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We are performing whole genome sequencing (WGS) of families with Autism Spectrum Disorder (ASD) to build a resource, named MSSNG, to enable the sub-categorization of phenotypes and underlying genetic factors involved. Here, we report WGS of 5,205 samples from families with ASD, accompanied by clinical information, creating a database accessible in a cloud platform, and through an internet portal with controlled access. We found an average of 73.8 de novo single nucleotide variants and 12.6 de novo insertion/deletions (indels) or copy number variations (CNVs) per ASD subject. We identified 18 new candidate ASD-risk genes such as MED13 and PHF3, and found that participants bearing mutations in susceptibility genes had significantly lower adaptive ability (p=6×10−4). In 294/2,620 (11.2%) of ASD cases, a molecular basis could be determined and 7.2% of these carried CNV/chromosomal abnormalities, emphasizing the importance of detecting all forms of genetic variation as diagnostic and therapeutic targets in ASD.

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

To thrive, the field that links biologists and their data urgently needs structure, recognition and support.

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 Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.

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.

The Rat Genome Database (RGD) (http://rgd.mcw.edu) aims to meet the needs of its community by providing genetic and genomic infrastructure while also annotating the strengths of rat research: biochemistry, nutrition, pharmacology and physiology. Here, we report on RGD's development towards creating a phenome database. Recent developments can be categorized into three groups. (i) Improved data collection and integration to match increased volume and biological scope of research. (ii) Knowledge representation augmented by the implementation of a new ontology and annotation system. (iii) The addition of quantitative trait loci data, from rat, mouse and human to our advanced comparative genomics tools, as well as the creation of new, and enhancement of existing, tools to enable users to efficiently browse and survey research data. The emphasis is on helping researchers find genes responsible for disease through the use of rat models. These improvements, combined with the genomic sequence of the rat, have led to a successful year at RGD with over two million page accesses that represent an over 4-fold increase in a year. Future plans call for increased annotation of biological information on the rat elucidated through its use as a model for human pathobiology. The continued development of toolsets will facilitate integration of these data into the context of rat genomic sequence, as well as allow comparisons of biological and genomic data with the human genomic sequence and of an increasing number of organisms.

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.

CORRIGENDUM: InterMOD: integrated data and tools for the unification of model organism research

Model organisms are widely used for understanding basic biology and have significantly contributed to the study of human disease. In recent years, genomic analysis has provided extensive evidence of widespread conservation of gene sequence and function amongst eukaryotes, allowing insights from model organisms to help decipher gene function in a wider range of species. The InterMOD consortium is developing an infrastructure based around the InterMine data warehouse system to integrate genomic and functional data from a number of key model organisms, leading the way to improved cross-species research. So far including budding yeast, nematode worm, fruit fly, zebrafish, rat and mouse, the project has set up data warehouses, synchronized data models and created analysis tools and links between data from different species. The project unites a number of major model organism databases, improving both the consistency and accessibility of comparative research, to the benefit of the wider scientific community.

The set of interacting molecules collectively referred to as a pathway or network represents a fundamental structural unit, the building block of the larger, highly integrated networks of biological systems. The scientific community's interest in understanding the fine details of how pathways work, communicate with each other and synergize, and how alterations in one or several pathways may converge into a disease phenotype, places heightened demands on pathway data and information providers. To meet such demands, the Rat Genome Database [(RGD) http://rgd.mcw.edu] has adopted a multitiered approach to pathway data acquisition and presentation. Resources and tools are continuously added or expanded to offer more comprehensive pathway data sets as well as enhanced pathway data manipulation, exploration and visualization capabilities. At RGD, users can easily identify genes in pathways, see how pathways relate to each other and visualize pathways in a dynamic and integrated manner. They can access these and other components from several entry points and effortlessly navigate between them and they can download the data of interest. The Pathway Portal resources at RGD are presented, and future directions are discussed. Database URL: http://rgd.mcw.edu

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.

Endothelial microparticles (EMPs) are small vesicles released from the plasma membrane of endothelial cells in response to cell injury, apoptosis, or activation. Low levels of MPs are shed into the blood from the endothelium, but in some pathologic states, the number of EMPs is elevated. The mechanism of MP formation and the wide-ranging effects of elevated EMPs are poorly understood. Here, we report the protein composition of EMPs derived from human umbilical cord endothelial cells stimulated with plasminogen activator inhibitor type 1 (PAI-1). Two-dimensional gel electrophoresis followed by mass spectrometry identified 58 proteins, of which some were verified by Western blot analysis. Gene Ontology database searches revealed that proteins identified on PAI-1-derived EMPs are highly diverse. Endothelial microparticles are composed of proteins from different cellular components that exhibit multiple molecular functions and are involved in a variety of biological processes. Important insight is provided into the generation and protein composition of PAI-1-derived EMPs.

Endothelium-derived microparticles (EMPs) are small vesicles released from endothelial cells in response to cell injury, apoptosis, or activation. Elevated concentrations of EMPs have been associated with many inflammatory and vascular diseases. EMPs also mediate long range signaling and alter downstream cell function. Unfortunately, the molecular and cellular basis of microparticle production and downstream cell function is poorly understood. We hypothesize that EMPs generated by different agonists will produce distinct populations of EMPs with unique protein compositions. To test this hypothesis, different EMP populations were generated from human umbilical vein endothelial cells by stimulation with plasminogen activator inhibitor type 1 (PAI-1) or tumor necrosis factor-alpha (TNF-alpha) and subjected to proteomic analysis by LC/MS. We identified 432 common proteins in all EMP populations studied. Also identified were 231 proteins unique to control EMPs, 104 proteins unique to PAI-1 EMPs and 70 proteins unique to TNF-alpha EMPs. Interestingly, variations in protein abundance were found among many of the common EMP proteins, suggesting that differences exist between EMPs on a relative scale. Finally, gene ontology (GO) and KEGG pathway analysis revealed many functional similarities and few differences between the EMP populations studied. In summary, our results clearly indicate that EMPs generated by PAI-1 and TNF-alpha produce EMPs with overlapping but distinct protein compositions. These observations provide fundamental insight into the mechanisms regulating the production of these particles and their physiological role in numerous diseases.

The rat is an important system for modeling human disease. Four years ago, the rich 150-year history of rat research was transformed by the sequencing of the rat genome, ushering in an era of exceptional opportunity for identifying genes and pathways underlying disease phenotypes. Genome-wide association studies in human populations have recently provided a direct approach for finding robust genetic associations in common diseases, but identifying the precise genes and their mechanisms of action remains problematic. In the context of significant progress in rat genomic resources over the past decade, we outline achievements in rat gene discovery to date, show how these findings have been translated to human disease, and document an increasing pace of discovery of new disease genes, pathways and mechanisms. Finally, we present a set of principles that justify continuing and strengthening genetic studies in the rat model, and further development of genomic infrastructure for rat research.

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.

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.

The main goal of comparative proteomics is the quantitation of the differences in abundance of many proteins between two different biological samples in a single experiment. By differentially labeling the peptides from the two samples and combining them in a single analysis, relative ratios of protein abundance can be accurately determined. Protease catalyzed (18)O exchange is a simple method to differentially label peptides, but the lack of robust software tools to analyze the data from mass spectra of (18)O labeled peptides generated by common ion trap mass spectrometers has been a limitation. ZoomQuant is a stand-alone computational tool that analyzes the mass spectra of (18)O labeled peptides from ion trap instruments and determines relative abundance ratios between two samples. Starting with a filtered list of candidate peptides that have been successfully identified by Sequest, ZoomQuant analyzes the isotopic forms of the peptides using high-resolution zoom scan spectrum data. The theoretical isotope distribution is determined from the peptide sequence and is used to deconvolute the peak areas associated with the unlabeled, partially labeled, and fully labeled species. The ratio between the labeled and unlabeled peptides is then calculated using several different methods. ZoomQuant's graphical user interface allows the user to view and adjust the parameters for peak calling and quantitation and select which peptides should contribute to the overall abundance ratio calculation. Finally, ZoomQuant generates a summary report of the relative abundance of the peptides identified in the two samples.

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 laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality 'draft' covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineage-independent evolutionary events such as expansion of gene families, orthology relations and protein evolution.

Background Our increasing use of genetic and genomic strategies to understand human prostate cancer means that we need access to simplified and integrated information present in the associated biomedical literature. In particular, microarray gene expression studies and associated genetic mapping studies in prostate cancer would benefit from a generalized understanding of the prior work associated with this disease. This would allow us to focus subsequent laboratory studies to genomic regions already related to prostate cancer by other scientific methods. We have developed a database of prostate cancer related chromosomal information from the existing biomedical literature. The input material was based on a broad literature search with subsequent hand annotation of information relevant to prostate cancer. Description The database was then analyzed for identifiable trends in the whole scale literature. We have used this database, named ChromSorter PC, to present graphical summaries of chromosomal regions associated with prostate cancer broken down by age, ethnicity and experimental method. In addition we have placed the database information on the human genome using the Generic Genome Browser tool that allows the visualization of the data with respect to user generated datasets. Conclusions We have used this database as an additional dataset for the filtering of genes identified through genetics and genomics studies as warranting follow-up validation studies. We would like to make this dataset publicly available for use by other groups. Using the Genome Browser allows for the graphical analysis of the associated data http://www.prostategenomics.org/datamining/chrom-sorter_pc.html. Additional material from the database can be obtained by contacting the authors (mdatta@mcw.edu).

We report the establishment of a hybridization-based marker system for the rat genome based on the PCR amplification of interspersed repetitive sequences (IRS). Overall, 351 IRS markers were mapped within the rat genome. The IRS marker panel consists of 210 nonpolymorphic and 141 polymorphic markers that were screened for presence/absence polymorphism patterns in 38 different rat strains and substrains that are commonly used in biomedical research. The IRS marker panel was demonstrated to be useful for rapid genome screening in experimental rat crosses and high-throughput characterization of large-insert genomic library clones. Information on corresponding YAC clones is made available for this IRS marker set distributed over the whole rat genome. The two existing rat radiation hybrid maps were integrated by placing the IRS markers in both maps. The genetic and physical mapping data presented provide substantial information for ongoing positional cloning projects in the rat.

An antiserum was raised against the African swine fever virus (ASFV)-encoded ubiquitin-conjugating enzyme (UBCv1) and used to demonstrate by Western blotting (immunoblotting) and immunofluorescence that the enzyme is present in purified extracellular virions, is expressed both early and late after infection of cells with ASFV, and is cytoplasmically located. Antiubiquitin serum was used to identify novel ubiquitin conjugates present during ASFV infections. This antiserum stained virus factories late after infection, suggesting that virion proteins may be ubiquitinated. This possibility was confirmed by Western blotting, which identified three major antiubiquitin-immunoreactive proteins with molecular masses of 5, 18, and 58 kDa in purified extracellular virions. The 18-kDa protein was solubilized from virions at relatively low concentrations of the detergent n-octyl-beta-D-glucopyranoside, indicating that it is externally located and is possibly in the virus capsid. The 18-kDa protein was purified, and N-terminal amino acid sequencing confirmed that the protein was ubiquitinated and was ASFV encoded. The ASFV gene encoding this protein (PIG1) was sequenced, and the encoded protein expressed in an Escherichia coli expression vector. Recombinant PIG1 was ubiquitinated in the presence of E. coli expressed UBCv1 in vitro. These results suggest that PIG1 may be a substrate for UBCv1. The predicted molecular masses of the PIG1 protein and recombinant ubiquitinated protein were larger than the 18-kDa molecular mass of the ubiquitinated protein present in virions. Therefore, during viral replication, a precursor protein may undergo limited proteolysis to generate the ubiquitinated 18-kDa protein.

A report on the third biannual 'Rat Genomics and Models' meeting, Cold Spring Harbor, USA, 11-14 December 2003.

Stable isotope labeling with (18)O is a promising technique for obtaining both qualitative and quantitative information from a single differential protein expression experiment. The small 4 Da mass shift produced by incorporation of two molecules of (18)O, and the lack of available methods for automated quantification of large data sets has limited the use of this approach with electrospray ionization-ion trap (ESI-IT) mass spectrometers. In this paper, we describe a method of acquiring ESI-IT mass spectrometric data that provides accurate calculation of relative ratios of peptides that have been differentially labeled using(18)O. The method utilizes zoom scans to provide high resolution data. This allows for accurate calculation of (18)O/(16)O ratios for peptides even when as much as 50% of a (18)O labeled peptide is present as the singly labeled species. The use of zoom scan data also provides sufficient resolution for calculating accurate ratios for peptides of +3 and lower charge states. Sequence coverage is comparable to that obtained with data acquisition modes that use only MS and MS/MS scans. We have employed a newly developed analysis software tool, ZoomQuant, which allows for the automated analysis of large data sets. We show that the combination of zoom scan data acquisition and analysis using ZoomQuant provides calculation of isotopic ratios accurate to approximately 21%. This compares well with data produced from (18)O labeling experiments using time of flight (TOF) and Fourier transform-ion cyclotron resonance (FT-ICR) MS instruments.

The laboratory rat (Rattus norvegicus) is a key animal model for biomedical research. However, the genetic infrastructure required for connecting phenotype and genotype in the rat is currently incomplete. Here, we report the construction and integration of two genomic maps: a dense genetic linkage map of the rat and the first radiation hybrid (RH) map of the rat. The genetic map was constructed in two F2 intercrosses (SHRSP × BN and FHH × ACI), containing a total of 4736 simple sequence length polymorphism (SSLP) markers. Allele sizes for 4328 of the genetic markers were characterized in 48 of the most commonly used inbred strains. The RH map is a lod ≥ 3 framework map, including 983 SSLPs, thereby allowing integration with markers on various genetic maps and with markers mapped on the RH panel. Together, the maps provide an integrated reference to >3000 genes and ESTs and >8500 genetic markers (5211 of our SSLPs and >3500 SSLPs developed by other groups). [Bihoreau et al. (1997); James and Tanigami, RHdb (http://www.ebi.ac.uk/RHdb/index.html); Wilder (http://www.nih.gov/niams/scientific/ratgbase); Serikawa et al. (1992); RATMAP server (http://ratmap.gen.gu.se)] RH maps (v. 2.0) have been posted on our web sites at http://goliath.ifrc.mcw.edu/LGR/index.htmlor http://curatools.curagen.com/ratmap. Both web sites provide an RH mapping server where investigators can localize their own RH vectors relative to this map. The raw data have been deposited in the RHdb database. Taken together, these maps provide the basic tools for rat genomics. The RH map provides the means to rapidly localize genetic markers, genes, and ESTs within the rat genome. These maps provide the basic tools for rat genomics. They will facilitate studies of multifactorial disease and functional genomics, allow construction of physical maps, and provide a scaffold for both directed and large-scale sequencing efforts and comparative genomics in this important experimental organism.

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.