Using the Gene Ontology to Annotate Key Players in Parkinson's Disease.

The Gene Ontology (GO) is widely recognised as the gold standard bioinformatics resource for summarizing functional knowledge of gene products in a consistent and computable, information-rich language. GO describes cellular and organismal processes across all species, yet until now there has been a considerable gene annotation deficit within the neurological and immunological domains, both of which are relevant to Parkinson's disease. Here we introduce the Parkinson's disease GO Annotation Project, funded by Parkinson's UK and supported by the GO Consortium, which is addressing this deficit by providing GO annotation to Parkinson's-relevant human gene products, principally through expert literature curation. We discuss the steps taken to prioritise proteins, publications and cellular processes for annotation, examples of how GO annotations capture Parkinson's-relevant information, and the advantages that a topic-focused annotation approach offers to users. Building on the existing GO resource, this project collates a vast amount of Parkinson's-relevant literature into a set of high-quality annotations to be utilized by the research community.

Representing virus-host interactions and other multi-organism processes in the Gene Ontology.

BACKGROUND: The Gene Ontology project is a collaborative effort to provide descriptions of gene products in a consistent and computable language, and in a species-independent manner. The Gene Ontology is designed to be applicable to all organisms but up to now has been largely under-utilized for prokaryotes and viruses, in part because of a lack of appropriate ontology terms. METHODS: To address this issue, we have developed a set of Gene Ontology classes that are applicable to microbes and their hosts, improving both coverage and quality in this area of the Gene Ontology. Describing microbial and viral gene products brings with it the additional challenge of capturing both the host and the microbe. Recognising this, we have worked closely with annotation groups to test and optimize the GO classes, and we describe here a set of annotation guidelines that allow the controlled description of two interacting organisms. CONCLUSIONS: Building on the microbial resources already in existence such as ViralZone, UniProtKB keywords and MeGO, this project provides an integrated ontology to describe interactions between microbial species and their hosts, with mappings to the external resources above. Housing this information within the freely-accessible Gene Ontology project allows the classes and annotation structure to be utilized by a large community of biologists and users.

Drosophila SnoN modulates growth and patterning by antagonizing TGF-beta signalling.

Signalling by TGF-beta ligands through the Smad family of transcription factors is critical for developmental patterning and growth. Disruption of this pathway has been observed in various cancers. In vertebrates, members of the Ski/Sno protein family can act as negative regulators of TGF-beta signalling, interfering with the Smad machinery to inhibit the transcriptional output of this pathway. In some contexts ski/sno genes function as tumour suppressors, but they were originally identified as oncogenes, whose expression is up-regulated in many tumours. These growth regulatory effects and the normal physiological functions of Ski/Sno proteins have been proposed to result from changes in TGF-beta signalling. However, this model is controversial and may be over-simplified, because recent findings indicate that Ski/Sno proteins can affect other signalling pathways. To address this issue in an in vivo context, we have analyzed the function of the Drosophila Ski/Sno orthologue, SnoN. We found that SnoN inhibits growth when overexpressed, indicating a tumour suppressor role in flies. It can act in multiple tissues to selectively and cell autonomously antagonise signalling by TGF-beta ligands from both the BMP and Activin sub-families. By contrast, analysis of a snoN mutant indicates that the gene does not play a global role in TGF-beta-mediated functions, but specifically inhibits TGF-beta-induced wing vein formation. We propose that SnoN normally functions redundantly with other TGF-beta pathway antagonists to finely adjust signalling levels, but that it can behave as an extremely potent inhibitor of TGF-beta signalling when highly expressed, highlighting the significance of its deregulation in cancer cells.

The Gene Ontology (GO) database and informatics resource.

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.