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It has been four years since the original publication of the draft sequence of the rat genome. Five groups are now working together to assemble, annotate and release an updated version of the rat genome. As the prevailing model for physiology, complex disease and pharmacological studies, there is an acute need for the rat's genomic resources to keep pace with the rat's prominence in the laboratory. In this commentary, we describe the current status of the rat genome sequence and the plans for its impending 'upgrade'. We then cover the key online resources providing access to the rat genome, including the new SNP views at Ensembl, the RefSeq and Genes databases at the US National Center for Biotechnology Information, Genome Browser at the University of California Santa Cruz and the disease portals for cardiovascular disease and obesity at the Rat Genome Database.

The Rat Genome Database (RGD, http://rgd.mcw.edu) is one of the core resources for rat genomics and recent developments have focused on providing support for disease-based research using the rat model. Recognizing the importance of the rat as a disease model we have employed targeted curation strategies to curate genes, QTL and strain data for neurological and cardiovascular disease areas. This work has centered on rat but also includes data for mouse and human to create ‘disease portals’ that provide a unified view of the genes, QTL and strain models for these diseases across the three species. The disease curation efforts combined with normal curation activities have served to greatly increase the content of the database, particularly for biological information, including gene ontology, disease, pathway and phenotype ontology annotations. In addition to improving the features and database content, community outreach has been expanded to demonstrate how investigators can leverage the resources at RGD to facilitate their research and to elicit suggestions and needs for future developments. We have published a number of papers that provide additional information on the ontology annotations and the tools at RGD for data mining and analysis to better enable researchers to fully utilize the database.

The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease.

Integration of the large variety of genome maps from several organisms provides the mechanism by which physiological knowledge obtained in model systems such as the rat can be projected onto the human genome to further the research on human disease. The release of the rat genome sequence provides new information for studies using the rat model and is a key reference against which existing and new rat physiological results can be aligned. Previously, we described comparative maps of the rat, mouse, and human based on EST sequence comparisons combined with radiation hybrid maps. Here, we use new data and introduce the Integrated Genomics Environment, an extensive database of curated and integrated maps, markers, and physiological results. These results are integrated by using VCMapview, a java-based map integration and visualization tool. This unique environment allows researchers to relate results from cytogenetic, genetic, and radiation hybrid studies to the genome sequence and compare regions of interest between human, mouse, and rat. Integrating rat physiology with mouse genetics and clinical results from human by using the respective genomes provides a novel route to capitalize on comparative genomics and the strengths of model organism biology.

Over the past 200 years, animal models have been selected and used primarily as surrogates for humans. The primary selection criteria for the animal models have been disease-based phenotypic characteristic(s) similar to those of humans. Indeed, many rat and mouse models share pathobiological characteristics similar to a human condition (Desnick et al. 1982). The idea that genomic organization also tends to be evolutionarily conserved between species was postulated in the early 1900s (Castle and Wachter 1924; Haldane 1927). Studies involving banding conservation and chromosome painting (ZOO-FISH) have since shown that large stretches of DNA are conserved in mammalian species as divergent as humans and fin whales (Nash and O'Brien 1982; Sawyer and Hozier 1986; Scherthan et al. 1994; Weinberg and Stanyon 1995). Although these studies showed genome conservation, they could not show the explicit conserved gene order at high resolution; such detail can only be accomplished at the genetic/physical mapping or sequence level. Several studies evaluating genome conservation at the genetic and physical mapping level have determined that gene order does tend to be conserved between mammals (Oakey et al. 1992; Sellar et al. 1994; Stubbs et al. 1994), opening up the prospect of constructing comparative maps between multiple species based on genetic sequence and map information (Nadeau 1989; Anderson et al. 1996; DeBry and Seldin 1996; Lyons 1997). As genetic and physical maps of human and model organisms developed with the advent of the Human Genome Project in the 1990s and as the number of identified genes increased, the number of possible integration points dramatically enhanced the potential quality and density of comparative maps (O'Brien et al. 1999). The increased number of mapped genes and expressed sequence tag (EST) sites has led to sequence comparisons to identify orthologous genes (homologous genes in different species evolving from the same common ancestral gene; Clark 1999; Fitch 2000). When mapped in both species, these orthologs serve as anchors that are useful in identifying conserved segments between species. However, until absolute phylogeny of the genes is truly known, the ortholog assignments between these species must be considered preliminary; thus, it is prudent to assign gene-based anchors using the more conservative homolog relationships. The Mouse Genome Informatics (MGI) group at The Jackson Laboratories (http://www.informatics.jax.org/; Blake et al. 2000) has curated and assigned 2105 rat-mouse (R-M), 1950 rat-human (R-H), and 5603 mouse-human (M-H) orthologs. However, fewer of these genes have been mapped across all three species, limiting the number of anchors for building comparative maps. Several lower-resolution comparative maps have been generated between rat, mouse, and human using fluorescence in situ hybridization (Levan et al. 1991; Scalzi and Hozier 1998; Grutzner et al. 1999) and combined genetic/radiation hybrid (RH) maps (Watanabe et al. 1999), the later identifying 522 anchor points between rat and human and/or mouse. The combined genetic/RH maps identified 41 conserved segments (identified by containing at least two homologous genes) between rat and mouse and 89 between rat and human (Watanabe et al. 1999). Using the analytical methodology developed by Nadeau and Taylor (1984), Watanabe et al. (1999) predicted the number of evolutionarily conserved segments between rat and human to be 152+21 and between rat and mouse to be 49+7. The emergence of the RH maps in human, rat, and mouse (Gyapay et al. 1996; Steen et al. 1999; VanEtten et al. 1999), coupled with the development of large numbers of UniGenes and ESTs for all three species, has revolutionized the way comparative maps can be built and maintained, before the complete genome sequencing of all three species. Indeed, the mapping approach described here can easily be extended to other mammals with significant EST libraries and RH maps and with entire genome sequences that will not likely be determined. There are many advantages of using the RH maps over curated or integrated genetic maps. First, RH mapping facilitates the integration of genetic markers, genes, and ESTs onto a single backbone map. Second, anchor (homology and map) assignments (based on sequence alignment, UniGene assemblies of ESTs, and map information) between species provide large numbers of hooks on and between the RH maps of rat, mouse, and human, which are useful for further sequence-based annotation of finished sequence from any source and, in particular, annotation of gene function based on results in animal models. Finally, the backbone of the maps has been developed and constructed using sequence-based comparison assignments coupled to a sophisticated scoring algorithm to choose the most likely homologies, thus providing an algorithm for de novo construction of comparative maps as the fundamental EST, gene assembly (UniGene or other), and RH map data sets mature. As the genomic sequence for human and mouse are in finishing and the sequencing of the rat is underway (Marshall 2000; Pennisi 2000a,b), such an RH-based scaffold becomes a powerful tool for early rat physical mapping, sequencing, and annotation of function. Comparative maps as described here provide a powerful platform for the integration of physiological and pharmacological information in the rat with genetic information in the mouse and clinical information in the human.

The Rat Genome Database (RGD, http://rgd.mcw.edu) was developed to provide a core resource for rat researchers combining genetic, genomic, pathway, phenotype and strain information with a focus on disease. RGD users are provided with access to structured and curated data from the molecular level through to the level of the whole organism, including the variations associated with disease phenotypes. To fully support use of the rat as a translational model for biological systems and human disease, RGD continues to curate these datasets while enhancing and developing tools to allow efficient and effective access to the data in a variety of formats including linear genome viewers, pathway diagrams and biological ontologies. To support pathophysiological analysis of data, RGD Disease Portals provide an entryway to integrated gene, QTL and strain data specific to a particular disease. In addition to tool and content development and maintenance, RGD promotes rat research and provides user education by creating and disseminating tutorials on the curated datasets, submission processes, and tools available at RGD. By curating, storing, integrating, visualizing and promoting rat data, RGD ensures that the investment made into rat genomics and genetics can be leveraged by all interested investigators.

The laboratory rat, Rattus norvegicus, is an important model of human health and disease, and experimental findings in the rat have direct relevance to human-based research. The Rat Genome Database (RGD, http://rgd.mcw.edu) is a model-organism database that provides access to wide variety of curated rat data such as genes and their homologs, quantitative trait loci, phenotypes, comparative mapping, and genome analysis. We present an overview of the database followed by specific examples that can be used to gain experience in employing RGD to explore the wealth of functional data available for the rat. We show how to make associations with the genome and use comparative tools to link the rat with human and mouse in order to integrate results from these three species of critical biomedical importance. Keywords: Rat; database; quantitative trait; ontology; comparative genomics; genome sequence

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

The Center for Eukaryotic Structural Genomics (CESG) produces and solves the structures of proteins from eukaryotes. We have developed and operate a pipeline to both solve structures and to test new methodologies. Both NMR and X-ray crystallography methods are used for structure solution. CESG chooses targets based on sequence dissimilarity to known structures, medical relevance, and nominations from members of the scientific community. Many times proteins qualify in more than one of these categories. Here we review some of the structures that have connections to human health and disease.

For most systems in biology, a large body of literature exists that describes the complexity of the system based on experimental results. Manual review of this literature to extract targeted information into biological databases is difficult and time consuming. To address this problem, we developed PubSearch and PubFetch, which store literature, keyword, and gene information in a relational database, index the literature with keywords and gene names, and provide a Web user interface for annotating the genes from experimental data found in the associated literature. A set of protocols is provided in this unit for installing, populating, running, and using PubSearch and PubFetch. In addition, we provide support protocols for performing controlled vocabulary annotations. Intended users of PubSearch and PubFetch are database curators and biology researchers interested in tracking the literature and capturing information about genes of interest in a more effective way than with conventional spreadsheets and lab notebooks.

The broad goal of physiological genomics research is to link genes to their functions using appropriate experimental and computational techniques. Modern genomics experiments enable the generation of vast quantities of data, and interpretation of this data requires the integration of information derived from many diverse sources. Computational biology and bioinformatics offer the ability to manage and channel this information torrent. The Rat Genome Database (RGD; http://rgd.mcw.edu ) has developed computational tools and strategies specifically supporting the goal of linking genes to their functional roles in rat and, using comparative genomics, to human and mouse. We present an overview of the database with a focus on these unique computational tools and describe strategies for the use of these resources in the area of physiological genomics.

One of the core activities of high-throughput proteomics is the identification of peptides from mass spectra. Some peptides can be identified using spectral matching programs like Sequest or Mascot, but many spectra do not produce high quality database matches. De novo peptide sequencing is an approach to determine partial peptide sequences for some of the unidentified spectra. A drawback of de novo peptide sequencing is that it produces a series of ordered and disordered sequence tags and mass tags rather than a complete, non-degenerate peptide amino acid sequence. This incomplete data is difficult to use in conventional search programs such as BLAST or FASTA. DeNovoID is a program that has been specifically designed to use degenerate amino acid sequence and mass data derived from MS experiments to search a peptide database. Since the algorithm employed depends on the amino acid composition of the peptide and not its sequence, DeNovoID does not have to consider all possible sequences, but rather a smaller number of compositions consistent with a spectrum. DeNovoID also uses a geometric indexing scheme that reduces the number of calculations required to determine the best peptide match in the database. DeNovoID is available at http://proteomics.mcw.edu/denovoid.

We describe the theoretical basis for a peptide identification method wherein peptides are represented as vectors based on their amino acid composition and grouped into clusters. Unknown peptides are identified by finding the database cluster and peptide entries with the shortest Euclidian distance. We demonstrate that the amino acid composition of peptides is virtually as informative as the sequence and allows rapid peptide identification more accurately than peptide mass alone.

ProMoST is a flexible web tool that calculates the effect of single or multiple posttranslational modifications (PTMs) on protein isoelectric point (pI) and molecular weight and displays the calculated patterns as two-dimensional (2D) gel images. PTMs of proteins control many biological regulatory and signaling mechanisms and 2D gel electrophoresis is able to resolve many PTM-induced isoforms, such as those due to phosphorylation, acetylation, deamination, alkylation, cysteine oxidation or tyrosine nitration. These modifications cause changes in the pI of the protein by adding, removing or changing titratable groups. Proteins differ widely in buffering capacity and pI and therefore the same PTMs may give rise to quite different patterns of pI shifts in different proteins. It is impossible by visual inspection of a pattern of spots on a gel to determine which modifications are most likely to be present. The patterns of PTM shifts for different proteins can be calculated and are often quite distinctive. The theoretical gel images produced by ProMoST can be compared to the experimental 2D gel results to implicate probable PTMs and focus efforts on more detailed study of modified proteins. ProMoST has been implemented as cgi script in Perl available on a WWW server at http://proteomics.mcw.edu/promost.

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.