ABSTRACT
BACKGROUND: The analysis and interpretation of data generated from patient-derived clinical samples relies on access to high-quality bioinformatics resources. These are maintained and updated by expert curators extracting knowledge from unstructured biological data described in free-text journal articles and converting this into more structured, computationally-accessible forms. This enables analyses such as functional enrichment of sets of genes/proteins using the Gene Ontology, and makes the searching of data more productive by managing issues such as gene/protein name synonyms, identifier mapping, and data quality. OBJECTIVE: To undertake a coordinated annotation update of key public-domain resources to better support Alzheimer's disease research. METHODS: We have systematically identified target proteins critical to disease process, in part by accessing informed input from the clinical research community. RESULTS: Data from 954 papers have been added to the UniProtKB, Gene Ontology, and the International Molecular Exchange Consortium (IMEx) databases, with 299 human proteins and 279 orthologs updated in UniProtKB. 745 binary interactions were added to the IMEx human molecular interaction dataset. CONCLUSION: This represents a significant enhancement in the expert curated data pertinent to Alzheimer's disease available in a number of biomedical databases. Relevant protein entries have been updated in UniProtKB and concomitantly in the Gene Ontology. Molecular interaction networks have been significantly extended in the IMEx Consortium dataset and a set of reference protein complexes created. All the resources described are open-source and freely available to the research community and we provide examples of how these data could be exploited by researchers.
Subject(s)
Alzheimer Disease/genetics , Computational Biology/methods , Databases, Protein , Expert Systems , Protein Interaction Maps/genetics , Public Sector , Alzheimer Disease/diagnosis , HumansABSTRACT
During the last few years, next-generation sequencing (NGS) technologies have accelerated the detection of genetic variants resulting in the rapid discovery of new disease-associated genes. However, the wealth of variation data made available by NGS alone is not sufficient to understand the mechanisms underlying disease pathogenesis and manifestation. Multidisciplinary approaches combining sequence and clinical data with prior biological knowledge are needed to unravel the role of genetic variants in human health and disease. In this context, it is crucial that these data are linked, organized, and made readily available through reliable online resources. The Swiss-Prot section of the Universal Protein Knowledgebase (UniProtKB/Swiss-Prot) provides the scientific community with a collection of information on protein functions, interactions, biological pathways, as well as human genetic diseases and variants, all manually reviewed by experts. In this article, we present an overview of the information content of UniProtKB/Swiss-Prot to show how this knowledgebase can support researchers in the elucidation of the mechanisms leading from a molecular defect to a disease phenotype.
Subject(s)
Databases, Protein/statistics & numerical data , Genetic Association Studies , Genetics, Medical , Knowledge Bases , Proteome , Software , Amino Acid Sequence , Genetic Variation , Genome, Human , High-Throughput Nucleotide Sequencing , Humans , Internet , Molecular Sequence Annotation , Molecular Sequence Data , Terminology as TopicABSTRACT
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.
Subject(s)
Databases, Protein , Molecular Sequence Annotation , Vocabulary, Controlled , Molecular Sequence Annotation/standardsABSTRACT
UniProtKB/Swiss-Prot (http://beta.uniprot.org/uniprot; last accessed: 19 October 2007) is a manually curated knowledgebase providing information on protein sequences and functional annotation. It is part of the Universal Protein Resource (UniProt). The knowledgebase currently records a total of 32,282 single amino acid polymorphisms (SAPs) touching 6,086 human proteins (Release 53.2, 26 June 2007). Nearly all SAPs are derived from literature reports using strict inclusion criteria. For each SAP, the knowledgebase provides, apart from the position of the mutation and the resulting change in amino acid, information on the effects of SAPs on protein structure and function, as well as their potential involvement in diseases. Presently, there are 16,043 disease-related SAPs, 14,266 polymorphisms, and 1,973 unclassified variants recorded in UniProtKB/Swiss-Prot. Relevant information on SAPs can be found in various sections of a UniProtKB/Swiss-Prot entry. In addition to these, cross-references to human disease databases as well as other gene-specific databases, are being added regularly. In 2003, the Swiss-Prot variant pages were created to provide a concise view of the information related to the SAPs recorded in the knowledgebase. When compared to the information on missense variants listed in other mutation databases, UniProtKB/Swiss-Prot further records information on direct protein sequencing and characterization including posttranslational modifications (PTMs). The direct links to the Online Mendelian Inheritance in Man (OMIM) database entries further enhance the integration of phenotype information with data at protein level. In this regard, SAP information in UniProtKB/Swiss-Prot complements nicely those existing in genomic and phenotypic databases, and is valuable for the understanding of SAPs and diseases.
