Providing Access to Genomic Variant Knowledge in a Healthcare Setting: A Vision for the ClinGen Electronic Health Records Workgroup.

The Clinical Genome Resource (ClinGen) is a National Institutes of Health (NIH)-funded collaborative program that brings together a variety of projects designed to provide high-quality, curated information on clinically relevant genes and variants. ClinGen's EHR (Electronic Health Record) Workgroup aims to ensure that ClinGen is accessible to providers and patients through EHR and related systems. This article describes the current scope of these efforts and progress to date. The ClinGen public portal can be accessed at www.clinicalgenome.org.

Expressions of hepatic genes, especially IGF-binding protein-1, correlating with serum corticosterone in microarray analysis.

Microarray technology was evaluated for usefulness in assessing relationships between serum corticosterone and hepatic gene expression. Nine pairs of female Swiss mice were chosen to provide a wide range of serum corticosterone ratios; cDNA microarray analysis (approximately 8000 genes) was performed on their livers. A statistical method based on calculation of 99% confidence intervals discovered 32 genes which varied significantly among the livers. Five of these ratios correlated significantly with serum corticosterone ratio, including tyrosine aminotransferase, stress-induced protein, pleiotropic regulator 1 and insulin-like growth factor-binding protein-1; the latter has a potential role in cancer development. Secondly, linear regression of gene expression vs corticosterone ratios was screened for those with r> or =0.8 (P<0.01), yielding 141 genes, including some known to be corticosterone regulated and others of interest as possible glucocorticoid targets. Half of these significant correlations involved data sets where no microarray ratio exceeded +/- 1.5. These results showed that microarray may be used to survey tissues for changes in gene expression related to serum hormones, and that even small changes in expression can be of statistical significance in a study with adequate numbers of replicate samples.

The Gene Ontology (GO) database and informatics resource.

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.

Visualization of expression clusters using Sammon's non-linear mapping.

A method of exploratory analysis and visualization of multi-dimensional gene expression data using Sammon's Non-Linear Mapping (NLM) is presented.

Genome comparisons highlight similarity and diversity within the eukaryotic kingdoms.

In 2000, the number of completely sequenced eukaryotic genomes increased to four. The addition of Drosophila and Arabidopsis into this cohort permits additional insights into the processes that have shaped evolution. Analysis and comparisons of both completed genomes and partially sequenced genomes have already shed light on mechanisms such as gene duplication and gene loss that have long been hypothesized to be major forces in speciation. Indeed, duplicate gene pairs in Saccharomyces, Arabidopsis, Caenorhabditis and Drosophila are high: 30%, 60%, 48% and 40%, respectively. Evidence of horizontal gene-transfer, thought to be a major evolutionary force in bacteria, has been found in Arabidopsis. The release of the 'first draft' of the human genome sequence in 2000 heralds a new stage of biological study. Understanding the as-yet-unannotated human genome will be largely based on conclusions, techniques and tools developed during the analysis and comparison of the genome of these four model organisms.

Saccharomyces Genome Database provides tools to survey gene expression and functional analysis data.

Upon the completion of the SACCHAROMYCES: cerevisiae genomic sequence in 1996 [Goffeau,A. et al. (1997) NATURE:, 387, 5], several creative and ambitious projects have been initiated to explore the functions of gene products or gene expression on a genome-wide scale. To help researchers take advantage of these projects, the SACCHAROMYCES: Genome Database (SGD) has created two new tools, Function Junction and Expression Connection. Together, the tools form a central resource for querying multiple large-scale analysis projects for data about individual genes. Function Junction provides information from diverse projects that shed light on the role a gene product plays in the cell, while Expression Connection delivers information produced by the ever-increasing number of microarray projects. WWW access to SGD is available at genome-www.stanford. edu/Saccharomyces/.

The Stanford Microarray Database.

The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77-80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73-76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10-14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332-333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45-48] and can be accessed at http://genome-www.stanford.edu/microarray.

Characteristics of amino acids.

This appendix presents useful basic information, including common abbreviations, useful measurements and data, characteristics of amino acids and nucleic acids, information on radioactivity and the safe use of radioisotopes and other hazardous chemicals, conversions for centrifuges and rotors, characteristics of common detergents, and common conversion factors.

Computer manipulation of DNA and protein sequences.

This unit outlines a variety of methods by which DNA sequences can be manipulated by computers. Procedures for entering sequence data into the computer and assembling raw sequence data into a contiguous sequence are described first, followed by a description of methods of analyzing and manipulating sequences--e.g., verifying sequences, constructing restriction maps, designing oligonucleotides, identifying protein-coding regions, and predicting secondary structures. This unit also provides information on the large amount of software available for sequence analysis. The appendix to this unit lists some of the commercial software, shareware, and free software related to DNA sequence manipulation. The goal of this unit is to serve as a starting point for researchers interested in utilizing the tremendous sequencing resources available to the computer-knowledgeable molecular biology laboratory.

Comparative genomics of the eukaryotes.

A comparative analysis of the genomes of Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae-and the proteins they are predicted to encode-was undertaken in the context of cellular, developmental, and evolutionary processes. The nonredundant protein sets of flies and worms are similar in size and are only twice that of yeast, but different gene families are expanded in each genome, and the multidomain proteins and signaling pathways of the fly and worm are far more complex than those of yeast. The fly has orthologs to 177 of the 289 human disease genes examined and provides the foundation for rapid analysis of some of the basic processes involved in human disease.

Integrating functional genomic information into the Saccharomyces genome database.

The Saccharomyces Genome Database (SGD) stores and organizes information about the nearly 6200 genes in the yeast genome. The information is organized around the 'locus page' and directs users to the detailed information they seek. SGD is endeavoring to integrate the existing information about yeast genes with the large volume of data generated by functional analyses that are beginning to appear in the literature and on web sites. New features will include searches of systematic analyses and Gene Summary Paragraphs that succinctly review the literature for each gene. In addition to current information, such as gene product and phenotype descriptions, the new locus page will also describe a gene product's cellular process, function and localization using a controlled vocabulary developed in collaboration with two other model organism databases. We describe these developments in SGD through the newly reorganized locus page. The SGD is accessible via the WWW at http://genome-www.stanford.edu/Saccharomyces/

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

The Saccharomyces Genome Database (SGD) collects and organizes information about the molecular biology and genetics of the yeast Saccharomyces cerevisiae. The latest protein structure and comparison tools available at SGD are presented here. With the completion of the yeast sequence and the Caenorhabditis elegans sequence soon to follow, comparison of proteins from complete eukaryotic proteomes will be an extremely powerful way to learn more about a particular protein's structure, its function, and its relationships with other proteins. SGD can be accessed through the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/

Unified display of Arabidopsis thaliana physical maps from AtDB, the A.thaliana database.

In the past several years, there has been a tremendous effort to construct physical maps and to sequence the genome of Arabidopsis thaliana. As a result, four of the five chromosomes are completely covered by overlapping clones except at the centromeric and nucleolus organizer regions (NOR). In addition, over 30% of the genome has been sequenced and completion is anticipated by the end of the year 2000. Despite these accomplishments, the physical maps are provided in many formats on laboratories' Web sites. These data are thus difficult to obtain in a coherent manner for researchers. To alleviate this problem, AtDB (Arabidopsis thaliana DataBase, URL: http://genome-www.stanford.edu/Arabidopsis/) has constructed a unified display of the physical maps where all publicly available physical-map data for all chromosomes are presented through the Web in a clickable, 'on-the-fly' graphic, created by CGI programs that directly consult our relational database.

Comparison of the complete protein sets of worm and yeast: orthology and divergence.

Comparative analysis of predicted protein sequences encoded by the genomes of Caenorhabditis elegans and Saccharomyces cerevisiae suggests that most of the core biological functions are carried out by orthologous proteins (proteins of different species that can be traced back to a common ancestor) that occur in comparable numbers. The specialized processes of signal transduction and regulatory control that are unique to the multicellular worm appear to use novel proteins, many of which re-use conserved domains. Major expansion of the number of some of these domains seen in the worm may have contributed to the advent of multicellularity. The proteins conserved in yeast and worm are likely to have orthologs throughout eukaryotes; in contrast, the proteins unique to the worm may well define metazoans.

Arabidopsis thaliana: a model plant for genome analysis.

Arabidopsis thaliana is a small plant in the mustard family that has become the model system of choice for research in plant biology. Significant advances in understanding plant growth and development have been made by focusing on the molecular genetics of this simple angiosperm. The 120-megabase genome of Arabidopsis is organized into five chromosomes and contains an estimated 20,000 genes. More than 30 megabases of annotated genomic sequence has already been deposited in GenBank by a consortium of laboratories in Europe, Japan, and the United States. The entire genome is scheduled to be sequenced by the end of the year 2000. Reaching this milestone should enhance the value of Arabidopsis as a model for plant biology and the analysis of complex organisms in general.

AtDB, the Arabidopsis thaliana database, and graphical-web-display of progress by the Arabidopsis Genome Initiative.

AtDB, the Arabidopsis thaliana Database, has a primary role to provide public access to the collected genomic information for A. thaliana via the World Wide Web (URL: http://genome-www.stanford. edu/ ). AtDB presents interactive physical and genetics maps that are hyperlinked with detailed information about the clones and markers placed on these maps. A large literature collection on Arabidopsis , contact information on researchers worldwide, laboratory method manuals and other information useful to plant molecular biologists are also provided. This paper discusses the database-driven clickable displays that provide easy navigation within a variety of genomic maps, including those summarizing progress of the international Arabidopsis genomic sequencing effort, AGI (the Arabidopsis Genome Initiative). The interface uses client-side hyperlinked GIF-images that direct the user to detailed database-information. A new BLAST service is also described. This gives users access to the thousands of Arabidopsis BAC clone end-sequences and includes hyperlinked images summarizing the search results. The linking of genetic and physically mapped regions and their sequence into information for loci within that region is an ongoing goal for this project.

SGD: Saccharomyces Genome Database.

The Saccharomyces Genome Database (SGD) provides Internet access to the complete Saccharomyces cerevisiae genomic sequence, its genes and their products, the phenotypes of its mutants, and the literature supporting these data. The amount of information and the number of features provided by SGD have increased greatly following the release of the S.cerevisiae genomic sequence, which is currently the only complete sequence of a eukaryotic genome. SGD aids researchers by providing not only basic information, but also tools such as sequence similarity searching that lead to detailed information about features of the genome and relationships between genes. SGD presents information using a variety of user-friendly, dynamically created graphical displays illustrating physical, genetic and sequence feature maps. SGD can be accessed via the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/

Expanding yeast knowledge online.

The completion of the Saccharomyces cerevisiae genome sequencing project and the continued development of improved technology for large-scale genome analysis have led to tremendous growth in the amount of new yeast genetics and molecular biology data. Efficient organization, presentation, and dissemination of this information are essential if researchers are to exploit this knowledge. In addition, the development of tools that provide efficient analysis of this information and link it with pertinent information from other systems is becoming increasingly important at a time when the complete genome sequences of other organisms are becoming available. The aim of this review is to familiarize biologists with the type of data resources currently available on the World Wide Web (WWW).