Presentation is loading. Please wait.

Presentation is loading. Please wait.

EBI is an Outstation of the European Molecular Biology Laboratory. EBI Bioinformatics Roadshow 15 March 2011 Düsseldorf, Germany Rebecca Foulger Introduction.

Similar presentations


Presentation on theme: "EBI is an Outstation of the European Molecular Biology Laboratory. EBI Bioinformatics Roadshow 15 March 2011 Düsseldorf, Germany Rebecca Foulger Introduction."— Presentation transcript:

1 EBI is an Outstation of the European Molecular Biology Laboratory. EBI Bioinformatics Roadshow 15 March 2011 Düsseldorf, Germany Rebecca Foulger Introduction to the Gene Ontology and GO Annotation Resources

2 OUTLINE OF TUTORIAL: PART I: Ontologies and the Gene Ontology (GO) PART II: GO Annotations How to access GO annotations How scientists use GO annotations GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

3 PART I: Gene Ontology GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

4 What’s in a name...? GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

5 Q: What is a cell? A: It really depends who you ask! GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

6 Different things can be described by the same name GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

7 Glucose synthesis Glucose biosynthesis Glucose formation Glucose anabolism Gluconeogenesis The same thing can be described by different names: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

8 Inconsistency in naming of biological concepts Same name for different concepts Different names for the same concept  Comparison is difficult – in particular across species or across databases Just one reason why the Gene Ontology (GO) is is needed… GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

9 Why do we need GO? Large datasets need to be interpreted quickly Inconsistency in naming of biological concepts Increasing amounts of biological data available Increasing amounts of biological data to come GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

10 Increasing amounts of biological data available Search on mesoderm development…. you get 9441 results! Expansion of sequence information GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

11 What is an ontology? Dictionary: A branch of metaphysics concerned with the nature and relations of being (philosophy) A formal representation of the knowledge by a set of concepts within a domain and the relationships between those concepts (computer science) Barry Smith: The science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality s GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

12 What is an ontology? More usefully: An 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. GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

13 What is an ontology? An ontology is more than just a list of terms (a controlled vocabulary) A vocabulary of terms Definitions for those terms *** Defined logical relationships between the terms *** GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

14 What’s in an Ontology? GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

15 What is the Gene Ontology (GO)? A way to capture biological knowledge in a written and computable form Describes attributes of gene products (RNA and protein) GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

16 The scope of GO What information might we want to capture about a gene product? What does the gene product do? Where does it act? How does it act? GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

17 Biological Process what does a gene product do? cell division transcription A commonly recognised series of events GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

18 Cellular Component where is a gene product located? plasma membrane mitochondrion mitochondrial membrane mitochondrial matrix mitochondrial lumen ribosome large ribosomal subunit small ribosomal subunit GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

19 Molecular Function how does a gene product act? insulin binding insulin receptor activity glucose-6-phosphate isomerase activity GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

20 Three separate ontologies or one large one? GO was originally three completely independent hierarchies, with no relationships between them As of 2009, GO have started making relationships between biological process and molecular function in the live ontology GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

21 Function Process GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

22 GO IS: species independent covers normal processes GO is NOT: NO pathological/disease processes NO experimental conditions NO evolutionary relationships NO gene products NOT a nomenclature system GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

23 Aims of the GO project Compile the ontologies Annotate gene products using ontology terms Provide a public resource of data and tools GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

24 Anatomy of a GO term Unique identifier Term name Definition Synonyms Cross- references GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

25 GO 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 relationships, which add to the meaning of the term node edge Ontology structure Nodes = terms in the ontology Edges = relationships between the concepts GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

26

27 Relationships between GO terms is_a part_of regulates positively regulates negatively regulates has_part GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

28 is_a If A is a B, then A is a subtype of B mitotic cell cycle is a cell cycle lyase activity is a catalytic activity. Transitive relationship: can infer up the graph GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

29 part_of Necessarily part of Wherever B exists, it is as part of A. But not all B is part of A. Transitive relationship (can infer up the graph) B A GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

30 regulates One process directly affects another process or quality Necessarily regulates: if both A and B are present, B always regulates A, but A may not always be regulated by B B A GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

31 Relationships are upside down compared to is_a and part_of Necessarily has part has_part GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

32 is_a complete For all terms in the ontology, you have to be able to reach the root through a complete path of is_a relationships: we call this being is_a complete important for reasoning over the ontology, and ontology development GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

33 True path rule Child terms inherit the meaning of all their parent terms. GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

34 How is GO maintained? GO editors and annotators work with experts to remodel specific areas of the ontology Signaling Kidney development Transcription Pathogenesis Cell cycle Deal with requests from the community database curators, researchers, software developers Some simple requests can be dealt with automatically GO Consortium meetings for large changes Mailing lists, conference calls, content workshops GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

35 Requesting changes to the ontology Public Source Forge (SF) tracker for term related issues https://sourceforge.net/projects/geneontology/

36 Why modify the GO? GO reflects current knowledge of biology Information from new organisms can make existing terms and arrangements incorrect Not everything perfect from the outset Improving definitions Adding in synonyms and extra relationships GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

37 Terms become obsolete when they are removed or redefined GO IDs are never deleted For each term, a comment is added to explain why the term is now obsolete Alternative GO terms are suggested to replace an obsoleted term Ensuring Stability in a Dynamic Ontology GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

38 Searching for GO terms … there are more browsers available on the GO Tools page: The latest OBO Gene Ontology file can be downloaded from: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

39 Exercise Browsing the Gene Ontology using QuickGO Exercise 1 GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

40 PART II: GO Annotation GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

41 Reactome E. Coli hub

42 A GO annotation is… A statement that a gene product: 1. has a particular molecular function Or is involved in a particular biological process Or is located within a certain cellular component 2. as determined by a particular method 3. as described in a particular reference GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

43 Evidence codes IDA: enzyme assay IPI: e.g. Y2H review papers subcategories of ISS BLASTs, orthology comparison, HMMs

44 GO evidence code decision tree GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

45 Gene Ontology Annotation (GOA) The GOA database at the EBI is: The largest open-source contributor of annotations to GO Member of the GO Consortium since 2001 Provides annotation for 321,998 species (February 2011 release) GOA’s priority is to annotate the human proteome GOA is responsible for human, chicken and bovine annotations in the GO consortium GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

46 GOA makes annotations using two methods Electronic  Quick way of producing large numbers of annotations Annotations are less detailed Manual  Time-consuming process producing lower numbers of annotations Annotations are very detailed and accurate GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

47 Electronic annotation by GOA 1. Mapping of external concepts to GO terms InterPro2GO (protein domains) SPKW2GO (UniProt/Swiss-Prot keywords) HAMAP2GO (Microbial protein annotation) EC2GO (Enzyme Commission numbers) SPSL2GO (Swiss-Prot subcellular locations ) 2. Automatic transfer of annotations to orthologs Macaque ChimpanzeeGuinea Pig Rat Mouse Cow Dog Chicken Ensembl compara GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

48 Mappings of concepts from UniProtKB files Aspartate transaminase activity ; GO: lipid transport; GO: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

49 Automatic transfer of annotations to orthologs MouseRatZebrafishXenopus Macaque Chimpanzee Guinea Pig Rat Mouse Dog Chicken Human Rat Human Mouse Human Xenopus Tetraodon Fugu Zebrafish Cow Ensembl COMPARA Homologies between different species calculated GO terms projected from MANUAL annotation only (IDA, IEP, IGI, IMP, IPI) One-to-one orthologies used. Currently provides 479,961 GO annotations for 60,515 proteins from 49 species (February 2011 release)

50 Manual annotation by GOA High-quality, specific annotations using: Peer-reviewed papers A range of evidence codes to categorize the types of evidence found in a paper GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

51 Finding annotations in a paper 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: wound response serine/threonine kinase activity, Function: protein serine/threonine kinase activity GO: integral membrane protein Component: integral to plasma membrane GO: …for B. napus PERK1 protein (Q9ARH1) PubMed ID: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

52 Qualifiers Modify the interpretation of an annotation NOT (protein is not associated with the GO term) colocalizes_with (protein associates with complex but is not a bona fide member) contributes_to (describes action of a complex of proteins) 'With' column Can include further information on the method being referenced e.g. the protein accession of an interacting protein Additional information GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

53 The NOT qualifier NOT is used to make an explicit note that the gene product is not associated with the GO term Also used to document conflicting claims in the literature NOT can be used with ALL three gene ontologies GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

54 In these cells, SIPP1 was mainly present in the nucleus, where it displayed a non-uniform, speckled distribution and appeared to be excluded from the nucleoli. excluded from the nucleoli GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

55 The colocalizes_with qualifier ONLY used with GO component ontology Gene products that are transiently or peripherally associated with an organelle or complex GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

56 Immunoblot analysis with anti-PSI polyclonal antibodies of U1 snRNP particles affinity purified from Drosophila embryonic nuclear extracts showed that PSI is physically associated with U1 snRNP (Figure 1A, top panel). Association of U1 snRNP with GST-PSI was detected by ethidium bromide staining of the selected snRNAs and was confirmed by blot hybridization with an antisense U1 snRNA riboprobe (Figure 1C, lane 4). PSI is physically associated with U1 snRNP Association of U1 snRNP with GST-PSI GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

57

58 The contributes_to qualifier Where an individual gene product that is part of a complex can be annotated to terms that describe the action (function or process) of the whole complex contributes_to is not needed to annotate a catalytic subunit. Furthermore, contributes_to may be used for any non-catalytic subunit, whether the subunit is essential for the activity of the complex or not Annotations to contributes_to often use the IC evidence code, but others may also be used. ONLY used with GO function ontology GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

59 ..we next examined whether a complex of four proteins can be formed…. As shown in Figure 4, FLAG-tagged PIG-C was precipitated efficiently with anti- FLAG beads in four combinations with other proteins (Figure 4A, lanes 1–4)….. These results strongly suggest that all four proteins form a complex. GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

60 .. To test whether the protein complex consisting of PIG-A, PIG-H, PIG-C and hGPI1 has GlcNAc transferase activity in vitro…. …incubation of the radiolabeled donor of GlcNAc, UDP- [6-3H]GlcNAc, with lysates of JY5 cells transfected with GST-tagged PIG-A resulted in synthesis of GlcNAc-PI and its subsequent deacetylation to glucosa- minyl phosphatidylinositol (GlcN-PI) whether the protein complex has GlcNAc transferase activity resulted in synthesis of GlcNAc-PI and Its subsequent deacetylation to glucosa-minyl phosphatidylinositol (GlcN-PI) GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

61 Unknown v.s. Unannotated When there is no existing data to support an annotation, gene is annotated to the ROOT (top level) term NOT the same as having no annotation at all No annotation means that no one has looked yet GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

62 WITH column The with column provides supporting evidence for ISS, IPI, IGI and IC evidence codes ISS: the accession of the aligned protein/ortholog IPI: the accession of the interacting protein IGI: the accession of the interacting gene IC: The GO:ID for the inferred_from term WITH column GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

63 How to access GO annotation data GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

64 Where can you find annotations? UniProtKB Ensembl Entrez gene

65 Gene Association Files 17 column files containing all information for each annotation GO Consortium website GOA website

66 GO browsers

67 QuickGO browser Search GO terms or proteins Find sets of GO annotations GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

68 Exercise Searching for GO annotations in QuickGO Exercise 2 Exercise 3 GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

69 Exercise Using QuickGO to create a tailored set of annotations Exercise 4: Filtering Exercise 5: Statistics GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

70 How scientists use the GO, and the tools they use for analysis GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

71 Using GO annotations If you wanted to find out the role of a gene product manually, you’d have to read an awful lot of papers But by using GO annotations, this work has already been done for you! GO: : apoptosis GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

72 How scientists use the GO Access gene product functional information Analyse high-throughput genomic or proteomic datasets Validation of experimental techniques Get a broad overview of a proteome Obtain functional information for novel gene products Some examples… GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

73 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 catabolism Immune response Bregje Wertheim at the Centre for Evolutionary Genomics, Department of Biology, UCL and Eugene Schuster Group, EBI. MicroArray data analysis GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

74 Validation of experimental techniques (Cao et al., Journal of Proteome Research 2006) Rat liver plasma membrane isolation GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

75 Analysis of high-throughput proteomic datasets (Orrù et al., Molecular and Cellular Proteomics 2007) Characterisation of proteins interacting with ribosomal protein S19 GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

76 Obtain functional information for novel gene products MPYVSQSQHIDRVRGAIEGRLPAPGNSSRLVSSWQRSYEQYRLDPGSVIGPRVLTS SELR DVQGKEEAFLRASGQCLARLHDMIRMADYCVMLTDAHGVTIDYRIDRDRRGD FKHAGLYI GSCWSEREEGTCGIASVLTDLAPITVHKTDHFRAAFTTLTCSASPIFAPTG ELIGVLDAS AVQSPDNRDSQRLVFQLVRQSAALIEDGYFLNQTAQHWMIFGHASRN FVEAQPEVLIAFD ECGNIAASNRKAQECIAGLNGPRHVDEIFDTSAVHLHDVARTDTI MPLRLRATGAVLYAR IRAPLKRVSRSACAVSPSHSGQGTHDAHNDTNLDAISRFLHS RDSRIARNAEVALRIAGK HLPILILGETGVGKEVFAQALHASGARRAKPFVAVNCGAIP DSLIESELFGYAPGAFTGA RSRGARGKIAQAHGGTLFLDEIGDMPLNLQTRLLRVLA EGEVLPLGGDAPVRVDIDVICA THRDLARMVEEGTFREDLYYRLSGATLHMPPLRER ADILDVVHAVFDEEAQSAGHVLTLD GRLAERLARFSWPGNIRQLRNVLRYACAVCDS TRVELRHVSPDVAALLAPDEAALRPALA LENDERARIVDALTRHHWRPNAAAEALGM InterProScan GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

77 Annotating novel sequences Can use BLAST queries to find similar sequences with GO annotation which can be transferred to the new sequence Two tools currently available; AmiGO BLAST (from GO Consortium) searches the GO Consortium database BLAST2GO (from Babelomics) searches the NCBI database GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

78 AmiGO BLAST Exportin-T from Pongo abelii (Sumatran orangutan) GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

79 Numerous Third Party Tools Many tools exist that use GO to find common biological functions from a list of genes: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

80 GO tools: enrichment analysis 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 Try exercise 7 at home GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

81 GO slims Many GO analysis tools use GO slims to give a broad overview of the dataset GO slims are cut-down versions of the GO and contain a subset of the terms in the whole GO GO slims usually contain less-specialised GO terms GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

82 Slimming the GO using the ‘true path rule’ Many gene products are associated with a large number of descriptive, leaf GO nodes: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

83 Slimming the GO using the ‘true path rule’ …however annotations can be mapped up to a smaller set of parent GO terms: GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

84 GO slims Custom slims are available for download; Or you can make your own using; QuickGO AmiGO's GO slimmer GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

85 Slimming with QuickGO Map-up annotations with GO slims Search GO terms or proteins Find sets of GO annotations GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

86 Exercise Map-up annotation using a GO slim Exercise 6 GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

87 Just some things to be aware of…. The GO is continually changing New terms created Existing terms obsoleted Re-structured New annotations being created ALWAYS use a current version of ontology and annotations If publishing your analyses, please report the versions/dates you use: Differences in representation of GO terms may be due to biological phenomenon. But also may be due to annotation-bias or experimental assays Often better to remove the ‘NOT’ annotations before doing any large-scale analysis, as they can skew the results ontology annotation GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

88

89 EBI is an Outstation of the European Molecular Biology Laboratory. Thank you


Download ppt "EBI is an Outstation of the European Molecular Biology Laboratory. EBI Bioinformatics Roadshow 15 March 2011 Düsseldorf, Germany Rebecca Foulger Introduction."

Similar presentations


Ads by Google