Groscurth, A.

Hoffmann, F.

Jöcker, A.

Schoof, H.

MPG.PuRe

BIOINFORMATICS APPLICATIONS NOTE Vol. 24 no. 20 2008, pages 2393–2394doi:10.1093/bioinformatics/btn394Sequence analysisProtein function prediction and annotation in an integratedenvironment powered by web services (AFAWE)Anika Jöcker, Fabian Hoffmann, Andreas Groscurth and Heiko Schoof∗Plant Computational Biology, Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10,50829 Cologne, GermanyReceived on April 28, 2008; revised on July 16, 2008; accepted on July 26, 2008Advance Access publication August 12, 2008Associate Editor: Burkhard RostABSTRACTSummary: Many sequenced genes are mainly annotated throughautomatic transfer of annotation from similar sequences. Manualcomparison of results or intermediate results from different tools canhelp avoid wrong annotations and give hints to the function of a geneeven if none of the automated tools could return any result.AFAWE simpliﬁes the task of manual functional annotation byrunning different tools and workﬂows for automatic functionprediction and displaying the results in a way that facilitatescomparison. Because all programs are executed as web services,AFAWE is easily extensible and can directly query primary databases,thereby always using the most up-to-date data sources. Visual ﬁltershelp to distinguish trustworthy results from non-signiﬁcant results.Furthermore, an interface to add detailed manual annotation to eachgene is provided, which can be displayed to other users.Availability: AFAWE is available at http://bioinfo.mpiz-koeln.mpg.de/afawe/Contact: afawe-admin@mpiz-koeln.mpg.deSupplementary information: SIFTER pipeline (S1), AFAWEtutorial (S2).1 INTRODUCTIONTransfer of functional annotations by sequence similarity froma homolog to a query sequence is the most common methodfor gene function prediction. However, this general method hasmany drawbacks (Gilks et al., 2002). For further improvementof the functional annotation, one can use several othermethods for automatic protein function prediction, for example,structure prediction and comparison, protein domain finding andphylogenomic analysis. Although tools in these fields have increasedaccuracy, limitations remain and at the moment no tool performsequally well for all kinds of genes. A major problem is thepropagation of annotation errors in public databases. Even if new(experimental) function information becomes available, these arerarely updated.However, by manual comparison of results from different tools,wrong functional annotations can be avoided and the function of agene can be further specified (Thibaud-Nissen et al., 2007). Anotheradvantage is that in some cases the automatic functional predictionof a single tool alone is not able to give a significant result. In this∗To whom correspondence should be addressed.case, the combination of individually insignificant data could giveclues to the function of a protein. Unfortunately, this comparison istime consuming, because each tool has its own scores and cutoffsand the user has to switch between different webpages to comparethe results. For some tools, there is no web interface available andit is hard to find out how to use these programs.In the last few years, more and more web services and workflowsfor biological data retrieval and analysis were published. Theyimprove flexibility by making it easier to include new functionalityor data sources; they remove the need for updating local copiesof data by working directly on the primary resource; they allowcomputing-intensive tasks to be executed remotely and improveexecution times by parallelizing across distributed resources.Here, we introduce AFAWE, a tool for Automatic and manualFunctional Annotation in a Web services Environment. It uses webservices and Taverna workflows (Oinn et al., 2004) to run differentfunction prediction tools. It is easily extensible and whereverappropriate web services are available runs directly on sourcedatabases, thus always providing up-to-date data. All results aredisplayed in an interactive web interface both in graphical andtabular form with extensive filtering options so that trustworthyresults are highlighted.2 METHODSAt the moment, AFAWE includes analyses for homolog detection, proteindomain search and phylogenomics. The homolog detection is done byrunning WU-Blast (Labarga et al., 2007) against the UniProt database andseparately against the SwissProt database to get a smaller set of homologswith reliable functional annotation. Protein domains are discovered byInterProScan (Labarga et al., 2007) and by RPSBlast against the ConservedDomain Database (Marchler-Bauer et al., 2003).For the phylogenomic part, we have implemented a Taverna workflow (seeSupplementary Data S1 and http://www.myexperiment.org/workflows/95),which uses SIFTER (Engelhardt et al., 2005) to transfer Gene Ontology(The Gene Ontology Consortium, 2000) terms inside the phylogenetic treeby considering duplication and speciation events.3 WEB INTERFACEThe AFAWE web interface can be entered either by starting a newanalysis or by retrieving previous results. A protein sequence andits source organism are the input for a new analysis. Cached results© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org 2393A.Jöcker et al.are searchable by internal and common public database identifiersas well as free text.The user can select the analysis tools to run and all selected webservices and workflows are called in parallel. The results are parsed,stored in a cache database and displayed in several dynamicallyupdated panes accessible through tabs. The graphical and tabulardisplays aim to allow both a quick overview and thorough browsingof results. The user can come back and view the cached resultswithout running the analyses again. The cached results are deletedif newer results become available (e.g. if databases are updated).To enable a faster comparison of the results, filters are providedto highlight the most significant analysis results. For the BLASTsearch, we provide five filters, one to show proteins having thesame domain composition as the query protein, and one to highlightproteins overlapping with the query sequence for >70% of theirlength. The other three filters show hit proteins, which have anexperimentally verified or reviewed GO term assigned in one of thethree main GO categories: Molecular Function, Biological Processand Cellular Component. GO term assignments are retrieved fromUniProt and Gene Ontology annotation files.We will use the Medicago truncatula gene AC144389_35.2 asan example (see Supplementary Data S2). Keyword search forAC144389_35.2 shows four different analysis results (BLASTagainst UniProt and SwissProt, InterProScan and SIFTER).The SIFTER results are generally more reliable in comparisonto BLAST, because they take evolutionary relationships intoaccount. In the ‘SIFTER’ tab, three different GO terms areshown [‘electron transporter, transferring electrons within CoQH2-cytochrome c reductase complex activity’ (GO:0045153), ‘stearoyl-CoA 9-desaturase’ (GO:0004768) and ‘enzyme activator activity’(GO:0008047)]. GO term GO:0045153, which has an assignedprobability of 0.98, is highlighted as reliable.By using the GO term filter for Molecular Function,experimentally verified or reviewed GO terms assigned to BLASThits can be reviewed. Only two proteins (CYB5_YEAST andCYB5_HUMAN) are highlighted, which means that at least oneof their assigned functions is verified. Both proteins have >70%overlap with the query and share the same domains with the query(both hits are highlighted in yellow if the overlap and domain filteris switched on) and therefore seem to belong to the same proteinfamily.The molecular function GO term assigned to Saccharomycescerevisiae gene CYB5_YEAST [‘electron carrier activity’(GO:009055)] is experimentally verified by direct assay (evidencecode ‘IDA’) and is the parent of GO:0045153, the term predictedby the SIFTER pipeline. By looking at protein domains predictedby InterProScan, only domains included in Cytochrome b areshown and most BLAST hits are also annotated as Cytochrome b.Cytochrome b is the main subunit of the transmembrane cytochromebc1 and b6f complexes and is responsible for the transmembraneelectron transfer (Howell, 1989). This fits well with GO:0045153.On the other hand, Homo sapiens gene CYB5_HUMAN hasGO term ‘cytochrome-c oxidase activity’ (GO:0004129) assignedby ‘traceable author statement (TAS),’ and annotation transfer bysimilarity would pick this up. However, no further support forCytochrome c oxidase activity can be found; all other sequence anddomain matches only support a role as Cytochrome b. Therefore, weassume that this GO term is a wrong annotation and mark it as suchin our manual annotation, at the same time marking GO:0045153 asconfirmed.Running a complete automatic annotation with AC144389_35.2as query, takes about 5 min on our machines, if all found domainsand homologous proteins are in the AFAWE database.4 OUTLOOKWe will use AFAWE in the annotation pipeline of both theinternational Medicago truncatula genome annotation projectIMGAG and the international tomato genome annotation projectITAG. In both projects, AFAWE will be used for communityannotation. We will extend AFAWE by further methods and analysisresults will be combined in a summary page. Web services will beprovided to retrieve data from the AFAWE database or to calculateproteins on the fly without using the web interface.ACKNOWLEDGEMENTSWe thank Barbara Engelhardt for providing us with the SIFTER codeand all providers of publicly accessible bioinformatics web services.Funding: European Commission 6th framework program, projectEU-SOL (FOOD-CT-2006-016214).Conflict of Interest: none declared.REFERENCESEngelhardt,B.E. et al. (2005) Protein molecular function prediction by Bayesianphylogenomics. PLoS Comput. Biol., 1, e45.Gilks,W.R. et al. (2002) Modeling the percolation of annotation errors in a database ofprotein sequences. Bioinformatics, 18, 1641–1649.Howell,N. (1989) Evolutionary conservation of protein regions in the protonmotivecytochrome b and their possible roles in redox catalysis. J. Mol. Evol., 29, 157–169.Labarga,A. et al. (2007) Web Services at the European Bioinformatics Institute. NucleicAcids Res., 35, W6–W11.Marchler-Bauer,A. et al. (2003) CDD: a curated Entrez database of conserved domainalignments. Nucleic Acids Res., 31, 383–387.Oinn,T. et al. (2004) Taverna: a tool for the composition and enactment of bioinformaticsworkflows. Bioinformatics, 20, 3045–3054.Thibaud-Nissen,F. et al. (2007) EuCAP, a Eukaryotic Community Annotation Package,and its application to the rice genome. BMC Genomics, 8, 388.The Gene Ontology Consortium (2000) Gene Ontology: tool for the unification ofbiology. Nat. Genet., 25, 25–29.2394

Protein function prediction and annotation in an integrated environment powered by web services (AFAWE)

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