1. Emily Dimmer edimmer@ebi.ac.uk GOA group European Bioinformatics Institute Wellcome Trust Genome Campus Cambridge UK Gene Ontology (GO)

2. Introduction to GO Description of the GO ontologies How groups annotate to GO Practical: Investigating the GO and OBO web sites Browsing the GO using the AmiGO Browser. Open Biomedical Ontologies How GO is being used Available Tools GO slims Practical: Creating your own GO slim GO Tutorial Outline:

3. Introduction to GO Description of the GO ontologies How groups annotate to GO Practical: Investigating the GO and OBO web sites Browsing the GO using the AmiGO Browser. Open Biomedical Ontologies How GO is being used Available Tools GO slims Practical: Creating your own GO slim GO Tutorial Outline:

4. Introduction to GO Description of the GO ontologies How groups annotate to GO Practical: Investigating the GO and OBO web sites Browsing the GO using the AmiGO Browser. Open Biomedical Ontologies How GO is being used Available Tools GO slims Practical: Creating your own GO slim GO Tutorial Outline:

5. Introduction to GO Description of the GO ontologies How groups annotate to GO Practical: Investigating the GO and OBO web sites Browsing the GO using the AmiGO Browser. Open Biomedical Ontologies How GO is being used Available Tools GO slims Practical: Creating your own GO slim GO Tutorial Outline:

6. Why is GO needed ? THE PROBLEM: Huge body of knowledge with an extremely large vocabulary to describe it Vocabulary used is poorly defined –i.e. one word can have different meanings –or different names for the same concept Biological systems are complex and our knowledge of such systems is incomplete RESULT: Large databases which are difficult to manage and impossible to mine computationally

7. A (part of the) solution: GO: “a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing” What is GO?

8. Access gene product functional information Provide a link between biological knowledge and … gene expression profiles proteomics data Find how much of a proteome is involved in a process/ function/ component in the cell using a GO-Slim (a slimmed down version of GO to summarize biological attributes of a proteome) Map GO terms and incorporate manual GOA annotation into own databases to enhance your dataset or to validate automated ways of deriving information about gene function (text-mining). What can scientists do with GO?

9. Tactition Tactile sense Taction ?

10. perception of touch ; GO:0050975 Tactition Tactile sense Taction

11. Molecular Function: elemental activity or task e.g. DNA binding, catalysis of a reaction Biological Process: broad objective or goal e.g. mitosis, signal transduction, metabolism Cellular Component: location or complex e.g. nucleus, ribosome GO Three (Orthogonal) Ontologies

12. Molecular Function: elemental activity or task e.g. DNA binding, catalysis of a reaction Biological Process: broad objective or goal e.g. mitosis, signal transduction, metabolism Cellular Component: location or complex e.g. nucleus, ribosome GO Three (Orthogonal) Ontologies

13. Molecular Function: elemental activity or task e.g. DNA binding, catalysis of a reaction Biological Process: broad objective or goal e.g. mitosis, signal transduction, metabolism Cellular Component: location or complex e.g. nucleus, ribosome GO Three (Orthogonal) Ontologies

14. Molecular Function: elemental activity or task e.g. DNA binding, catalysis of a reaction Biological Process: broad objective or goal e.g. mitosis, signal transduction, metabolism Cellular Component: location or complex e.g. nucleus, ribosome GO Three (Orthogonal) Ontologies

15. How does GO work? Provides a standard, species-neutral way of representing biology GO covers ‘normal’ functions and processes –No pathological processes –No experimental conditions

16. Molecular Function 7,493 terms Biological Process 9,640 terms Cellular Component 1,634 terms Total 18,767 terms Definitions: 16,696 (93.9 %) Content of GO

17. What is GO? NOT a system of nomenclature or a list of gene products GO doesn’t attempt to cover all aspects of biology or evolutionary relationships Open Biomedical Ontologies http://obo.sourceforge.net NOT a dictated standard NOT a way to unify databases

18. http://www.geneontology.org Reactome

19. Anatomy of a GO term GO terms are composed of: Term name Unique GO ID Definition (93 % of GO terms are defined) Synonyms (optional) Database references (optional) Relationships to other GO terms

20. Ontologies “Ontologies provide controlled, consistent vocabularies to describe concepts and relationships, thereby enabling knowledge sharing” (Gruber 1993) I. The GO Ontologies

21. Can be used to: Formalise the representation of biological knowledge Describe a common and defined vocabulary for database annotation Standardise database submissions Provide unified access to information through ontology-based querying of databases, both human and computational Improve management and integration of data within databases. Facilitate data mining Ontology applications

22. Ontologies can be represented as graphs, where the vertices (nodes and leaves) are connected by edges. The nodes are concepts in the ontology. The edges are the relationships between the concepts node edge Ontology Structure

23. The Gene Ontology is structured as a hierarchical directed acyclic graph (DAG). Terms are linked by two relationships –is-a –part-of Terms can have more than one parent

24. Simple hierarchies Directed Acyclic (Trees) Graphs

25. Directed Acyclic Graph cell membrane chloroplast mitochondrial chloroplast membrane is-a part-of

26. True Path Rule The path from a child term all the way up to its top-level parent(s) must always be true cell  cytoplasm  chromosome  nuclear chromosome  nucleus  nuclear chromosome is-a  part-of 

27. Terms become obsolete when they are removed or redefined GO IDs are never deleted For each term, a comment is added to explains why the term is now obsolete Ensuring Stability in a Dynamic Ontology Obsolete Cellular Component Obsolete Molecular Function Obsolete Biological Process Biological Process Molecular Function Cellular Component

28. Access to the Gene Ontology Downloads formats available: OBO GO XMLOWL MySQL (http://www.geneontology.org/GO.downloads) Web-based tools AmiGO (http://www.godatabase.org) QuickGO (http://www.ebi.ac.uk/ego)

29. II. Annotating to GO Use of GO terms to represent the activities and localizations of gene products. Basic information needed: 1. Database object (e.g. a protein or gene identifier) e.g. Q9ARH1 2. Reference ID e.g. PubMed ID: 12374299 3. GO term ID e.g. GO:0004674 4. Evidence code e.g. TAS

30. GenNav: http://etbsun2.nlm.nih.gov:8000/perl/gennav.pl

31. J. Clark et al. Plant Physiology 2005 (in press)

32. Two types of GO Annotation:  Electronic Annotation  Manual Annotation All annotations must: be attributed to a source. indicate what evidence was found to support the GO term-gene/protein association.

33. Electronic Annotation Provides large-coverage High-quality BUT annotations tend to use high-level GO terms and provide little detail.

34. 1.Assignment of GO terms to gene products using existing information within database entries Manual mapping of GO terms to concepts external to GO (‘translation tables’). Proteins then electronically annotated with the relevant GO term(s). 2.Automatic sequence analyses to transfer annotations between highly similar gene products Electronic Annotation

35. Fatty acid biosynthesis ( Swiss-Prot Keyword) EC:6.4.1.2 (EC number) IPR000438: Acetyl-CoA carboxylase carboxyl transferase beta subunit ( InterPro entry) MF_00527: Putative 3- methyladenine DNA glycosylase (HAMAP) GO:Fatty acid biosynthesis ( GO:0006633 ) GO:acetyl-CoA carboxylase activity ( GO:0003989 ) GO:acetyl-CoA carboxylase activity (GO:0003989) GO:DNA repair (GO:0006281) Electronic Annotation

36. http://www.geneontology.org/GO.indices.shtml Mappings of external concepts to GO

37. Evaluation of precision of annotation electronic techniques (InterPro2GO, SPKW2GO, EC2GO) Compared manually-curated test set of GO annotated proteins with the electronic annotations InterPro2GO = most coverage EC2GO = 67 % of predictions exactly match the manual GO annotation. 91-100 % of time the 3 mappings predicted GO terms within the same lineage Camon et al. BMC Bioinformatics 2005 in press

38. Manual Annotation High–quality, specific gene/gene product associations made, using: Peer-reviewed papers Evidence codes to grade evidence BUT – is very time consuming and requires trained biologists

39. Finding GO terms In this study, we report the isolation and molecular characterization of the B. napus PERK1 cDNA, that is predicted to encode a novel receptor-like kinase. We have shown that like other plant RLKs, the kinase domain of PERK1 has serine/threonine kinase activity, In addition, the location of a PERK1-GTP fusion protein to the plasma membrane supports the prediction that PERK1 is an integral membrane protein…these kinases have been implicated in early stages of wound response… Process: response to wounding GO:0009611 serine/threonine kinase activity, Function: protein serine/threonine kinase activity GO:0004674 integral membrane protein Component: integral to plasma membrane GO:0005887 …for B. napus PERK1 protein (Q9ARH1) PubMed ID: 12374299 wound response

40. GO Evidence Codes *With column required Manually annotated CodeDefinition *IEAInferred from Electronic Annotation IDAInferred from Direct Assay IEPInferred from Expression Pattern *IGIInferred from Genetic Interaction IMPInferred from Mutant Phenotype *IPIInferred from Physical Interaction *ISSInferred from Sequence Similarity TASTraceable Author Statement NASNon-traceable Author Statement *ICInferred from Curator RCAInferred from Reviewed Computational Analysis NDNo Data IDA: Enzyme assays In vitro reconstitution (transcription) Immunofluorescence Cell fractionation TAS: In the literature source the original experiments referred to are traceable (referenced).

41. GO Evidence Codes *With column required Manually annotated additional needed identifier for annotations using certain evidence codes CodeDefinition *IEAInferred from Electronic Annotation IDAInferred from Direct Assay IEPInferred from Expression Pattern *IGIInferred from Genetic Interaction IMPInferred from Mutant Phenotype *IPIInferred from Physical Interaction *ISSInferred from Sequence Similarity TASTraceable Author Statement NASNon-traceable Author Statement *ICInferred from Curator RCAInferred from Reviewed Computational Analysis NDNo Data IGI: a gene identifier for the "other" gene involved in the interaction IPI: a gene or protein identifier for the "other" protein involved in the interaction IC: GO term from another annotation used as the basis of a curator inference

42. Annotation of a gene product to one ontology is independent from its annotation to other ontologies. Terms reflecting a normal activity or location are only annotated to. Usage of ‘unknown’ GO terms (e.g. Molecular function unknown GO:0005554 ) …some extra things:

43. A set of ‘Qualifier’ terms is also available to curators modify the interpretation of an annotation. Allowable values: 1. NOT a gene product is not associated with the GO term to document conflicting claims in the literature. 2. Contributes to distinguishes between individual subunits functions and whole complex functions (used with GO Function Ontology) 3. Colocalizes with Transiently or peripherally associated with an organelle or complex where the resolution of an assay is not accurate. (used with GO Component Ontology) …some extra things: Qualifier Information

44. The Qualifier column can be used to modify the interpretation of an annotation. Allowable values: 1. NOT a gene product is not associated with the GO term to document conflicting claims in the literature. 2. Contributes to distinguishes between individual subunits functions and whole complex functions (used with GO Function Ontology) 3. Colocalizes with Transiently or peripherally associated with an organelle or complex where the resolution of an assay is not accurate. (used with GO Component Ontology) …some extra things:

45. The Qualifier column can be used to modify the interpretation of an annotation. Allowable values: 1. NOT a gene product is not associated with the GO term to document conflicting claims in the literature. 2. Contributes to distinguishes between individual subunits functions and whole complex functions (used with GO Function Ontology) 3. Colocalizes with Transiently or peripherally associated with an organelle or complex where the resolution of an assay is not accurate. (used with GO Component Ontology) …some extra things:

46. The Qualifier column can be used to modify the interpretation of an annotation. Allowable values: 1. NOT a gene product is not associated with the GO term to document conflicting claims in the literature. 2. Contributes to distinguishes between individual subunit functions and whole complex functions (used with GO Function Ontology) 3. Colocalizes with Transiently or peripherally associated with an organelle or complex where the resolution of an assay is not accurate. (used with GO Component Ontology) …some extra things:

47. Accessing annotations to the Gene Ontology 1. Downloads Annotations – gene association files Ontologies and annotations – MySQL and XML 2. Web-based access AmiGO (http://www.godatabase.org) QuickGO (http://www.ebi.ac.uk/ego) …among others…

48. Gene Association File Calcyclin IPI00027463 protein taxon:9606 20040426 UniProt Calcyclin IPI00027463 protein taxon:9606 20030721 UniProt UniProtP06703S106_HUMAN GO:0008083 GOA:spkw IEA F UniProtP06703 S106_HUMAN NOT GO:0007409 PMID:12152788 NAS P UniProtP06703 S106_HUMAN GO:0005515 PMID:12577318 IPI UniProt:P50995 F via web (GO consortium page) http://www.geneontology.org/GO.current.annotations.shtml DB DB_Object_ID DB_Object_Symbol Qualifier GOid DB:Reference Evidence With Aspect DB_Object_Name DB_Object_Synonym DB_Object_Type taxon Date Assigned by

49. http://www.geneontology.org/GO.current.annotations.shtml

50. Summary GO is still being developed and updated - it requires a serious and ongoing effort. –the biological community is involved New model organism databases are joining the GO Consortium annotation effort

51. Practical session 1.Visit the GO website 2.Visit the OBO website 3.Browse the ontologies using the official GO Consortium Browser – AmiGO

52. GO web site: www.geneontology.org Part 1.

59. OBO web site: http://obo.sourceforge.net

61. AmiGO: http://www.godatabase.org

65. GO terms with no children

70. Filter queries by organism, data source or evidence Search for GO terms or by Gene symbol/name Querying the GO

75. GOst tool

77. QuickGO browser: http://www.ebi.ac.uk/ego

82. OBO and Gene Ontology Uses and Tools

83. Anatomy Physiology Phenotype Pathway Disease Molecular Metabolic Developmental Stage Ontologies

84. Beyond GO – Open Biomedical Ontologies Orthogonal to existing ontologies to facilitate combinatorial approaches - Share unique identifier space - Include definitions Anatomies Cell Types Sequence Attributes Temporal Attributes Phenotypes Diseases More…. http://obo.sourceforge.net

85. Sequence Ontology http://song.sourceforge.net

86. Ontology of ‘small molecular entities’ http://www.ebi.ac.uk/chebi

87. http://www.fruitfly.org/cgi-bin/ex/go.cgi

88. Access to GO and its annotations

89. How to access the Gene ontology and its annotations 1. Downloads Ontologies – (various – GO, OBO, XML, OWL MySQL) Annotations – gene association files Ontologies and Annotations – MySQL and XML 2. Web-based access AmiGO (http://www.godatabase.org) QuickGO (http://www.ebi.ac.uk/ego) among others…

90. http://www.ncbi.nlm.nih.gov/entrez

91. www.uniprot.org/

92. http://www.ebi.ac.uk/intact

93. SRS view… http://srs.ebi.ac.uk

94. www.ensembl.org/

96. Access gene product functional information Provide a link between biological knowledge and … gene expression profiles proteomics data Find how much of a proteome is involved in a process/ function/ component in the cell using a GO-Slim (a slimmed down version of GO to summarize biological attributes of a proteome) Map GO terms and incorporate manual GOA annotation into own databases to enhance your dataset or to validate automated ways of deriving information about gene function (text-mining). What can scientists do with GO?

97. attacked time control Puparial adhesion Molting cycle hemocyanin Defense response Immune response Response to stimulus Toll regulated genes JAK-STAT regulated genes Immune response Toll regulated genes Amino acid catabolism Lipid metobolism Peptidase activity Protein catabloism Immune response Bregje Wertheim at the Centre for Evolutionary Genomics, Department of Biology, UCL and Eugene Schuster Group, EBI. …analysis of high-throughput data according to GO MicroArray data analysis

98. Proteomics data analysis Kislinger T et al, Mol Cell Proteomics, 2003 GO classification …analysis of high-throughput data according to GO

99. http://www.geneontology.org/GO.tools Analysis of Data: Clustering

100. Color indicates up/down regulation GoMiner Tool, John Weinstein et al, Genome Biol. 4 (R28) 2003

101. Compare annotations associated with the test set to the entire set of GO annotations…. DNA Repair seems to be a common theme. Example of VLAD Output

102. …overview proteome with GO Slim http://www.ebi.ac.uk/integr8

103. http://go.princeton.edu/cgi-bin/GOTermMapper map2slim.pl distributed as part of the go-perl package maps a set of annotations up to their parent GO slim terms Off-the-shelf GO slims

104. Summary  The Gene Ontology project precipitated a generalized implementation for ontologies for molecular biology  Bio-ontologies such as GO have facilitated development of systems for hypothesis generation in biological systems  Further integration – creation of cross-products between different ontologies

105. Practical II – Creation of GO slims using the DAG-Edit tool. http://sourceforge.net/projects/geneontology/

107. …loading the GO

112. ftp://ftp.geneontology.org/pub/go/ontology/gene_ontology.obo …loading the GO

115. …browsing the GO

116. …viewing GO terms

117. …searching for GO terms

120. …creating a new GO slim

125. …creating a renderer for the GO slim

131. …adding terms to the GO slim

135. …filtering GO for terms in the GO slim

138. …removing filters/renderers

139. …saving the newly created GO slim