Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder.

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

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 Rat Genome Database pathway portal.

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 curation tool suite: a set of optimized software tools enabling efficient acquisition, organization, and presentation of biological data.

The Rat Genome Database (RGD) is the premier repository of rat genomic and genetic data and currently houses over 40,000 rat gene records as well as human and mouse orthologs, 1771 rat and 1911 human quantitative trait loci (QTLs) and 2209 rat strains. Biological information curated for these data objects includes disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components. A suite of tools has been developed to aid curators in acquiring and validating data objects, assigning nomenclature, attaching biological information to objects and making connections among data types. The software used to assign nomenclature, to create and edit objects and to make annotations to the data objects has been specifically designed to make the curation process as fast and efficient as possible. The user interfaces have been adapted to the work routines of the curators, creating a suite of tools that is intuitive and powerful. Database URL: http://rgd.mcw.edu.

Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.

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 ).

The Rat Genome Database 2009: variation, ontologies and pathways.

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.

Protein composition of plasminogen activator inhibitor type 1-derived endothelial microparticles.

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.

Comparative proteomic analysis of PAI-1 and TNF-alpha-derived endothelial microparticles.

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.

Progress and prospects in rat genetics: a community view.

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.

What everybody should know about the rat genome and its online resources.

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.

Interoperability with Moby 1.0--it's better than sharing your toothbrush!

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/.

Structures of proteins of biomedical interest from the Center for Eukaryotic Structural Genomics.

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 Rat Genome Database, update 2007--easing the path from disease to data and back again.

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.

Exploring phenotypic data at the rat genome database.

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.

PubSearch and PubFetch: a simple management system for semiautomated retrieval and annotation of biological information from the literature.

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.

A new method for identifying informative genetic markers in selectively bred rats.

Microsatellite length polymorphisms are useful for the mapping of heritable traits in rats. Over 4000 such microsatellites have been characterized for 48 inbred rat strains and used successfully to map phenotypes that differ between strains. At present, however, it is difficult to use this microsatellite database for mapping phenotypes in selectively bred rats of unknown genotype derived from outbred populations because it is not immediately obvious which markers might differ between strains and be informative. We predicted that markers represented by many alleles among the known inbred rat strains would also be most likely to differ between selectively bred strains derived from outbred populations. Here we describe the development and successful application of a new genotyping tool (HUMMER) that assigns "heterozygosity" (Het) and "uncertainty" (Unc) scores to each microsatellite marker that corresponds to its degree of heterozygosity among the 48 genotyped inbred strains. We tested the efficiency of HUMMER on two rat strains that were selectively bred from an outbred Sprague-Dawley stock for either high or low activity in the forced swim test (SwHi rats and SwLo rats, respectively). We found that the markers with high Het and Unc scores allowed the efficient selection of markers that differed between SwHi and SwLo rats, while markers with low Het and Unc scores typically identified markers that did not differ between strains. Thus, picking markers based on Het and Unc scores is a valuable method for identifying informative microsatellite markers in selectively bred rodent strains derived from outbred populations.

Tools and strategies for physiological genomics: the Rat Genome Database.

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.

DeNovoID: a web-based tool for identifying peptides from sequence and mass tags deduced from de novo peptide sequencing by mass spectroscopy.

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.