Kenneth S. Katz

ClinVar: public archive of interpretations of clinically relevant variants

ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) at the National Center for Biotechnology Information (NCBI) is a freely available archive for interpretations of clinical significance of variants for reported conditions. The database includes germline and somatic variants of any size, type or genomic location. Interpretations are submitted by clinical testing laboratories, research laboratories, locus-specific databases, OMIM®, GeneReviews™, UniProt, expert panels and practice guidelines. In NCBIs Variation submission portal, submitters upload batch submissions or use the Submission Wizard for single submissions. Each submitted interpretation is assigned an accession number prefixed with SCV. ClinVar staff review validation reports with data types such as HGVS (Human Genome Variation Society) expressions; however, clinical significance is reported directly from submitters. Interpretations are aggregated by variant-condition combination and assigned an accession number prefixed with RCV. Clinical significance is calculated for the aggregate record, indicating consensus or conflict in the submitted interpretations. ClinVar uses data standards, such as HGVS nomenclature for variants and MedGen identifiers for conditions. The data are available on the web as variant-specific views; the entire data set can be downloaded via ftp. Programmatic access for ClinVar records is available through NCBIs E-utilities. Future development includes providing a variant-centric XML archive and a web page for details of SCV submissions.

Introducing RefSeq and LocusLink: curated human genome resources at the NCBI

RefSeq records are included in the Entrez retrieval system (http://www.ncbi.nlm.nih.gov/entrez/). This allows a third query pathway, namely directly by Entrez nucleotide or protein text queries or indirectly by neighboring strategies. LocusLink and RefSeq data are also provided without restriction for ftp transfer (ftp://ncbi.nlm.nih.gov/refseq). Therefore, the combination of LocusLink and RefSeq resources provides a powerful approach to answering such questions as: •Is my sequence from a known gene? (Try blast and look for a RefSeq result.)•What sequence can I use as a standard for gene A? (Try blast or LocusLink.)•Where can I get more information about gene B? (Start at LocusLink.)•What genes are related to disorder Z? (Start at OMIM or LocusLink.)The goal of LocusLink and RefSeq is to include all known genes and their major products. As of the end of August 1999, ∼10 690 loci have been included, 7500 with at least some sequence data and 5985 reference mRNAs. Expanding the LocusLink and RefSeq datasets is an ongoing effort – LocusIDs are established as additional genes are identified, and RefSeq records are added as new links between genes and sequences with complete coding regions are made. The public sites are refreshed weekly. We welcome collaborations with the scientific community to ensure that these resources are as comprehensive and accurate as possible.

Human immunodeficiency virus type 1, human protein interaction database at NCBI

The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Protein Interaction Database’, available through the National Library of Medicine at www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions, was created to catalog all interactions between HIV-1 and human proteins published in the peer-reviewed literature. The database serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. To facilitate this discovery approach, the following information for each HIV-1 human protein interaction is provided and can be retrieved without restriction by web-based downloads and ftp protocols: Reference Sequence (RefSeq) protein accession numbers, Entrez Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. Currently, 2589 unique HIV-1 to human protein interactions and 5135 brief descriptions of the interactions, with a total of 14 312 PMID references to the original articles reporting the interactions, are stored in this growing database. In addition, all protein–protein interactions documented in the database are integrated into Entrez Gene records and listed in the ‘HIV-1 protein interactions’ section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication.

Gene: a gene-centered information resource at NCBI

The National Center for Biotechnology Informations (NCBI) Gene database (www.ncbi.nlm.nih.gov/gene) integrates gene-specific information from multiple data sources. NCBI Reference Sequence (RefSeq) genomes for viruses, prokaryotes and eukaryotes are the primary foundation for Gene records in that they form the critical association between sequence and a tracked gene upon which additional functional and descriptive content is anchored. Additional content is integrated based on the genomic location and RefSeq transcript and protein sequence data. The content of a Gene record represents the integration of curation and automated processing from RefSeq, collaborating model organism databases, consortia such as Gene Ontology, and other databases within NCBI. Records in Gene are assigned unique, tracked integers as identifiers. The content (citations, nomenclature, genomic location, gene products and their attributes, phenotypes, sequences, interactions, variation details, maps, expression, homologs, protein domains and external databases) is available via interactive browsing through NCBIs Entrez system, via NCBIs Entrez programming utilities (E-Utilities and Entrez Direct) and for bulk transfer by FTP.

Cataloguing the HIV type 1 human protein interaction network.

Although many interactions between HIV-1 and human proteins have been reported in the scientific literature, no publicly accessible source for efficiently reviewing this information was available. Therefore, a project was initiated in an attempt to catalogue all published interactions between HIV-1 and human proteins. HIV-related articles in PubMed were used to develop a database containing names, Entrez GeneIDs, and RefSeq protein accession numbers of interacting proteins. Furthermore, brief descriptions of the interactions, PubMed identification numbers of articles describing the interactions, and keywords for searching the interactions were incorporated. Over 100,000 articles were reviewed, resulting in the identification of 1448 human proteins that interact with HIV-1 comprising 2589 unique HIV-1-to-human protein interactions. Preliminary analysis of the extracted data indicates 32% were direct physical interactions (e.g., binding) and 68% were indirect interactions (e.g., upregulation through activation of signaling pathways). Interestingly, 37% of human proteins in the database were found to interact with more than one HIV-1 protein. For example, the signaling protein mitogen-activated protein kinase 1 has a surprising range of interactions with 10 different HIV-1 proteins. Moreover, large numbers of interactions were published for the HIV-1 regulatory protein Tat and envelope proteins: 30% and 33% of total interactions identified, respectively. The database is accessible at http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/ and is cross-linked to other National Center for Biotechnology Information databases and programs via Entrez Gene. This database represents a unique and continuously updated scientific resource for understanding HIV-1 replication and pathogenesis to assist in accelerating the development of effective therapeutic and vaccine interventions.

Molecular profiling of clinical tissue specimens: feasibility and applications.

The relationship between gene expression profiles and cellular behavior in humans is largely unknown. Expression patterns of individual cell types have yet to be precisely measured, and, at present, we know or can predict the function of a relatively small percentage of genes. However, biomedical research is in the midst of an informational and technological revolution with the potential to increase dramatically our understanding of how expression modulates cellular phenotype and response to the environment. The entire sequence of the human genome will be known by the year 2003 or earlier. 1,2 In concert, the pace of efforts to complete identification and full-length cDNA sequencing of all genes has accelerated, and these goals will be attained within the next few years. 3-7 Accompanying the expanding base of genetic information are several new technologies capable of global gene expression measurements. 8-16 Taken together, the expanding genetic database and developing expression technologies are leading to an exciting new paradigm in biomedical research known as molecular profiling.

Molecular Profiling of Clinical Tissue Specimens : Feasibility and Applications

The relationship between gene expression profiles and cellular behavior in humans is largely unknown. Expression patterns of individual cell types have yet to be precisely measured, and, at present, we know or can predict the function of a relatively small percentage of genes. However, biomedical research is in the midst of an informational and technological revolution with the potential to increase dramatically our understanding of how expression modulates cellular phenotype and response to the environment. The entire sequence of the human genome will be known by the year 2003 or earlier. 1, 2 In concert, the pace of efforts to complete identification and full-length cDNA sequencing of all genes has accelerated, and these goals will be attained within the next few years. 3, 4, 5, 6, 7 Accompanying the expanding base of genetic information are several new technologies capable of global gene expression measurements. 8, 9, 10, 11, 12, 13, 14, 15, 16 Taken together, the expanding genetic database and developing expression technologies are leading to an exciting new paradigm in biomedical research known as molecular profiling.

The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency

The National Institutes of Health Genetic Testing Registry (GTR; available online at http://www.ncbi.nlm.nih.gov/gtr/) maintains comprehensive information about testing offered worldwide for disorders with a genetic basis. Information is voluntarily submitted by test providers. The database provides details of each test (e.g. its purpose, target populations, methods, what it measures, analytical validity, clinical validity, clinical utility, ordering information) and laboratory (e.g. location, contact information, certifications and licenses). Each test is assigned a stable identifier of the format GTR000000000, which is versioned when the submitter updates information. Data submitted by test providers are integrated with basic information maintained in National Center for Biotechnology Information’s databases and presented on the web and through FTP (ftp.ncbi.nih.gov/pub/GTR/_README.html).

HIV-1, human interaction database: current status and new features

The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Interaction Database’, available through the National Library of Medicine at http://www.ncbi.nlm.nih.gov/genome/viruses/retroviruses/hiv-1/interactions, serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. Each HIV-1 human protein interaction can be retrieved without restriction by web-based downloads and ftp protocols and includes: Reference Sequence (RefSeq) protein accession numbers, National Center for Biotechnology Information Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. In addition to specific HIV-1 protein–human protein interactions, included are interaction effects upon HIV-1 replication resulting when individual human gene expression is blocked using siRNA. A total of 3142 human genes are described participating in 12 786 protein–protein interactions, along with 1316 replication interactions described for each of 1250 human genes identified using small interfering RNA (siRNA). Together the data identifies 4006 human genes involved in 14 102 interactions. With the inclusion of siRNA interactions we introduce a redesigned web interface to enhance viewing, filtering and downloading of the combined data set.

ClinVar: improving access to variant interpretations and supporting evidence

Abstract ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant (‘provider interpretation’) or from groups such as patient registries that primarily provide phenotypic information from patients (‘phenotyping only’). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.