1. Introduction to the Gene Ontology and GO Annotation Resources
EBI Bioinformatics Roadshow 15 March Düsseldorf, Germany
Rebecca Foulger

2. OUTLINE OF TUTORIAL: PART I:. Ontologies and the Gene
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. A: It really depends who you ask!
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. The same thing can be described by different names:
Glucose synthesis
Glucose biosynthesis
Glucose formation
Glucose anabolism
Gluconeogenesis
All refer to the process of making glucose from simpler components
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…
English is not a very precise language. This makes it difficult to carry out comparisons across species or databases.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

9. Why do we need GO? Inconsistency in naming of biological concepts
Increasing amounts of biological data available
Large datasets need to be interpreted quickly
Large datasets need to be interpreted quickly: Nee to organise data, analyse it, share it to benefit other researchers. People’s time is expensive so we need a quick and effective way to do this.
GO is computer compliant.
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? 1606 1700s 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.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

12. is part of 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.
is part of
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 ***
Ontologies go a step beyond controlled vocabularies, to model the relationships between them
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)
Biologists use up a lot of time and effort in searching for all of the available information about each small area of research.
The Gene Ontology (GO) project is a collaborative effort to address the need for consistent descriptions of gene products in different databases.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

16. What information might we want to capture about a gene product?
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?
A commonly recognised series of events
transcription
cell division
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
An elemental activity or task or job
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
Functions are mini-processes.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

21. Process Function Function
It makes sense to connect the transports to the process they’re involved in
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

22. covers normal processes GO is NOT: NO pathological/disease processes
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
Currently 31,821 and growing daily
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

24. Anatomy of a GO term Unique identifier Term name Definition Synonyms
17800 terms in three ontologies
94% of terms defined
Cross-references
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

25. Ontology structure
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
Nodes = terms in the ontology
Edges = relationships between the concepts
GO isn’t just a flat list of terms
Nodes connected by edges
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

26. GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

27. Relationships between GO terms
is_a
part_of
regulates
positively regulates
negatively regulates
has_part
GO currently has 4 relationship types
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. A B 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) A B
E.g. All replication forks are part of a chromosome.
Not all chromosomes have replication forks.
Is_a & part_of relationships work such that the parent term is broader (more general) than the child term.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

30. A B 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 A B
cycle checkpoints regulate the cell cycle.
The cell cycle is not solely regulated by cell cycle checkpoints
There’s no inference made about specificity. For is_a, and part_of relationships, then term nearest the node (the top) is more general than its child (which is more specific). You can’t infer this from a regulates relationship.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

31. has_part Relationships are upside down compared to is_a and part_of
Necessarily has part
All nuclei have chromosomes. Not all chromosomes are part of nuclei
There’s two versions of GO for download: a full and a public version. Only the full version has has_part relationships at the moment.
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
Other rules are applied to GO to make it ontologically correct
Everything needs to be is_a something
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

33. True path rule
Child terms inherit the meaning of all their parent terms.
If this goes wrong, you get true path violations.
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 is a very rapidly developing ontology - the editorial office is here on site at EBI, and there are several of us who edit the ontologies full-time, plus others at the model organism databases who also edit the ontologies.
We edit and develop the ontologies in response to requests from the community, which in this case is people from the genome and protein databases who are creating GO annotations, from research scientists who are concerned we represent their fields correctly, and from people developing tools using GO.
These requests are now managed via a tracker system on sourceforge.net, which allows us to log them and for others to comment.
Changes to the ontologies are discussed over various mailing lists, and major changes to the ontologies, as well as changes to format etc are discussed at three times yearly consortium meetings.
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
Web-based tracking system hosted at SourceForge
Public
Tracker item for each new request or question

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
Most of what editorial office do is in response to annotator needs - firefighting
We don’t develop terms prospectively unless needed for annotation
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

37. Ensuring Stability in a Dynamic Ontology
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
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. Browsing the Gene Ontology using QuickGO
Exercise
Browsing the Gene Ontology using QuickGO
Exercise 1
Try searching for ‘apoptosis’ and repeat the search using at least one other term name, to give you an idea of the type of terms in GO… mitochondrion, heart development, isomerase activity, protein kinase activity.
Autocomplete in search box.
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. http://www.geneontology.org Reactome
E. Coli hub
Reactome
The GO Consortium has grown to include many databases, including several of the world's major repositories for plant, animal and microbial genomes.

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
Minimal information required for a GO annotation.
Every annotation requires a GO ID, a reference, and an evidence code (gives you an idea of what methods were done to find out that info)
Accession
Name
GO ID
GO term name
Reference
Evidence Code
P00505
GOT2
GO:
Aspartate transaminase activity
PMID:
IDA
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

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

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
Annotations are high-quality and have an explanation of the method.
Ensembl compara
Macaque Chimpanzee
Guinea Pig Rat Mouse
Cow
Dog Chicken
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

48. Mappings of concepts from UniProtKB files
Aspartate transaminase activity ; GO:
A manually produced translation table is run over UniProt entries
currently 13,608 external identifiers have been mapped to GO producing 51,155,464 annotations
lipid transport; GO:006869
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

49. Automatic transfer of annotations to orthologs
Human
Mouse
Rat
Zebrafish
Xenopus
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)
Macaque Chimpanzee
Xenopus
Zebrafish
Human
Human
Guinea Pig Rat Mouse
Tetraodon
Rat
Mouse
Cow
Dog Chicken
Fugu

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
…for B. napus PERK1 protein (Q9ARH1)
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…
serine/threonine kinase activity,
integral membrane protein
wound response
PubMed ID:
…piece of text…from which can pull out GO terms
Generally use the abstract as a summary, and go to the method section of a paper to pull out the associations
Function: protein serine/threonine kinase activity GO:
Component: integral to plasma membrane GO:
Process: response to wounding GO:
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

52. Additional information
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
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
E.g. if the authors show that a protein is NOT found in the nucleolus.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

54. excluded from the nucleoli
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
Gene products that are transiently or peripherally associated with an organelle or complex
ONLY used with GO component ontology
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

56. PSI is physically associated with U1 snRNP
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. The reason for the association becomes clear as the authors show that the protein interact with one of the U1snRNP complex members.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

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

69. Using QuickGO to create a tailored
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!
But by using GO annotations, this work has already been done for you - someone has already sat down and associated a particular gene with a particular process…
Saves loads of time… especially given a list of thousands of gene products
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. JAK-STAT regulated genes
attacked
time
control
Puparial adhesion
Molting cycle
Hemocyanin
Defense response
Immune response
Response to stimulus
Toll regulated genes
JAK-STAT regulated genes
Amino acid catabolism
Lipid metobolism
Peptidase activity
Protein catabolism
MicroArray data analysis
Treat samples
Collect mRNA
Label
Hybridize
Scan
Normalize
Select differentially regulated genes
Understand the biological phenomena involved
Bregje Wertheim at the Centre for Evolutionary Genomics, Department of Biology, UCL and Eugene Schuster Group, EBI.
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

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

75. Analysis of high-throughput proteomic datasets
Characterisation of proteins interacting with ribosomal protein S19
(Orrù et al., Molecular and Cellular Proteomics 2007)
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. Exportin-T from Pongo abelii (Sumatran orangutan)
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:
Freely available for use
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 Search GO terms or proteins Find sets of
GO annotations
Map-up annotations
with GO slims
GO and GO Annotation, EBI Bioinformatics Roadshow. Düsseldorf. March 2011

86. Map-up annotation using a GO slim
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

89. Thank you