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UniProt and Complete proteomes

Sandra Orchard. UniProt and Complete proteomes. Importance of reference protein sequence databases. Completeness and minimal redundancy A non redundant protein sequence database, with maximal coverage including splice isoforms, disease variant and PTMs.

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UniProt and Complete proteomes

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  1. Sandra Orchard UniProt and Complete proteomes

  2. Importance of reference protein sequence databases • Completeness and minimal redundancy A non redundant protein sequence database, with maximal coverage including splice isoforms, disease variant and PTMs. Low degree of redundancy for facilitating peptide assignments • Stabilityand consistency Stable identifiers and consistent nomenclature Databases are in constant change due to a substantial amount of work to improve their completeness and the quality of sequence annotation • High quality protein annotation Detailed information on protein function, biological processes, molecular interactions and pathways cross-referenced to external source Computational analysis and biological interpretation of shotgun proteomic data requires a reference protein sequence database

  3. Summary of some protein sequence databases used in proteomics Updated from Nesvizhskii, A. I., and Aebersold, R. (2005) Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics. 4,1419–1440l

  4. Protein sequences: UniProt databases

  5. IPI Closure • IPI was launched in 2001 to cover the gaps in gene predictions between different databases • It is an integrated database which clusters protein sequences from different databases (e.g. UniProt, Ensembl and Refseq) to provide non-redundant complete data sets for human, mouse, rat, zebrafish, arabidopsis, chicken and cow. • Collaboration efforts between Ensembl, Refseq and UniProt to improve gene prediction quality coverage for many of the most-studied genomes.

  6. Collaboration projects between database resources • CCDS project, a collaboration between Ensembl, NCBI, UCSC and UniProt, aims to provide a standard set of gene predictions for the human and mouse genomes • Considerable communication effort between curators from different groups is on-going • Ensembl and UniProt collaboration to cover the gaps in gene predictions in UniProtKB (one sequence for each protein coding transcript in Ensembl) • Ensembl high quality gene/transcript models (quality checks remove gene models with erroneous structures or supported by dubious evidence – e.g. cDNA fragments with short/wrongly annotated ORF) • UniProtKB high quality protein sequences

  7. Complete proteome data set for IPI species • Complete proteome data sets for IPI species are based on existing UniProtKB sequences supplemented by high quality predictions imported from Ensembl • Includes the UniProtKB/Swiss-Prot manual annotated protein sequences supplemented by protein sequences in UniProtKB/TrEMBL from high quality predictions cross-referenced or imported from Ensembl

  8. Complete proteome data sets for IPI species in UniProtKB • Ensembl sequences have now been incorporated for all the species represented in IPI: human, mouse, rat , zebrafish, chicken and cow. • Also for species such as dog, pig, C.elegans, Drosophila melanogaster and Saccharomycescerevisiae. • Complete proteome keyword by release 2011_07 of 28th June • Fasta files by FTP • One file per species containing canonical + isoform sequences • Will work in other species of interest

  9. Manual annotation of the human proteome(UniProtKB/Swiss-Prot) – May 2010 A draft of the complete human proteome has been available in UniProtKB/Swiss-Prot since 2008 Manually annotated representation of 20,252 protein coding genes with over 35,000 protein sequences - an additional 41,000 UniProtKB/TrEMBL form the complete proteome set Approximately 63,000 single amino acid polymorphisms (SAPs), mostly disease-linked 80,000 post-translational modifications (PTMs) Close collaboration with NCBI, Ensembl, Sanger Institute and UCSC to provide the authoritative set to the user community

  10. Finding a complete proteome in UniProtKB

  11. Complete Proteomes

  12. Selecting a sequence set

  13. UniProtKB/TrEMBL • Multiple entries for the same protein (redundancy) can arise in UniProtKB/TrEMBL due to: • Erroneous gene model predictions • Sequence errors (Frame shifts) • Polymorphisms • Alternative start sites • Isoforms • Apart from 100% identical sequences all merged sequences are analysed by a curator so they can be annotated accordingly.

  14. Manual annotation of UniProtKB/Swiss-Prot Splice variants Sequence Sequence features UniProtKB Ontologies Annotations References Nomenclature

  15. Sequence curation, stable identifiers, versioning and archiving • For example – erroneous gene model predictions, frameshifts • …. ..premature stop codons, read-throughs, erroneous initiator methionines….. Master headline

  16. Splice variants Master headline

  17. Domain annotation Binding sites Master headline

  18. Identification of amino acid variants ..and of PTMs Master headline

  19. Statistics of Protein Modifications Number of different modifications produced from each of the encoded amino acids, as currently annotated in the RESID Database of Protein Modifications (523 total).

  20. Statistics of Protein Modifications Number of modifications produced from each of the encoded amino acids in all the proteins currently annotated in the UniProt Knowledgebase.

  21. Understanding PTMs – additional resources High quality PTM annotation required for peptide identification – must take additional weight of any PTM into account RESID (www.ebi.ac.uk/resid) - collection of annotations and structures for protein modifications and cross-links including pre-, co-, and post-translational modifications. - provides systematic and alternate names, atomic formulas and masses, enzymatic activities that generate the modifications, keywords, literature citations, Gene Ontology (GO) cross-references, protein sequence database feature table annotations, structure diagrams, and molecular models. Master headline

  22. Understanding PTMs – additional resources Requirements for MS • Both specific (O-phospho-L-serine) and ambiguous (phosphorylation) chemical terms are needed to describe modifications at different levels of experimental resolution. • Must include protein cross-linking modifications. • Must include artificial modifications • Must include masses and mass differences • Must provide for sequential modifications on the same residue, and for neutral losses Master headline

  23. Understanding PTMs – additional resources PSI-MOD - community standard ontology that reconciles descriptions of protein residue modifications across multiple resources (UniProt, RESID, UniMOD, DeltaMass) www.ebi.ac.uk/ontology-lookup/browse.do?ontName=MOD Master headline

  24. Protein nomenclature Master headline

  25. Master headline

  26. Annotation - >30 defined fields Controlled vocabularies used whenever possible… Master headline

  27. ..and also imported from external resources Binary interactions taken from the IntAct database Interactors of human p53 Master headline

  28. Controlled vocabulary usage increasing – for example from the Gene Ontology Annotation for human Rhodopsin Master headline

  29. Evidence at protein level There is experimental evidence of the existence of a protein (e.g. Edman sequencing, MS, X-ray/NMR structure, good quality protein-protein interaction, detection by antibodies) Evidence at transcript level The existence of a protein has not been proven but there is expression data (e.g. existence of cDNAs, RT-PCR or Northern blots) that indicates the existence of a transcript. Inferred from homology The existence of a protein is likely because orthologs exist in closely related species 4 Predicted 5 Uncertain Sequence evidence Type of evidence that supports the existence of a protein

  30. UniProtKB/TrEMBL • Multiple entries for the same protein (redundancy) can arise in UniProtKB/TrEMBL due to: • Erroneous gene model predictions • Sequence errors (Frame shifts) • Polymorphisms • Alternative start sites • Isoforms • Apart from 100% identical sequences all merged sequences are analysed by a curator so they can be annotated accordingly.

  31. Automatic Annotation • Automated clean-up of annotation from original nucleotide sequence entry • Additional value added by using automatic annotation • Recognises common annotation belonging to a closely related family within UniProtKB/Swiss-Prot • Identifies all members of this family using pattern/motif/HMMs in InterPro • Transfers common annotation to related family members in TrEMBL Master headline

  32. Master headline

  33. Text-based searching • Logical operators ‘&’ (and), ‘|’ Searching UniProt – Simple Search Master headline

  34. Searching UniProt – Advanced Search Master headline

  35. Each linked to the UniProt entry Searching UniProt – Search Results Master headline

  36. Searching UniProt – Search Results Master headline

  37. Searching UniProt – Search Results Master headline

  38. Searching UniProt – Blast Search Master headline

  39. Searching UniProt – Blast Search Master headline

  40. Alignment with query sequence Searching UniProt – Blast Results Master headline

  41. Searching UniProt – Blast Results Master headline

  42. Contributing to UniProtKB

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