- UNIPROT SUPPORTING AN INTEGRATED MULTIDISCIPLINARY RESEARCH AGENDA FOR ALZHEIMER?S DISEASE- SUPPLEMENT REQUEST 2018 The mission of the Universal Protein Resource (UniProt) is to support biomedical research by providing a freely available, stable, comprehensive, richly and accurately annotated protein sequence knowledgebase. Currently, 5.7 million US citizens are currently living with the effects of Alzheimer?s Disease (AD), which is estimated to rise to 14 million by 2025. A National Plan has been implemented by the US aimed at preventing and effectively treating AD and related dementias by 2025. To support precision medicine based on genomic data, it is essential to develop and maintain a centralized resource that both links the genome to the functional proteins it encodes and also efficiently identifies, captures and disseminates published information on protein function facilitating computational analysis. This centralized resource is UniProt, which facilitates scientific discovery by collecting and organizing current biological knowledge, enabling researchers to analyze and interpret genomic data and other types of high content large-scale biomedical datasets.
The aim of this Supplement is to support AD research via: (1) targeted curation of associated proteins by extracting knowledge from the scientific literature and expertly curating this into UniProtKB/Swiss-Prot. We will identify and describe protein variants linked to the disease and provide a mechanistic description of their effect on protein function. We will collaborate with experts in the field, and organise a focused curation workshop for selected researchers to provide inputs into the curation process. Additionally, as part of the collaboration with the Genome Center for Alzheimer?s Disease (GCAD) and NIAGADS consortium projects, UniProt will provide reciprocal links for cross-referencing AD-related genes in DR lines with NIAGADS GenomicsDB [www.niagads.org/genomics/ tools-and-software/databases/genomics-database], visualization of AD- related genetic variants using the ProtVista viewer, and navigation of AD-related pathways using the pathway viewer and analysis tools. (2) We will leverage an existing collaboration of the UniProt database with the IMEx Consortium of molecular interaction databases [www.imexconsortium.org] to identify and systematically capture details of molecules which interact with AD-associated proteins. These data will be subject to quality filters and high-confidence binary interactors will be exported back into the relevant UniProtKB/Swiss-Prot records. Finally, (3) we will develop a graphical interface through which researchers can navigate the resulting network of proteins involved with the disease. This will be created using user experience design principles for eventual integration into a disease-centric view of the UniProt webpages, further enhanced by AD gene-disease-variant-drug related information identified using text-mining protocols. We will thus provide researchers with both a human-readable and computer-accessible resource enabling them to link genomic variation to protein function and disease to navigate through the disease process and identify tractable targets for therapeutic intervention.
- UNIPROT SUPPORTING AN INTEGRATED MULTIDISCIPLINARY RESEARCH AGENDA FOR ALZHEIMER?S DISEASE- SUPPLEMENT REQUEST 2018 Further enhancement of the UniProt resource with newly published information relevant to AD will enable us to provide a FAIR (Findable, Accessible, Interoperable and Reusable) resource of protein sequences, variation data and disease information to researchers in this field. The functional annotation made available includes human, model organisms, and thousands of microbes (microbiome), and constitutes a platform to integrate multiple ?omics data types, ranging from genome and variation data through to transcriptome, proteome and metabolome data, and thus supports the recommendations for an integrated multidisciplinary research agenda for AD by the 2018 NIH AD Research Summit.
| Watkins, Xavier; Garcia, Leyla J; Pundir, Sangya et al. (2017) ProtVista: visualization of protein sequence annotations. Bioinformatics 33:2040-2041 |
