE perform various quality control functions including the processing, filtering and formatting of stored data. The R statistical package is used to import database expression values and execute a number of statistical analyses including t-tests, correlation coefficients and hierarchical clustering. Values from all statistical analyses can be queried through CGI-based tools and web forms found on the ‘Search’ section of the database website. Query results are embedded with graphical capabilities as well as with links to other databases containing valuable gene resources, including Entrez Gene, GO, Biocarta, GeneCards, dbSNP and the NCBI Map Viewer.

GeneTide--Terra Incognita Discovery Endeavor: a new transcriptome focused member of the GeneCards/GeneNote suite of databases

GeneCards® is an automatically mined database of human genes that strives to create, along with its auxiliary databases—GeneLoc, GeneNote and GeneAnnot—the most inclusive resource of gene-centered information of the human genome. GeneTide, the Gene Terra Incognita Discovery Endeavor (http://genecards.weizmann.ac.il/genetide/), the newest addition to this family, is a transcriptome-focused database which aims to enhance GeneCards with additional expressed sequence tag (EST)-based genes. This is achieved by comprehensively mapping >85% of the ∼5.6 million human ESTs currently available at dbEST to known genes by means of data mining and integration of genomic resources including UniGene, DoTS, AceView and in-house resources. GeneTide thus creates comprehensive links between ESTs and GeneCards genes. Furthermore, groups of unassociated transcripts serve as a basis for defining novel EST-based GeneCards Candidates (EGCs). These EGCs, nearly 25 000 of which were defined in version 0.3 of GeneTide, are further annotated with various parameters, including splicing evidence and expression data extracted from the GeneNote database, to determine their validity as possible de novo genes.

Promoter features related to tissue specificity as measured by Shannon entropy

BACKGROUND

The regulatory mechanisms underlying tissue specificity are a crucial part of the development and maintenance of multicellular organisms. A genome-wide analysis of promoters in the context of gene-expression patterns in tissue surveys provides a means of identifying the general principles for these mechanisms.

RESULTS

We introduce a definition of tissue specificity based on Shannon entropy to rank human genes according to their overall tissue specificity and by their specificity to particular tissues. We apply our definition to microarray-based and expressed sequence tag (EST)-based expression data for human genes and use similar data for mouse genes to validate our results. We show that most genes show statistically significant tissue-dependent variations in expression level. We find that the most tissue-specific genes typically have a TATA box, no CpG island, and often code for extracellular proteins. As expected, CpG islands are found in most of the least tissue-specific genes, which often code for proteins located in the nucleus or mitochondrion. The class of genes with no CpG island or TATA box are the most common mid-specificity genes and commonly code for proteins located in a membrane. Sp1 was found to be a weak indicator of less-specific expression. YY1 binding sites, either as initiators or as downstream sites, were strongly associated with the least-specific genes.

CONCLUSIONS

We have begun to understand the components of promoters that distinguish tissue-specific from ubiquitous genes, to identify associations that can predict the broad class of gene expression from sequence data alone.

Linking disease-associated genes to regulatory networks via promoter organization

Pathway- or disease-associated genes may participate in more than one transcriptional co-regulation network. Such gene groups can be readily obtained by literature analysis or by high-throughput techniques such as microarrays or protein-interaction mapping. We developed a strategy that defines regulatory networks by in silico promoter analysis, finding potentially co-regulated subgroups without a priori knowledge. Pairs of transcription factor binding sites conserved in orthologous genes (vertically) as well as in promoter sequences of co-regulated genes (horizontally) were used as seeds for the development of promoter models representing potential co-regulation. This approach was applied to a Maturity Onset Diabetes of the Young (MODY)-associated gene list, which yielded two models connecting functionally interacting genes within MODY-related insulin/glucose signaling pathways. Additional genes functionally connected to our initial gene list were identified by database searches with these promoter models. Thus, data-driven in silico promoter analysis allowed integrating molecular mechanisms with biological functions of the cell.

Prediction of the odorant binding site of olfactory receptor proteins by human-mouse comparisons

Olfactory receptors (ORs) are a large family of proteins involved in the recognition and discrimination of numerous odorants. These receptors belong to the G-protein coupled receptor (GPCR) hyperfamily, for which little structural data are available. In this study we predict the binding site residues of OR proteins by analyzing a set of 1441 OR protein sequences from mouse and human. The central insight utilized is that functional contact residues would be conserved among pairs of orthologous receptors, but considerably less conserved among paralogous pairs. Using judiciously selected subsets of 218 ortholog pairs and 518 paralog pairs, we have identified 22 sequence positions that are both highly conserved among the putative orthologs and variable among paralogs. These residues are disposed on transmembrane helices 2 to 7, and on the second extracellular loop of the receptor. Strikingly, although the prediction makes no assumption about the location of the binding site, these amino acid positions are clustered around a pocket in a structural homology model of ORs, mostly facing the inner lumen. We propose that the identified positions constitute the odorant binding site. This conclusion is supported by the observation that all but one of the predicted binding site residues correspond to ligand-contact positions in other rhodopsin-like GPCRs.

Target SNP selection in complex disease association studies

BACKGROUND

The massive amount of SNP data stored at public internet sites provides unprecedented access to human genetic variation. Selecting target SNP for disease-gene association studies is currently done more or less randomly as decision rules for the selection of functional relevant SNPs are not available.

RESULTS

We implemented a computational pipeline that retrieves the genomic sequence of target genes, collects information about sequence variation and selects functional motifs containing SNPs. Motifs being considered are gene promoter, exon-intron structure, AU-rich mRNA elements, transcription factor binding motifs, cryptic and enhancer splice sites together with expression in target tissue. As a case study, 396 genes on chromosome 6p21 in the extended HLA region were selected that contributed nearly 20,000 SNPs. By computer annotation ~2,500 SNPs in functional motifs could be identified. Most of these SNPs are disrupting transcription factor binding sites but only those introducing new sites had a significant depressing effect on SNP allele frequency. Other decision rules concern position within motifs, the validity of SNP database entries, the unique occurrence in the genome and conserved sequence context in other mammalian genomes.

CONCLUSION

Only 10% of all gene-based SNPs have sequence-predicted functional relevance making them a primary target for genotyping in association studies.

GeneNote: whole genome expression profiles in normal human tissues

A novel data set, GeneNote (Gene Normal Tissue Expression), was produced to portray complete gene expression profiles in healthy human tissues using the Affymetrix GeneChip HG-U95 set, which includes 62 839 probe-sets. The hybridization intensities of two replicates were processed and analyzed to yield the complete transcriptome for twelve human tissues. Abundant novel information on tissue specificity provides a baseline for past and future expression studies related to diseases. The data is posted in GeneNote (http://genecards.weizmann.ac.il/genenote/), a widely used compendium of human genes (http://bioinfo.weizmann.ac.il/genecards).

The canine olfactory subgenome

We identified 971 olfactory receptor (OR) genes in the dog genome, estimated to constitute approximately 80% of the canine OR repertoire. This was achieved by directed genomic DNA cloning of olfactory sequence tags as well as by mining the Celera canine genome sequences. The dog OR subgenome is estimated to have 12% pseudogenes, suggesting a functional repertoire similar to that of mouse and considerably larger than for humans. No novel OR families were discovered, but as many as 34 gene subfamilies were unique to the dog. "Fish-like" Class I ancient ORs constituted 18% of the repertoire, significantly more than in human and mouse. A set of 122 dog-human-mouse ortholog triplets was identified, with a relatively high fraction of Class I ORs. The elucidation of a large portion of the canine olfactory receptor gene superfamily, with some dog-specific attributes, may help us understand the unique chemosensory capacities of this species.

Genew: the Human Gene Nomenclature Database, 2004 updates

Genew, the Human Gene Nomenclature Database http://www.gene.ucl.ac.uk/cgi-bin/nomenclature/searchgenes.pl is the only resource that provides data for all human genes that have approved symbols. It is managed by the HUGO Gene Nomenclature Committee (HGNC) as a confidential database, containing over 22 000 records, 75% of which are represented online by a publicly searchable text file. Since 2002, there have been significant improvements to the Genew search engine. Additionally we have increased our capacity to analyse confidential sequence data, which has enabled us to manage the large numbers of gene symbol requests that we receive from the chromosome sequencing consortia.

LIFEdb: a database for functional genomics experiments integrating information from external sources, and serving as a sample tracking system

We have implemented LIFEdb (http://www.dkfz.de/LIFEdb) to link information regarding novel human full-length cDNAs generated and sequenced by the German cDNA Consortium with functional information on the encoded proteins produced in functional genomics and proteomics approaches. The database also serves as a sample-tracking system to manage the process from cDNA to experimental read-out and data interpretation. A web interface enables the scientific community to explore and visualize features of the annotated cDNAs and ORFs combined with experimental results, and thus helps to unravel new features of proteins with as yet unknown functions.

Biomedical Literature Mining

It is now obvious that the rate-limiting step in high throughput experimentation is neither data acquisition nor analysis, but rather our ability to interpret data on a genome-wide scale. Indeed, the explosion of data sampling capacity combined with increasing publication rates greatly impairs our ability to find meaning in vast collections of data. In order to support data interpretation, bioinformatic tools are needed to identify critical information contained in large bodies of literature. However, extracting knowledge embedded in free text is an arduous task, compounded in the biomedical field by an inconsistent gene nomenclature, domain-specific language and restricted access to full text articles. This paper presents a selection of currently available biomedical literature mining software. These tools rely on statistic and, more recently, semantic analyses (Natural Language Processing) to automatically extract information from the literature. In addition, a literature mining strategy has been developed to explore patterns of term occurrences in abstracts. This method automatically identifies relevant keywords in collections of abstracts, and uses a pattern discovery algorithm to generate a visual interface for exploring functional associations among genes. Term occurrence heatmaps can also be combined with gene expression profiles to provide valuable functional annotations. Furthermore, as demonstrated with tumor cell line literature profiling results, this approach can be applied to a variety of themes beyond genomic data analysis. Altogether, these examples illustrate how literature analysis can be employed to support knowledge discovery in biomedical research.