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Gene Ontology John Pinney j.pinney@imperial.ac.uk

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  1. Gene Ontology John Pinney j.pinney@imperial.ac.uk

  2. Gene annotation • Goal: • transfer knowledge about the function of gene products from model organisms to other genomes

  3. Gene annotation • Problem: • keyword systems are different between research communities

  4. Gene annotation • Solution: • controlled vocabulary

  5. Ontology • structured • controlled vocabulary

  6. Ontology: • a collection of terms • and their definitions • and the logical relationships between them

  7. Gene Ontology (GO): • a collection of terms • and their definitions • and the logical relationships between them describing gene products

  8. nucleus GO:0005634 “A membrane-bounded organelle of eukaryotic cells in which chromosomes are housed and replicated. In most cells, the nucleus contains all of the cell's chromosomes except the organellar chromosomes, and is the site of RNA synthesis and processing. In some species, or in specialized cell types, RNA metabolism or DNA replication may be absent.”

  9. “part of” cell nucleus nucleoplasm nucleolus nuclear membrane

  10. “is a” intracellular organelle membrane-bounded organelle intracellular membrane-bounded organelle nucleus pronucleus

  11. A term may have more than one parent term and more than one child term. => The gene ontology is not a tree

  12. The gene ontology has a structure known as aDirected Acyclic Graph (DAG). relationships are not symmetrical there are no directed loops mathematical term for a network

  13. GO is actually made up of 3 different ontologies: cellular component molecular function biological process

  14. cellular component “The part of a cell or its extracellular environment in which a gene product is located. A gene product may be located in one or more parts of a cell.”

  15. cellular component examples: cohesin core heterodimer extracellular region laminin-1 complex replication fork transcription factor complex

  16. molecular function “Elemental activities, such as catalysis or binding, describing the actions of a gene product at the molecular level. A given gene product may exhibit one or more molecular functions.”

  17. molecular function examples: transcription factor binding enzyme activator activity 3'-nucleotidase activity metallopeptidase activity hexokinase activity

  18. biological process “Those processes specifically pertinent to the functioning of integrated living units: cells, tissues, organs, and organisms. A process is a collection of molecular events with a defined beginning and end.”

  19. biological process examples: para-aminobenzoic acid biosynthetic process protein localization establishment of blood-nerve barrier circadian rhythm posterior midgut development

  20. geneontology.org

  21. geneontology.org search and browse the ontologies

  22. geneontology.org search and browse the ontologies

  23. geneontology.org download ontologies

  24. geneontology.org download mappings from other databases enzyme functions (EC,KEGG, MetaCyc) protein domains (Pfam, SMART, PRINTS,…) other controlled vocabularies of functions (E. coli functions, MIPS FunCat)

  25. geneontology.org download annotations for various genomes

  26. geneontology.org download annotations for various genomes database gene product ID NCBI_NP NP_354299.2 lolD GO:0043190 ISS "ABC transporter, nucleotide binding/ATPase protein (lipoprotein)" taxon:176299 20070612 PAMGO_GAT gene symbol GO term ID evidence code

  27. evidence codes Allow curators to indicate the type of evidence for each gene-term annotation. experimental computational author statement e.g. IMP Inferred from mutant phenotype IDA Inferred from direct assay e.g. ISS Inferred from sequence similarity IGC Inferred from genome context e.g. TAS Traceable author statement

  28. geneontology.org download annotations for various genomes database gene product ID NCBI_NP NP_354299.2 lolD GO:0043190 ISS "ABC transporter, nucleotide binding/ATPase protein (lipoprotein)" taxon:176299 20070612 PAMGO_GAT gene symbol GO term ID evidence code description organism (taxon) ID date annotation project ID

  29. geneontology.org repository of analysis tools that use GO search, edit and and browse ontologies / annotations software libraries statistical analysis text mining protein interactions enrichment analysis

  30. Enrichment analysis

  31. Which GO terms occur significantly more often than expected in this gene set? whole genome (annotated) significant expression change in a microarray experiment ArrayTrack gene set cluster from a protein interaction network BiNGO some other experiment / analysis GOstat

  32. Advantages of GO single set of terms to describe the function of gene products from all organisms. DAG structure provides a logical framework to represent knowledge at whatever level of detail is available. continually revised to reflect the state of current knowledge. can quantify strength of relationships between terms (semantic similarity). many statistical analysis tools available.

  33. Limitations of GO GO is limited in scope: it does not cover processes that are not normal functions of gene products (e.g. oncogenesis). sequence attributes (e.g. introns/exons) protein structures or interactions evolution gene expression

  34. The gene ontology (GO) is a structured, controlled vocabulary to describe the function of gene products. Terms in GO have logical relationships (“is a”, “part of”) with one another. Together these form a structure called a Directed Acyclic Graph (DAG). GO is formed of 3 separate ontologies describing different aspects of gene function: cellular component, molecular function and biological process. Summary (1)

  35. geneontology.org is the central resource for downloading ontology, annotation and mapping files. evidence codes are used in annotations to show the experimental, computational or literature support for each function. Summary (2)

  36. many software tools are available to support GO analysis of experimental data, including enrichment analysis by ArrayTrack (microarray expression data) BiNGO (protein interaction clusters) GOstat (any data in the form of gene sets) Summary (3)