216 research outputs found

    The GOA database in 2009—an integrated Gene Ontology Annotation resource

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    The Gene Ontology Annotation (GOA) project at the EBI (http://www.ebi.ac.uk/goa) provides high-quality electronic and manual associations (annotations) of Gene Ontology (GO) terms to UniProt Knowledgebase (UniProtKB) entries. Annotations created by the project are collated with annotations from external databases to provide an extensive, publicly available GO annotation resource. Currently covering over 160 000 taxa, with greater than 32 million annotations, GOA remains the largest and most comprehensive open-source contributor to the GO Consortium (GOC) project. Over the last five years, the group has augmented the number and coverage of their electronic pipelines and a number of new manual annotation projects and collaborations now further enhance this resource. A range of files facilitate the download of annotations for particular species, and GO term information and associated annotations can also be viewed and downloaded from the newly developed GOA QuickGO tool (http://www.ebi.ac.uk/QuickGO), which allows users to precisely tailor their annotation set

    IntAct—open source resource for molecular interaction data

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    IntAct is an open source database and software suite for modeling, storing and analyzing molecular interaction data. The data available in the database originates entirely from published literature and is manually annotated by expert biologists to a high level of detail, including experimental methods, conditions and interacting domains. The database features over 126 000 binary interactions extracted from over 2100 scientific publications and makes extensive use of controlled vocabularies. The web site provides tools allowing users to search, visualize and download data from the repository. IntAct supports and encourages local installations as well as direct data submission and curation collaborations. IntAct source code and data are freely available from

    Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

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    Background Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes. Methods We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants. Results Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects. Conclusions Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application

    Representing kidney development using the gene ontology.

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    Gene Ontology (GO) provides dynamic controlled vocabularies to aid in the description of the functional biological attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). Here we describe collaboration between the renal biomedical research community and the GO Consortium to improve the quality and quantity of GO terms describing renal development. In the associated annotation activity, the new and revised terms were associated with gene products involved in renal development and function. This project resulted in a total of 522 GO terms being added to the ontology and the creation of approximately 9,600 kidney-related GO term associations to 940 UniProt Knowledgebase (UniProtKB) entries, covering 66 taxonomic groups. We demonstrate the impact of these improvements on the interpretation of GO term analyses performed on genes differentially expressed in kidney glomeruli affected by diabetic nephropathy. In summary, we have produced a resource that can be utilized in the interpretation of data from small- and large-scale experiments investigating molecular mechanisms of kidney function and development and thereby help towards alleviating renal disease

    A method for increasing expressivity of Gene Ontology annotations using a compositional approach.

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    BACKGROUND: The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. RESULTS: The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector-target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions. CONCLUSIONS: The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism's gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction

    Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

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    <p>Abstract</p> <p>Background</p> <p>The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation.</p> <p>Results</p> <p>We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology.</p> <p>Conclusions</p> <p>Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at <url>https://sourceforge.net/tracker/?atid=605890&group_id=36855</url>.</p

    Overview of the Proton-coupled MCT (SLC16A) Family of Transporters: Characterization, Function and Role in the Transport of the Drug of Abuse γ-Hydroxybutyric Acid

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    The transport of monocarboxylates, such as lactate and pyruvate, is mediated by the SLC16A family of proton-linked membrane transport proteins known as monocarboxylate transporters (MCTs). Fourteen MCT-related genes have been identified in mammals and of these seven MCTs have been functionally characterized. Despite their sequence homology, only MCT1–4 have been demonstrated to be proton-dependent transporters of monocarboxylic acids. MCT6, MCT8 and MCT10 have been demonstrated to transport diuretics, thyroid hormones and aromatic amino acids, respectively. MCT1–4 vary in their regulation, tissue distribution and substrate/inhibitor specificity with MCT1 being the most extensively characterized isoform. Emerging evidence suggests that in addition to endogenous substrates, MCTs are involved in the transport of pharmaceutical agents, including γ-hydroxybuytrate (GHB), 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors (statins), salicylic acid, and bumetanide. MCTs are expressed in a wide range of tissues including the liver, intestine, kidney and brain, and as such they have the potential to impact a number of processes contributing to the disposition of xenobiotic substrates. GHB has been extensively studied as a pharmaceutical substrate of MCTs; the renal clearance of GHB is dose-dependent with saturation of MCT-mediated reabsorption at high doses. Concomitant administration of GHB and l-lactate to rats results in an approximately two-fold increase in GHB renal clearance suggesting that inhibition of MCT1-mediated reabsorption of GHB may be an effective strategy for increasing renal and total GHB elimination in overdose situations. Further studies are required to more clearly define the role of MCTs on drug disposition and the potential for MCT-mediated detoxification strategies in GHB overdose

    The early asthmatic response is associated with glycolysis, calcium binding and mitochondria activity as revealed by proteomic analysis in rats

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    <p>Abstract</p> <p>Background</p> <p>The inhalation of allergens by allergic asthmatics results in the early asthmatic response (EAR), which is characterized by acute airway obstruction beginning within a few minutes. The EAR is the earliest indicator of the pathological progression of allergic asthma. Because the molecular mechanism underlying the EAR is not fully defined, this study will contribute to a better understanding of asthma.</p> <p>Methods</p> <p>In order to gain insight into the molecular basis of the EAR, we examined changes in protein expression patterns in the lung tissue of asthmatic rats during the EAR using 2-DE/MS-based proteomic techniques. Bioinformatic analysis of the proteomic data was then performed using PPI Spider and KEGG Spider to investigate the underlying molecular mechanism.</p> <p>Results</p> <p>In total, 44 differentially expressed protein spots were detected in the 2-DE gels. Of these 44 protein spots, 42 corresponded to 36 unique proteins successfully identified using mass spectrometry. During subsequent bioinformatic analysis, the gene ontology classification, the protein-protein interaction networking and the biological pathway exploration demonstrated that the identified proteins were mainly involved in glycolysis, calcium binding and mitochondrial activity. Using western blot and semi-quantitative RT-PCR, we confirmed the changes in expression of five selected proteins, which further supports our proteomic and bioinformatic analyses.</p> <p>Conclusions</p> <p>Our results reveal that the allergen-induced EAR in asthmatic rats is associated with glycolysis, calcium binding and mitochondrial activity, which could establish a functional network in which calcium binding may play a central role in promoting the progression of asthma.</p

    The UniProt-GO Annotation database in 2011

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    The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set
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