1. A Common Language for Annotation of Genes from Yeast, Flies and Mice The Gene Ontologies …and Plants and Worms …and Humans …and anything else!

2. Gene Ontology Objectives GO represents categories used to classify specific parts of our biological knowledge: –Biological Process –Molecular Function –Cellular Component GO develops a common language applicable to any organism GO terms can be used to annotate gene products from any species, allowing comparison of information across species

3. Expansion of Sequence Info

4. Eukaryotic Genome Sequences YearGenome# Genes Size (Mb) Yeast ( S. cerevisiae )1996 12 6,000 Worm ( C. elegans )1998 97 19,100 Fly ( D. melanogaster )2000 120 13,600 Plant ( A. thaliana )2001 125 25,500 Human ( H. sapiens, 1st Draft )2001 ~3000~35,000 Entering the Genome Sequencing Era

5. Baldauf et al. (2000) Science 290:972

6. MCM3 MCM2 CDC46/MCM5 CDC47/MCM7 CDC54/MCM4 MCM6 These proteins form a hexamer in the species that have been examined Comparison of sequences from 4 organisms

7. http://www.geneontology.org/

8. Outline of Topics Introduction to the Gene Ontologies (GO) Annotations to GO terms GO Tools Applications of GO

9. What is an Ontology? (from OED) 1721 B AILEY, Ontology, an Account of being in the Abstract. 1733 (title) A Brief Scheme of Ontology or the Science of Being in General. a1832 B ENTHAM Fragm. Ontol. Wks. 1843 VIII. 195 The field of ontology, or as it may otherwise be termed, the field of supremely abstract entities, is a yet untrodden labyrinth. 1884 B OSANQUET tr. Lotze's Metaph. 22 Ontology..as a doctrine of the being and relations of all reality, had precedence given to it over Cosmology and Psychology, the two branches of enquiry which follow the reality into its opposite distinctive forms.

10. What is Ontology? Dictionary:A branch of metaphysics concerned with the nature and relations of being. Barry Smith:The science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. 1606 1700s

11. So what does that mean? From a practical view, ontology is the representation of something we know about. “Ontologies" consist of a representation of things, that are detectable or directly observable, and the relationships between those things.

12. Sriniga Srinivasan, Chief Ontologist, Yahoo! The ontology. Dividing human knowledge into a clean set of categories is a lot like trying to figure out where to find that suspenseful black comedy at your corner video store. Questions inevitably come up, like are Movies part of Art or Entertainment? (Yahoo! lists them under the latter.) -Wired Magazine, May 1996

13. Molecular Function = elemental activity/task –the tasks performed by individual gene products; examples are carbohydrate binding and ATPase activity Biological Process = biological goal or objective –broad biological goals, such as mitosis or purine metabolism, that are accomplished by ordered assemblies of molecular functions Cellular Component = location or complex –subcellular structures, locations, and macromolecular complexes; examples include nucleus, telomere, and RNA polymerase II holoenzyme The 3 Gene Ontologies

14. Function (what) Process (why) Drive nail (into wood) Carpentry Drive stake (into soil) Gardening Smash roach Pest Control Clown’s juggling object Entertainment Example: Gene Product = hammer

15. Biological Examples Molecular Function Biological Process Cellular Component

16. term: MAPKKK cascade (mating sensu Saccharomyces) goid: GO:0007244 definition: OBSOLETE. MAPKKK cascade involved in transduction of mating pheromone signal, as described in Saccharomyces. definition_reference: PMID:9561267 comment: This term was made obsolete because it is a gene product specific term. To update annotations, use the biological process term 'signal transduction during conjugation with cellular fusion ; GO:0000750'. Terms, Definitions, IDs definition: MAPKKK cascade involved in transduction of mating pheromone signal, as described in Saccharomyces

18. Ontology Includes: 1.A vocabulary of terms (names for concepts) 2.Definitions 3.Defined logical relationships to each other

19. [other types of chromosomes] [other organelles] chromosome organelle nucleus nuclear chromosome

20. Ontologies can be represented as graphs, where the nodes are connected by edges Nodes = terms in the ontology Edges = relationships between the concepts node edge Ontology Structure

21. Chromosome Cytoplasmic chromosome Mitochondrial chromosome Plastid chromosome Nuclear chromosome A child is a subset or instances of a parent’s elements Parent-Child Relationships

22. Ontology Structure The Gene Ontology is structured as a hierarchical directed acyclic graph (DAG) Terms can have more than one parent and zero, one or more children Terms are linked by two relationships –is-a –part-of is_apart_of

23. is-a part-of [other types of chromosomes] [other organelles] chromosome organelle nucleus nuclear chromosome Directed Acyclic Graph (DAG)

24. http://www.ebi.ac.uk/ego

26. Evidence Codes for GO Annotations http://www.geneontology.org/GO.evidence.html

27. Evidence codes Indicate the type of evidence in the cited source* that supports the association between the gene product and the GO term *capturing information

28. Experimental codes - IDA, IMP, IGI, IPI, IEP Computational codes - ISS, IEA, RCA, IGC Author statement - TAS, NAS Other codes - IC, ND Types of evidence codes

29. IDA Inferred from Direct Assay direct assay for the function, process, or component indicated by the GO term Enzyme assays In vitro reconstitution (e.g. transcription) Immunofluorescence (for cellular component) Cell fractionation (for cellular component)

30. IMP Inferred from Mutant Phenotype variations or changes such as mutations or abnormal levels of a single gene product Gene/protein mutation Deletion mutant RNAi experiments Specific protein inhibitors Allelic variation

31. IGI Inferred from Genetic Interaction Any combination of alterations in the sequence or expression of more than one gene or gene product Traditional genetic screens - Suppressors, synthetic lethals Functional complementation Rescue experiments An entry in the ‘with’ column is recommended

32. IPI Inferred from Physical Interaction Any physical interaction between a gene product and another molecule, ion, or complex 2-hybrid interactions Co-purification Co-immunoprecipitation Protein binding experiments An entry in the ‘with’ column is recommended

33. IEP Inferred from Expression Pattern Timing or location of expression of a gene –Transcript levels Northerns, microarray Exercise caution when interpreting expression results

34. ISS Inferred from Sequence or structural Similarity Sequence alignment, structure comparison, or evaluation of sequence features such as composition –Sequence similarity –Recognized domains/overall architecture of protein An entry in the ‘with’ column is recommended

35. RCA Inferred from Reviewed Computational Analysis non-sequence-based computational method –large-scale experiments genome-wide two-hybrid genome-wide synthetic interactions –integration of large-scale datasets of several types –text-based computation (text mining)

36. IGC Inferred from Genomic Context Chromosomal position Most often used for Bacteria - operons –Direct evidence for a gene being involved in a process is minimal, but for surrounding genes in the operon, the evidence is well- established

37. IEA Inferred from Electronic Annotation depend directly on computation or automated transfer of annotations from a database –Hits from BLAST searches –InterPro2GO mappings No manual checking Entry in ‘with’ column is allowed (ex. sequence ID)

38. TAS Traceable Author Statement publication used to support an annotation doesn't show the evidence –Review article Would be better to track down cited reference and use an experimental code

39. NAS Non-traceable Author Statement Statements in a paper that cannot be traced to another publication

40. ND No biological Data available Can find no information supporting an annotation to any term Indicate that a curator has looked for info but found nothing –Place holder –Date

41. IC Inferred by Curator annotation is not supported by evidence, but can be reasonably inferred from other GO annotations for which evidence is available ex. evidence = transcription factor (function) –IC = nucleus (component)

42. Ask yourself: What is the experiment that was done? Choosing the correct evidence code

43. http://www.geneontology.org/GO.evidence.html