The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

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.

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The BB (BioBreeding) rat is one of the best models of spontaneous autoimmune diabetes and is used to study non-MHC loci contributing to Type 1 diabetes. Type 1 diabetes in the diabetes-prone BB (BBDP) rat is polygenic, dependent upon mutations at several loci.Iddm1, on chromosome 4, is responsible for a lymphopenia (lyp) phenotype and is essential to diabetes. In this study, we report the positional cloning of theIddm1/lyp locus. We show that lymphopenia is due to a frameshift deletion in a novel member (Ian5) of the Immune-Associated Nucleotide (IAN)-related gene family, resulting in truncation of a significant portion of the protein. This mutation was absent in 37 other inbred rat strains that are nonlymphopenic and nondiabetic. The IAN gene family, lying within a tight cluster on rat chromosome 4, mouse chromosome 6, and human chromosome 7, is poorly characterized. Some members of the family have been shown to be expressed in mature T cells and switched on during thymic T-cell development, suggesting thatIan5 may be a key factor in T-cell development. The lymphopenia mutation may thus be useful not only to elucidate Type 1 diabetes, but also in the function of the Ian gene family as a whole.[Sequence data reported in this paper has been deposited in GenBank and assigned the following accession nos:AF517674, AF517675, AF517676, and AF517677. Supplemental material is available online at http://depts.washington.edu/rhwlab/ and http:www.genome.org. ] The following individuals and institutions kindly provided reagents, samples, or unpublished information as indicated in the paper: K. Matsumoto and the Sir Frederick Banting Research Centre.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology – a computational knowledge structure describing functional characteristics of genes; 2) GO annotations – evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) – mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project.

SummaryLarge numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models.PaperClip

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.

Models of human disease have long been used to understand the basic pathophysiology of disease and to facilitate the discovery of new therapeutics. However, as long as models have been used there have been debates about the utility of these models and their ability to mimic clinical disease at the phenotypic level. The application of genetic studies to both humans and model systems allows for a new paradigm, whereby a novel comparative genomics strategy combined with phenotypic correlates can be used to bridge between clinical relevance and model utility. This study presents a comparative genomic map for "candidate hypertension loci in humans" based on translating QTLs between rat and human, predicting 26 chromosomal regions in the human genome that are very likely to harbor hypertension genes. The predictive power appears robust, as several of these regions have also been implicated in mouse, suggesting that these regions represent primary targets for the development of SNPs for linkage disequilibrium testing in humans and/or provide a means to select specific models for additional functional studies and the development of new therapeutics.