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The Epigenomics resource at the National Center for Biotechnology Information (NCBI) has been created to serve as a comprehensive public repository for whole-genome epigenetic data sets (www.ncbi.nlm.nih.gov/epigenomics). We have constructed this resource by selecting the subset of epigenetics-specific data from the Gene Expression Omnibus (GEO) database and then subjecting them to further review and annotation. Associated data tracks can be viewed using popular genome browsers or downloaded for local analysis. We have performed extensive user testing throughout the development of this resource, and new features and improvements are continuously being implemented based on the results. We have made substantial usability improvements to user interfaces, enhanced functionality, made identification of data tracks of interest easier and created new tools for preliminary data analyses. Additionally, we have made efforts to enhance the integration between the Epigenomics resource and other NCBI databases, including the Gene database and PubMed. Data holdings have also increased dramatically since the initial publication describing the NCBI Epigenomics resource and currently consist of >3700 viewable and downloadable data tracks from 955 biological sources encompassing five well-studied species. This updated manuscript highlights these changes and improvements.

The Epigenomics database at the National Center for Biotechnology Information (NCBI) is a new resource that has been created to serve as a comprehensive public resource for whole-genome epigenetic data sets (www.ncbi.nlm.nih.gov/epigenomics). Epigenetics is the study of stable and heritable changes in gene expression that occur independently of the primary DNA sequence. Epigenetic mechanisms include post-translational modifications of histones, DNA methylation, chromatin conformation and non-coding RNAs. It has been observed that misregulation of epigenetic processes has been associated with human disease. We have constructed the new resource by selecting the subset of epigenetics-specific data from general-purpose archives, such as the Gene Expression Omnibus, and Sequence Read Archives, and then subjecting them to further review, annotation and reorganization. Raw data is processed and mapped to genomic coordinates to generate ‘tracks’ that are a visual representation of the data. These data tracks can be viewed using popular genome browsers or downloaded for local analysis. The Epigenomics resource also provides the user with a unique interface that allows for intuitive browsing and searching of data sets based on biological attributes. Currently, there are 69 studies, 337 samples and over 1100 data tracks from five well-studied species that are viewable and downloadable in Epigenomics.

We present the completed dataset and clone repository of the Cancer Chromosome Aberration Project (CCAP), an initiative developed and funded through the intramural program of the U.S. National Cancer Institute, to provide seamless linkage of human cytogenetic markers with the primary nucleotide sequence of the human genome. Spaced at 1-2 Mb intervals across the human genome, 1,339 bacterial artificial chromosome (BAC) clones have been localized to chromosomal bands through high-resolution fluorescence in situ hybridization (FISH) mapping. Of these clones, 99.8% can be positioned on the primary human genome sequence and 95% are placed at or close to their precise nucleotide starts and stops. This dataset can be studied and manipulated within generally available public Web sites. The clones are available from a commercial repository. The CCAP BAC clone set provides anchors for the interrogation of gene and sequence involvement in oncogenic and developmental disorders when the starting point is the recognition of a structural, numerical, or interstitial chromosomal aberration. This dataset also provides a current view of the quality and coherence of the available genome sequence and insight into the nucleotide and three-dimensional structures that manifest as Giemsa light and dark chromosomal banding patterns.

The human genome is by far the largest genome to be sequenced, and its size and complexity present many challenges for sequence assembly. The International Human Genome Sequencing Consortium constructed a map of the whole genome to enable the selection of clones for sequencing and for the accurate assembly of the genome sequence. Here we report the construction of the whole-genome bacterial artificial chromosome (BAC) map and its integration with previous landmark maps and information from mapping efforts focused on specific chromosomal regions. We also describe the integration of sequence data with the map.

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.

To date, despite the increasing number of genomic tools, there is no repository of ordered human BAC clones that covers entire chromosomes. This project presents a resource of mapped large DNA fragments that span eight human chromosomes at ∼1-Mb resolution. These DNA fragments are bacterial artificial chromosome (BAC) clones anchored to sequence tagged site (STS) markers. This clone collection, which currently contains 759 mapped clones, is useful in a wide range of applications from microarray-based gene mapping to identification of chromosomal mutations. In addition to the clones themselves, we describe a database, GenMapDB (http://genomics.med.upenn.edu/genmapdb), that contains information about each clone in our collection.

Microarray technology makes it possible to simultaneously study the expression of thousands of genes during a single experiment. We have developed an information system, ArrayDB, to manage and analyse large-scale expression data. The underlying relational database was designed to allow flexibility in the nature and structure of data input and also in the generation of standard or customized reports through a web-browser interface. ArrayDB provides varied options for data retrieval and analysis tools that should facilitate the interpretation of complex hybridization results. A sampling of ArrayDB storage, retrieval and analysis capabilities is available ( http://www.nhgri.nih.gov/DIR/LCG/15K/HTML/ ), along with information on a set of approximately 15,000 genes used to fabricate several widely used microarrays. Information stored in ArrayDB is used to provide integrated gene expression reports by linking array target sequences with NCBI's Entrez retrieval system, UniGene and KEGG pathway views. The integration of external information resources is essential in interpreting intrinsic patterns and relationships in large-scale gene expression data.

The highly specific and sensitive PCR provides the basis for sequence-tagged sites (STSs), unique landmarks that have been used widely in the construction of genetic and physical maps of the human genome. Electronic PCR (e-PCR) refers to the process of recovering these unique sites in DNA sequences by searching for subsequences that closely match the PCR primers and have the correct order, orientation, and spacing that they could plausibly prime the amplification of a PCR product of the correct molecular weight. A software tool was developed to provide an efficient implementation of this search strategy and allow the sort of en masse searching that is required for modern genome analysis. Some sample searches were performed to demonstrate a number of factors that can affect the likelihood of obtaining a match. Analysis of one large sequence database record revealed the presence of several microsatellite and gene-based markers and allowed the exact base-pair distances among them to be calculated. This example provides a demonstration of how e-PCR can be used to integrate the growing body of genomic sequence data with existing maps, reveal relationships among markers that existed previously on different maps, and correlate genetic distances with physical distances.

The human genome is thought to harbor 50,000 to 100,000 genes, of which about half have been sampled to date in the form of expressed sequence tags. An international consortium was organized to develop and map gene-based sequence tagged site markers on a set of two radiation hybrid panels and a yeast artificial chromosome library. More than 16,000 human genes have been mapped relative to a framework map that contains about 1000 polymorphic genetic markers. The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease. The integrated resource is available through a site on the World Wide Web at http://www.ncbi.nlm.nih.gov/SCIENCE96/.

Multiple sequence alignment can be a useful technique for studying molecular evolution, as well as for analyzing relationships between structure or function and primary sequence. We have developed for this purpose an interactive program, MACAW (Multiple Alignment Construction and Analysis Workbench), that allows the user to construct multiple alignments by locating, analyzing, editing, and combining "blocks" of aligned sequence segments. MACAW incorporates several novel features. (1) Regions of local similarity are located by a new search algorithm that avoids many of the limitations of previous techniques. (2) The statistical significance of blocks of similarity is evaluated using a recently developed mathematical theory. (3) Candidate blocks may be evaluated for potential inclusion in a multiple alignment using a variety of visualization tools. (4) A user interface permits each block to be edited by moving its boundaries or by eliminating particular segments, and blocks may be linked to form a composite multiple alignment. No completely automatic program is likely to deal effectively with all the complexities of the multiple alignment problem; by combining a powerful similarity search algorithm with flexible editing, analysis and display tools, MACAW allows the alignment strategy to be tailored to the problem at hand.

A map of 30,181 human gene–based markers was assembled and integrated with the current genetic map by radiation hybrid mapping. The new gene map contains nearly twice as many genes as the previous release, includes most genes that encode proteins of known function, and is twofold to threefold more accurate than the previous version. A redesigned, more informative and functional World Wide Web site ( www.ncbi.nlm.nih.gov/genemap ) provides the mapping information and associated data and annotations. This resource constitutes an important infrastructure and tool for the study of complex genetic traits, the positional cloning of disease genes, the cross-referencing of mammalian genomes, and validated human transcribed sequences for large-scale studies of gene expression.

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, PubMed, PubMed Central, LocusLink, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SARS Coronavirus Resource, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, PubMed, PubMed Central (PMC), LocusLink, the NCBITaxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR (e-PCR), Open Reading Frame (ORF) Finder, References Sequence (RefSeq), UniGene, HomoloGene, ProtEST, Database of Single Nucleotide Polymorphisms (dbSNP), Human/Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker (MM), Evidence Viewer (EV), Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.

The National Institutes of Health Mammalian Gene Collection (MGC) Program is a multiinstitutional effort to identify and sequence a cDNA clone containing a complete ORF for each human and mouse gene. ESTs were generated from libraries enriched for full-length cDNAs and analyzed to identify candidate full-ORF clones, which then were sequenced to high accuracy. The MGC has currently sequenced and verified the full ORF for a nonredundant set of >9,000 human and >6,000 mouse genes. Candidate full-ORF clones for an additional 7,800 human and 3,500 mouse genes also have been identified. All MGC sequences and clones are available without restriction through public databases and clone distribution networks (see http://mgc.nci.nih.gov ).

We have placed 7,600 cytogenetically defined landmarks on the draft sequence of the human genome to help with the characterization of genes altered by gross chromosomal aberrations that cause human disease. The landmarks are large-insert clones mapped to chromosome bands by fluorescence in situ hybridization. Each clone contains a sequence tag that is positioned on the genomic sequence. This genome-wide set of sequence-anchored clones allows structural and functional analyses of the genome. This resource represents the first comprehensive integration of cytogenetic, radiation hybrid, linkage and sequence maps of the human genome; provides an independent validation of the sequence map1,2 and framework for contig order and orientation; surveys the genome for large-scale duplications, which are likely to require special attention during sequence assembly; and allows a stringent assessment of sequence differences between the dark and light bands of chromosomes. It also provides insight into large-scale chromatin structure and the evolution of chromosomes and gene families and will accelerate our understanding of the molecular bases of human disease and cancer. Supplementary information The online version of this article (doi:10.1038/35057192) contains supplementary material, which is available to authorized users.

Gene expression quantifying techniques promise to shape our understanding of the distribution and regulation of the products of transcription in normal and abnormal cell types. cDNA microarray (DeRisi 1997), high-density oligo DNA array (Wodicka 1997) and serial analysis of gene expression (Velculescu 1995) techniques have all been developed to quickly and efficiently survey genome-wide transcript expression. However, each of these techniques has the potential to produce, in a single experiment, vast amounts of data which must be sifted and ordered for useful information to become apparent. Additional challenges are met when attempts are made to compare, merge and contrast data from experiments conducted under differing conditions and locales. As a prototype for the handling, analysis and exchange of gene expression data in the public forum, we have undertaken the production of a public repository and resource for a particular set of gene expression data, i.e., serial analysis of gene expression (SAGE) data. This repository was designed initially to archive SAGE data produced through the Cancer Genome Anatomy Project (CGAP) (Strausberg 1997; http://www.ncbi.nlm.nih.gov/cgap) but is now capable of accepting submissions of SAGE sequence data from any source, without fee or restriction on dissemination or use. It is our goal to provide free and open access to raw SAGE sequence data, precomputed tag extractions, and several modest analysis tools. This resource currently contains over two million tags from 47 SAGE libraries. We call this resource SAGEmap. Its two online components are available via the World Wide Web (http://www.ncbi.nlm.nih.gov/sage) and anonymous FTP (ftp://ncbi.nlm.nih.gov/pub/sage).

This paper describes a fast and scalable strategy for constructing a radiation hybrid (RH) map from data on different RH panels. The maps on each panel are then integrated to produce a single RH map for the genome. Recurring problems in using maps from several sources are that the maps use different markers, the maps do not place the overlapping markers in same order, and the objective functions for map quality are incomparable. We use methods from combinatorial optimization to develop a strategy that addresses these issues. We show that by the standard objective functions of obligate chromosome breaks and maximum likelihood, software for the traveling salesman problem produces RH maps with better quality much more quickly than using software specifically tailored for RH mapping. We use known algorithms for the longest common subsequence problem as part of our map integration strategy. We demonstrate our methods by reconstructing and integrating maps for markers typed on the Genebridge 4 (GB4) and the Stanford G3 panels publicly available from the RH database. We compare map quality of our integrated map with published maps for GB4 panel and G3 panel by considering whether markers occur in the same order on a map and in DNA sequence contigs submitted to GenBank. We find that all of the maps are inconsistent with the sequence data for at least 50% of the contigs, but our integrated maps are more consistent. The map integration strategy not only scales to multiple RH maps but also to any maps that have comparable criteria for measuring map quality. Our software improves on current technology for doing RH mapping in areas of computation time and algorithms for considering a large number of markers for mapping. The essential impediments to producing dense high-quality RH maps are data quality and panel size, not computation.

A crucial event in the history of the Human Genome Project was the decision to use sequence-tagged sites (STSs) as common landmarks for genomic mapping. Following several years of constructing STS-based maps of ever-increasing detail, the emphasis has recently shifted towards large-scale genomic sequencing. A computational procedure called 'electronic PCR' allows STS landmarks to be revealed as data emerge from the sequencing pipeline, thereby bridging the gap between mapping and sequencing activities.

Publisher Summary Entrez is a biomedical information resource that has been designed to facilitate the discovery process by providing connections among biological sequences, molecular structures, and abstracts. Because it must be anticipated that the amount of data will continue to grow at phenomenal rates, the Internet would seem to be the most practical medium for the future dissemination of this information. However, besides these quantitative changes, several trends promise to alter qualitatively the nature of the nucleotide sequence database. It is necessary to be prepared for the expected volume of data, but changes to the Entrez user interface may also be needed to make effective use of it. For example, imagine finding a sequence of interest and asking for its sequence neighbors only to be presented with a complete chromosome sequence. A new graphical viewer in Entrez will allow the user to view the genomic landscape from different vantage points and make connections to the sequences, structures, and abstracts relevant to specific chromosomal regions.

A crotonyl-CoA reductase (EC 1.3.1.38, acyl-CoA:NADP+ trans-2-oxidoreductase) catalyzing the conversion of crotonyl-CoA to butyryl-CoA has been purified and characterized from Streptomyces collinus. This enzyme, a dimer with subunits of identical mass (48 kDa), exhibits a Km = 18 microM for crotonyl-CoA and 15 microM for NADPH. The enzyme was unable to catalyze the reduction of any other enoyl-CoA thioesters or to utilize NADH as an electron donor. A highly effective inhibition by straight-chain fatty acids (Ki = 9.5 microM for palmitoyl-CoA) compared with branched-chain fatty acids (Ki400 microM for isopalmitoyl-CoA) was observed. All of these properties are consistent with a proposed role of the enzyme in providing butyryl-CoA as a starter unit for straight-chain fatty acid biosynthesis. The crotonyl-CoA reductase gene was cloned in Escherichia coli. This gene, with a proposed designation of ccr, is encoded in a 1344-bp open reading frame which predicts a primary translation product of 448 amino acids with a calculated molecular mass of 49.4 kDa. Several dispersed regions of highly significant sequence similarity were noted between the deduced amino acid sequence and various alcohol dehydrogenases and fatty acid synthases, including one region that contains a putative NADPH binding site. The ccr gene product was expressed in E. coli and the induced crotonyl-CoA reductase was purified tenfold and shown to have similar steady-state kinetics and electrophoretic mobility on sodium dodecyl sulfate/polyacrylamide to the native protein.

Regulation of mRNA turnover has emerged as an important control point in lymphokine and oncogene expression. We have studied a monocytic tumor in which activation of GM-CSF expression results from the constitutive stabilization of the normally short-lived GM-CSF mRNA. Linkage of the germ-line 3' untranslated region of the GM-CSF gene to a neo reporter gene demonstrated that mRNA stabilization is mediated by a tumor-specific trans-acting factor(s), rather than by an alteration of the GM-CSF gene itself. Significantly, similar fusions of the c-myc and c-fos 3' untranslated regions to neo yielded mRNAs that turned over rapidly in all cells, including the tumor cells. These results demonstrate that AU-rich mRNA turnover signals are recognized differentially in trans within the same cell.

Rearrangement or deregulation of the c-myc gene has been observed in a variety of tumors and transformed cell lines (reviewed by Cole, 1986). Yet, the normal function or the exact contribution of c-myc in tumorigenesis remains controversial. We have recently described a tumor system in which a c-myc retrovirus induces monocyte/macrophage tumors in pristane treated BALB/c mice with very high frequency (Baumbach et al., 1986). This system has enabled us to begin dissecting the molecular changes during c-myc induced transformation of monocytes in vivo. Expression of c-myc alone is insufficient for full tumorigenicity, and as in the case of ras cooperativity (Land et al., 1983, Ruley et al., 1983), collaboration of a second genetic activation appears to be necessary. We have shown that in at least one monocyte tumor (tumor 7.1.3), a change involving the CSF-1 gene has occurred (Baumbach et al., 1987). In this tumor an endogenous ecotropic virus has integrated just upstream of the CSF-1 gene, thus activating production of CSF-1. This tumor now grows by an autocrine mechanism. Indeed all of the tumors have aquired a degree of autonomy, and so do not require CSF-1 for growth.

The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is 'to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community'. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.