Presentation is loading. Please wait.

Presentation is loading. Please wait.

25th June 2007 Jane Lomax Using the Gene Ontology (GO) for analysis of expression data Jane Lomax EMBL-EBI.

Similar presentations


Presentation on theme: "25th June 2007 Jane Lomax Using the Gene Ontology (GO) for analysis of expression data Jane Lomax EMBL-EBI."— Presentation transcript:

1 25th June 2007 Jane Lomax Using the Gene Ontology (GO) for analysis of expression data Jane Lomax EMBL-EBI

2 25th June 2007 Jane Lomax What is the Gene Ontology? Set of standard biological phrases (terms) which are applied to genes/proteins: –protein kinase –apoptosis –membrane

3 25th June 2007 Jane Lomax What is the Gene Ontology? Genes are linked, or associated, with GO terms by trained curators at genome databases –known as ‘gene associations’ or GO annotations Some GO annotations created automatically

4 25th June 2007 Jane Lomax gene -> GO term associated genes GO annotations GO database genome and protein databases

5 25th June 2007 Jane Lomax What is the Gene Ontology? Allows biologists to make queries across large numbers of genes without researching each one individually

6 Copyright ©1998 by the National Academy of Sciences Eisen, Michael B. et al. (1998) Proc. Natl. Acad. Sci. USA 95,

7 25th June 2007 Jane Lomax GO structure GO isn’t just a flat list of biological terms terms are related within a hierarchy

8 25th June 2007 Jane Lomax GO structure gene A

9 25th June 2007 Jane Lomax GO structure This means genes can be grouped according to user-defined levels Allows broad overview of gene set or genome

10 25th June 2007 Jane Lomax How does GO work? GO is species independent –some terms, especially lower-level, detailed terms may be specific to a certain group e.g. photosynthesis –But when collapsed up to the higher levels, terms are not dependent on species

11 25th June 2007 Jane Lomax How does GO work? What does the gene product do? Where and does it act? Why does it perform these activities? What information might we want to capture about a gene product?

12 25th June 2007 Jane Lomax GO structure GO terms divided into three parts: –cellular component –molecular function –biological process

13 25th June 2007 Jane Lomax Cellular Component where a gene product acts

14 25th June 2007 Jane Lomax Cellular Component

15 25th June 2007 Jane Lomax Cellular Component

16 25th June 2007 Jane Lomax Cellular Component Enzyme complexes in the component ontology refer to places, not activities.

17 25th June 2007 Jane Lomax Molecular Function activities or “ jobs ” of a gene product glucose-6-phosphate isomerase activity

18 25th June 2007 Jane Lomax Molecular Function insulin binding insulin receptor activity

19 25th June 2007 Jane Lomax Molecular Function drug transporter activity

20 25th June 2007 Jane Lomax Molecular Function A gene product may have several functions Sets of functions make up a biological process.

21 25th June 2007 Jane Lomax Biological Process a commonly recognized series of events cell division

22 25th June 2007 Jane Lomax Biological Process transcription

23 25th June 2007 Jane Lomax Biological Process regulation of gluconeogenesis

24 25th June 2007 Jane Lomax Biological Process limb development

25 25th June 2007 Jane Lomax Biological Process courtship behavior

26 25th June 2007 Jane Lomax Ontology Structure Terms are linked by two relationships –is-a  –part-of 

27 25th June 2007 Jane Lomax Ontology Structure cell membrane chloroplast mitochondrial chloroplast membrane is-a part-of

28 25th June 2007 Jane Lomax Ontology Structure Ontologies are structured as a hierarchical directed acyclic graph (DAG) Terms can have more than one parent and zero, one or more children

29 25th June 2007 Jane Lomax Ontology Structure cell membrane chloroplast mitochondrial chloroplast membrane Directed Acyclic Graph (DAG) - multiple parentage allowed

30 25th June 2007 Jane Lomax Anatomy of a GO term id: GO: name: gluconeogenesis namespace: process def: The formation of glucose from noncarbohydrate precursors, such as pyruvate, amino acids and glycerol. [http://cancerweb.ncl.ac.uk/omd/index.html] exact_synonym: glucose biosynthesis xref_analog: MetaCyc:GLUCONEO-PWY is_a: GO: is_a: GO: unique GO ID term name definition synonym database ref parentage ontology

31 25th June 2007 Jane Lomax GO terms Where do GO terms come from? –GO terms are added by editors at EBI and annotating databases –new terms are usually only added when they are asked for by annotators –GO editors work with experts to make major ontology developments metabolism pathogenesis cell cycle

32 25th June 2007 Jane Lomax GO stats over 23,000 GO terms: –13593 biological_process –1980 cellular_component –7700 molecular_function

33 25th June 2007 Jane Lomax GO annotations Where do the links between genes and GO terms come from?

34 25th June 2007 Jane Lomax GO annotations Contributing databases: –Berkeley Drosophila Genome Project (BDGP)Berkeley Drosophila Genome Project (BDGP –dictyBase (Dictyostelium discoideum)dictyBase –FlyBase (Drosophila melanogaster)FlyBase –GeneDB (Schizosaccharomyces pombe, Plasmodium falciparum, Leishmania major and Trypanosoma brucei)GeneDBSchizosaccharomyces pombe –UniProt Knowledgebase (Swiss-Prot/TrEMBL/PIR-PSD) and InterPro databasesUniProt KnowledgebaseInterPro –Gramene (grains, including rice, Oryza)Gramene –Mouse Genome Database (MGD) and Gene Expression Database (GXD) (Mus musculus)Mouse Genome Database (MGD) and Gene Expression Database (GXD) –Rat Genome Database (RGD) (Rattus norvegicus) –ReactomeReactome –Saccharomyces Genome Database (SGD) (Saccharomyces cerevisiae)Saccharomyces Genome Database (SGD) –The Arabidopsis Information Resource (TAIR) (Arabidopsis thaliana)The Arabidopsis Information Resource (TAIR) –The Institute for Genomic Research (TIGR): databases on several bacterial speciesThe Institute for Genomic Research (TIGR) –WormBase (Caenorhabditis elegans)WormBase –Zebrafish Information Network (ZFIN): (Danio rerio)Zebrafish Information Network (ZFIN)

35 25th June 2007 Jane Lomax Species coverage All major eukaryotic model organism species Human via GOA group at UniProt Several bacterial and parasite species through TIGR and GeneDB at Sanger –many more in pipeline

36 25th June 2007 Jane Lomax Annotation coverage

37 25th June 2007 Jane Lomax Anatomy of a GO annotation Three key parts: –gene name/id –GO term(s) –evidence for association

38 25th June 2007 Jane Lomax Example annotation Breast cancer type 1 susceptibility protein gene in humans

39 25th June 2007 Jane Lomax Types of GO annotation:  Electronic Annotation  Manual Annotation

40 25th June 2007 Jane Lomax Manual annotation Created by scientific curators High quality Small number

41 25th June 2007 Jane Lomax Manual annotation 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…

42 25th June 2007 Jane Lomax Manual annotation

43 25th June 2007 Jane Lomax Electronic Annotation Annotation derived without human validation –mappings file e.g. interpro2go, ec2go. –Blast search ‘hits’ Lower ‘quality’ than manual codes

44 25th June 2007 Jane Lomax Mappings files Fatty acid biosynthesis ( Swiss-Prot Keyword) EC: (EC number) IPR000438: Acetyl-CoA carboxylase carboxyl transferase beta subunit ( InterPro entry) GO:Fatty acid biosynthesis ( GO: ) GO:acetyl-CoA carboxylase activity ( GO: ) GO:acetyl-CoA carboxylase activity (GO: )

45 25th June 2007 Jane Lomax Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

46 25th June 2007 Jane Lomax GO tools GO resources are freely available to anyone to use without restriction –Includes the ontologies, gene associations and tools developed by GO Other groups have used GO to create tools for many purposes:

47 25th June 2007 Jane Lomax GO tools Affymetrix also provide a Gene Ontology Mining Tool as part of their NetAffx™ Analysis Center which returns GO terms for probe sets

48 25th June 2007 Jane Lomax GO tools Many tools exist that use GO to find common biological functions from a list of genes:

49 25th June 2007 Jane Lomax GO tools Most of these tools work in a similar way: –input a gene list and a subset of ‘interesting’ genes –tool shows which GO categories have most interesting genes associated with them i.e. which categories are ‘enriched’ for interesting genes –tool provides a statistical measure to determine whether enrichment is significant

50 25th June 2007 Jane Lomax Microarray process Treat samples Collect mRNA Label Hybridize Scan Normalize Select differentially regulated genes Understand the biological phenomena involved

51 25th June 2007 Jane Lomax Traditional analysis Gene 1 Apoptosis Cell-cell signaling Protein phosphorylation Mitosis … Gene 2 Growth control Mitosis Oncogenesis Protein phosphorylation … Gene 3 Growth control Mitosis Oncogenesis Protein phosphorylation … Gene 4 Nervous system Pregnancy Oncogenesis Mitosis … Gene 100 Positive ctrl. of cell prolif Mitosis Oncogenesis Glucose transport …

52 25th June 2007 Jane Lomax Traditional analysis gene by gene basis requires literature searching time-consuming

53 25th June 2007 Jane Lomax Using GO annotations But by using GO annotations, this work has already been done for you! GO: : apoptosis

54 25th June 2007 Jane Lomax Grouping by process Apoptosis Gene 1 Gene 53 Mitosis Gene 2 Gene 5 Gene45 Gene 7 Gene 35 … Positive ctrl. of cell prolif. Gene 7 Gene 3 Gene 12 … Growth Gene 5 Gene 2 Gene 6 … Glucose transport Gene 7 Gene 3 Gene 6 …

55 25th June 2007 Jane Lomax GO for microarray analysis Annotations give ‘function’ label to genes Ask meaningful questions of microarray data e.g. –genes involved in the same process, same/different expression patterns?

56 25th June 2007 Jane Lomax Using GO in practice statistical measure –how likely your differentially regulated genes fall into that category by chance microarray 1000 genes experiment100 genes differentially regualted mitosis – 80/100 apoptosis – 40/100 p. ctrl. cell prol. – 30/100 glucose transp. – 20/100

57 25th June 2007 Jane Lomax Using GO in practice However, when you look at the distribution of all genes on the microarray: ProcessGenes on array # genes expected in occurred 100 random genes mitosis 800/ apoptosis 400/ p. ctrl. cell prol. 100/ glucose transp. 50/

58 25th June 2007 Jane Lomax Enrichment tools GO is developing its own enrichment tool as part of the GO browser AmiGO Currently in testing phase, should be released next month

59 25th June 2007 Jane Lomax Onto-Express walkthrough


Download ppt "25th June 2007 Jane Lomax Using the Gene Ontology (GO) for analysis of expression data Jane Lomax EMBL-EBI."

Similar presentations


Ads by Google