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      The Universal Protein Resource (UniProt) in 2010

      research-article
      Author(s): The UniProt Consortium *
      Publication date (Electronic):
      Journal: Nucleic Acids Research
      Publisher: Oxford University Press

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          Abstract

          The primary mission of UniProt is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 3 weeks and can be accessed online for searches or download at http://www.uniprot.org.

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          UniRef: comprehensive and non-redundant UniProt reference clusters.

          Baris Suzek, Hongzhan Huang, Peter McGarvey … (2007)
          Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences. The UniRef (UniProt Reference Clusters) provide clustered sets of sequences from the UniProt Knowledgebase (UniProtKB) and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. Currently covering >4 million source sequences, the UniRef100 database combines identical sequences and subfragments from any source organism into a single UniRef entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences at the 90 or 50% sequence identity levels. UniRef100, UniRef90 and UniRef50 yield a database size reduction of approximately 10, 40 and 70%, respectively, from the source sequence set. The reduced redundancy increases the speed of similarity searches and improves detection of distant relationships. UniRef entries contain summary cluster and membership information, including the sequence of a representative protein, member count and common taxonomy of the cluster, the accession numbers of all the merged entries and links to rich functional annotation in UniProtKB to facilitate biological discovery. UniRef has already been applied to broad research areas ranging from genome annotation to proteomics data analysis. UniRef is updated biweekly and is available for online search and retrieval at http://www.uniprot.org, as well as for download at ftp://ftp.uniprot.org/pub/databases/uniprot/uniref. Supplementary data are available at Bioinformatics online.
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            The Arabidopsis Information Resource (TAIR): gene structure and function annotation

            David Swarbreck, Christopher Wilks, Philippe Lamesch … (2008)
            The Arabidopsis Information Resource (TAIR, http://arabidopsis.org) is the model organism database for the fully sequenced and intensively studied model plant Arabidopsis thaliana. Data in TAIR is derived in large part from manual curation of the Arabidopsis research literature and direct submissions from the research community. New developments at TAIR include the addition of the GBrowse genome viewer to the TAIR site, a redesigned home page, navigation structure and portal pages to make the site more intuitive and easier to use, the launch of several TAIR web services and a new genome annotation release (TAIR7) in April 2007. A combination of manual and computational methods were used to generate this release, which contains 27 029 protein-coding genes, 3889 pseudogenes or transposable elements and 1123 ncRNAs (32 041 genes in all, 37 019 gene models). A total of 681 new genes and 1002 new splice variants were added. Overall, 10 098 loci (one-third of all loci from the previous TAIR6 release) were updated for the TAIR7 release.
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              The consensus coding sequence (CCDS) project: Identifying a common protein-coding gene set for the human and mouse genomes.

              Kim D. Pruitt, Jennifer Harrow, Rachel A. Harte … (2009)
              Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Journal ID (hwp): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): January 2010
                Publication date (Electronic): 20 October 2009
                Publication date PMC-release: 20 October 2009
                Volume: 38
                Issue: Database issue , Database issue
                Pages: D142-D148
                Affiliations
                The EMBL Outstation, The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland, Protein Information Resource, Georgetown University Medical Center, 3300 Whitehaven St. NW, Suite 1200, Washington, DC 20007 and University of Delaware, 15 Innovation Way, Suite 205, Newark, DE 19711, USA
                Author notes
                *Correspondence should be addressed to Rolf Apweiler. Tel: +44 1223 494435; Fax: +44 1223 494468; Email: apweiler@ 123456ebi.ac.uk

                †The members of the UniProt Consortium are given in the Acknowledgements.

                Article
                Publisher ID: gkp846
                DOI: 10.1093/nar/gkp846
                PMC ID: 2808944
                PubMed ID: 19843607
                SO-VID: ef77c089-6650-4e77-a8a2-25d4c37c3da9
                Copyright © © The Author(s) 2009. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 15 September 2009
                Date accepted : 22 September 2009
                Categories
                Subject: Articles

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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