Transcript Document
Gene Ontology (GO)
Emily Dimmer
GOA group European Bioinformatics Institute Wellcome Trust Genome Campus Cambridge UK
GO Tutorial Outline:
• Introduction to GO • Description of the GO ontologies • How groups annotate to GO •
Practical:
• Investigating the GO and OBO web sites • Browsing the GO using the AmiGO Browser.
• Open Biomedical Ontologies • How GO is being used • Available Tools • GO slims •
Practical:
• Creating your own GO slim
GO Tutorial Outline:
• Introduction to GO • Description of the GO ontologies • How groups annotate to GO •
Practical:
• Investigating the GO and OBO web sites • Browsing the GO using the AmiGO Browser.
• Open Biomedical Ontologies • How GO is being used • Available Tools • GO slims •
Practical:
• Creating your own GO slim
GO Tutorial Outline:
• Introduction to GO • Description of the GO ontologies • How groups annotate to GO •
Practical:
• Investigating the GO and OBO web sites • Browsing the GO using the AmiGO Browser.
• Open Biomedical Ontologies • How GO is being used • Available Tools • GO slims •
Practical:
• Creating your own GO slim
GO Tutorial Outline:
• Introduction to GO • Description of the GO ontologies • How groups annotate to GO •
Practical:
• Investigating the GO and OBO web sites • Browsing the GO using the AmiGO Browser.
• Open Biomedical Ontologies • How GO is being used • Available Tools • GO slims •
Practical:
• Creating your own GO slim
Why is GO needed ?
THE PROBLEM:
• • Huge body of knowledge with an extremely large vocabulary to describe it Vocabulary used is poorly defined – i.e. one word can have different meanings – or different names for the same concept • Biological systems are complex and our knowledge of such systems is incomplete
RESULT:
Large databases which are difficult to manage and impossible to mine computationally
What is GO?
• A (part of the) solution:
GO
: “a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing”
What can scientists do with GO?
•
Access gene product functional information
•
Provide a link between biological knowledge and …
•
gene expression profiles
•
proteomics data
•
Find how much of a proteome is involved in a process/ function/ component in the cell
• using a GO-Slim (a slimmed down version of GO to summarize biological attributes of a proteome) •
Map GO terms and incorporate manual GOA annotation into own databases
• to enhance your dataset • or to validate automated ways of deriving information about gene function (text-mining).
Tactition Taction
?
Tactile sense
Tactition Taction Tactile sense
perception of touch ; GO:0050975
GO Three (Orthogonal) Ontologies
•
Molecular Function
: elemental activity or task e.g. DNA binding, catalysis of a reaction •
Biological Process
: broad objective or goal e.g. mitosis, signal transduction, metabolism •
Cellular Component
: location or complex e.g. nucleus, ribosome
GO Three (Orthogonal) Ontologies
•
Molecular Function
: elemental activity or task e.g. DNA binding, catalysis of a reaction •
Biological Process
: broad objective or goal e.g. mitosis, signal transduction, metabolism •
Cellular Component
: location or complex e.g. nucleus, ribosome
GO Three (Orthogonal) Ontologies
•
Molecular Function
: elemental activity or task e.g. DNA binding, catalysis of a reaction •
Biological Process
: broad objective or goal e.g. mitosis, signal transduction, metabolism •
Cellular Component
: location or complex e.g. nucleus, ribosome
GO Three (Orthogonal) Ontologies
•
Molecular Function
: elemental activity or task e.g. DNA binding, catalysis of a reaction •
Biological Process
: broad objective or goal e.g. mitosis, signal transduction, metabolism •
Cellular Component
: location or complex e.g. nucleus, ribosome
How does GO work?
• Provides a standard, species-neutral way of representing biology • GO covers ‘normal’ functions and processes
– No pathological processes – No experimental conditions
Content of GO
Molecular Function Biological Process Cellular Component
Total
Definitions:
7,493 terms 9,640 terms 1,634 terms 18,767 terms
16,696 (93.9 %)
What is GO?
•
NOT a system of nomenclature or a list of gene products
•
GO doesn’t attempt to cover all aspects of biology or evolutionary relationships Open Biomedical Ontologies http://obo.sourceforge.net
•
NOT a dictated standard
•
NOT a way to unify databases
http://www.geneontology.org
Reactome
Anatomy of a GO term
• GO terms are composed of: • • • • • •
Term name Unique GO ID Definition (93 % of GO terms are defined) Synonyms (optional) Database references (optional) Relationships to other GO terms
I. The GO Ontologies
Ontologies
• “Ontologies provide controlled, consistent vocabularies to describe concepts and relationships, thereby enabling knowledge sharing” (Gruber 1993)
Ontology applications
Can be used to:
• • • • • •
Formalise the representation knowledge of biological Describe a common and defined vocabulary database annotation for Standardise database submissions Provide unified access to information through ontology-based querying of databases, both human and computational Improve management and integration within databases.
of data Facilitate data mining
Ontology Structure
•
Ontologies can be represented as graphs, where the vertices (nodes and leaves) are connected by edges
.
•
The nodes are concepts in the ontology.
•
The edges are the relationships between the concepts node node
edge
node
Ontology Structure
•
The Gene Ontology is structured as a hierarchical directed acyclic graph (DAG).
•
Terms are linked by two relationships
–
is-a
–
part-of
•
Terms can have more than one parent
Simple hierarchies (Trees) Directed Acyclic Graphs
Directed Acyclic Graph
cell membrane chloroplast mitochondrial chloroplast membrane membrane is-a part-of
True Path Rule
• The path from a child term all the way up to its top-level parent(s) must always be true is-a part-of cell cytoplasm chromosome nuclear chromosome nucleus nuclear chromosome
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 explains why the term is now obsolete
Biological Process Molecular Function Cellular Component Obsolete Biological Process Obsolete Molecular Function Obsolete Cellular Component
Access to the Gene Ontology
• Downloads • formats available: OBO GO XML MySQL OWL (http://www.geneontology.org/GO.downloads) • Web-based tools • AmiGO
(http://www.godatabase.org)
• QuickGO (http://www.ebi.ac.uk/ego)
II. Annotating to GO
Use of GO terms to represent the activities and localizations of gene products.
Basic information needed: 1.
Database object (e.g. a protein or gene identifier) e.g. Q9ARH1 2.
Reference ID e.g. PubMed ID: 12374299 3.
GO term ID e.g. GO:0004674 4.
Evidence code e.g. TAS
GenNav: http://etbsun2.nlm.nih.gov:8000/perl/gennav.pl
J. Clark
et al.
Plant Physiology 2005 (in press)
Two types of GO Annotation:
Electronic Annotation Manual Annotation All annotations
must
: • be attributed to a source.
• indicate what evidence was found to support the GO term-gene/protein association.
Electronic Annotation
• Provides large-coverage • High-quality • BUT annotations tend to use high-level GO terms and provide little detail.
Electronic Annotation
1. Assignment of GO terms to gene products using existing information within database entries
• Manual mapping of GO terms to concepts external to GO (‘translation tables’).
• Proteins then electronically annotated with the relevant GO term(s).
2. Automatic sequence analyses to transfer annotations between highly similar gene products
Electronic Annotation
Fatty acid biosynthesis ( Swiss-Prot Keyword) EC:6.4.1.2 (EC number) IPR000438: Acetyl-CoA carboxylase carboxyl transferase beta subunit ( InterPro entry) MF_00527: Putative 3 methyladenine DNA glycosylase (HAMAP) GO:Fatty acid biosynthesis ( GO:0006633 ) GO:acetyl-CoA carboxylase activity ( GO:0003989 ) GO:acetyl-CoA carboxylase activity (GO:0003989) GO:DNA repair (GO:0006281)
Mappings of external concepts to GO
http://www.geneontology.org/GO.indices.shtml
Evaluation of precision of annotation electronic techniques (InterPro2GO, SPKW2GO, EC2GO)
• Compared manually-curated test set of GO annotated proteins with the electronic annotations • InterPro2GO = most coverage • EC2GO = 67 % of predictions exactly match the manual GO annotation.
• 91-100 % of time the 3 mappings predicted GO terms within the same lineage
Camon et al. BMC Bioinformatics 2005 in press
Manual Annotation
• High–quality, specific gene/gene product associations made, using: • Peer-reviewed papers • Evidence codes to grade evidence
BUT –
is very time consuming and requires trained biologists
Finding GO terms
…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, 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 …
PubMed ID: 12374299 Function: protein serine/threonine kinase activity GO:0004674 Component: integral to plasma membrane GO:0005887 Process: response to wounding GO:0009611
GO Evidence Codes
Code
*IEA IDA IEP *IGI IMP *IPI *ISS TAS NAS *IC RCA ND
Definition IDA: I
nferred from
E
lectronic
A
nnotation
I
nferred from
D
irect
A
ssay •
Enzyme assays I
nferred from
E
xpression
P
•
In vitro reconstitution (transcription) I I
nferred from
G
enetic
I
nteraction
*With column
nferred from
M
utant
P
henotype
Cell fractionation required I
nferred from
P
hysical
I
nteraction
Manually annotated I
nferred from
S
equence
S
imilarity
T
raceable
A
uthor
S
tatement
TAS: N
on-traceable
A
uthor
S
tatement •
In the literature source the original experiments I
nferred from
C
urator
referred to are traceable
Inferred from
R
eviewed
C
omputational
A
nalysis
N
o
D
ata
GO Evidence Codes
• additional needed identifier for annotations using certain evidence codes
Code
*IEA IDA IEP *IGI IMP *IPI *ISS TAS NAS *IC RCA ND
Definition IGI: I
nferred from
E
lectronic
A
•
I
nferred from
D
irect
A
ssay
a gene identifier for the "other" gene involved in the interaction I
nferred from
E
xpression
P
attern
I
nferred from
G
enetic
I
nteraction
I
nferred from
M
utant
P
henotype
IPI: *With column required I I
nferred from nferred from
P S
hysical
I
equence
S T
raceable
A
uthor
S
tatement •
a gene or protein identifier for the "other" protein annotated involved in the interaction N
on-traceable
A
uthor
S
tatement
I
nferred from
C
urator
IC:
Inferred from
R
eviewed
C
•
A
nalysis
GO term from another annotation used as the N
o
D
ata
basis of a curator inference
…some extra things: • Annotation of a gene product to one ontology is independent from its annotation to other ontologies.
• Terms reflecting a normal activity or location are only annotated to.
• Usage of ‘unknown’ GO terms (e.g.
Molecular function unknown GO:0005554
)
…some extra things: Qualifier Information A set of ‘Qualifier’ terms is also available to curators modify the interpretation of an annotation. Allowable values: 1
. NOT
• a gene product is not associated with the GO term • to document conflicting claims in the literature.
2. Contributes to
• distinguishes between individual subunits functions and whole complex functions • (used with GO Function Ontology) 3
. Colocalizes with
• Transiently or peripherally associated with an organelle or complex • where the resolution of an assay is not accurate. (used with GO Component Ontology)
…some extra things: • The Qualifier column can be used to modify the interpretation of an annotation. Allowable values: 1
. NOT
• a gene product is not associated with the GO term • to document conflicting claims in the literature.
2. Contributes to
• distinguishes between individual subunits functions and whole complex functions • (used with GO Function Ontology) 3
. Colocalizes with
• Transiently or peripherally associated with an organelle or complex • where the resolution of an assay is not accurate. (used with GO Component Ontology)
…some extra things: • The Qualifier column can be used to modify the interpretation of an annotation. Allowable values: 1
. NOT
• a gene product is not associated with the GO term • to document conflicting claims in the literature.
2. Contributes to
• distinguishes between individual subunits functions and whole complex functions • (used with GO Function Ontology) 3
. Colocalizes with
• Transiently or peripherally associated with an organelle or complex • where the resolution of an assay is not accurate. (used with GO Component Ontology)
…some extra things: • The Qualifier column can be used to modify the interpretation of an annotation. Allowable values: 1
. NOT
• a gene product is not associated with the GO term • to document conflicting claims in the literature.
2. Contributes to
• distinguishes between individual subunit functions and whole complex functions • (used with GO Function Ontology) 3
. Colocalizes with
• Transiently or peripherally associated with an organelle or complex • where the resolution of an assay is not accurate. (used with GO Component Ontology)
Accessing annotations to the Gene Ontology
1. Downloads • Annotations – gene association files • Ontologies and annotations – MySQL and XML 2. Web-based access • AmiGO
(http://www.godatabase.org)
• QuickGO (http://www.ebi.ac.uk/ego) …among others…
Gene Association File
DB DB_Object_ID DB_Object_Symbol Qualifier UniProt UniProt UniProt GOid DB:Reference Evidence With Aspect P06703 P06703 P06703 S106_HUMAN GO:0008083 GOA:spkw IEA S106_HUMAN NOT GO:0007409 PMID:12152788 NAS S106_HUMAN F P GO:0005515 PMID:12577318 IPI UniProt:P50995 F DB_Object_Name DB_Object_Synonym DB_Object_Type taxon Date Assigned by Calcyclin IPI00027463 protein taxon:9606 20040426 UniProt Calcyclin IPI00027463 protein taxon:9606 20030721 UniProt Calcyclin IPI00027463 protein taxon:9606 20030721 UniProt
• •
via web (GO consortium page)
http://www.geneontology.org/GO.current.annotations.shtml
http://www.geneontology.org/GO.current.annotations.shtml
Summary
• GO is still being developed and updated it requires a serious and ongoing effort.
– the biological community is involved • New model organism databases are joining the GO Consortium annotation effort
Practical session
1. Visit the GO website 2. Visit the OBO website 3. Browse the ontologies using the official GO Consortium Browser – AmiGO
Part 1.
GO web site: www.geneontology.org
OBO web site: http://obo.sourceforge.net
AmiGO: http://www.godatabase.org
GO terms with no children
Querying the GO
Search for GO terms or by Gene symbol/name Filter queries by organism, data source or evidence
Querying the GO
Querying the GO
GOst tool
GOst tool
QuickGO browser: http://www.ebi.ac.uk/ego
QuickGO browser: http://www.ebi.ac.uk/ego
QuickGO browser: http://www.ebi.ac.uk/ego
OBO and Gene Ontology Uses and Tools
Disease
Developmental Stage
Metabolic Molecular
Ontologies
Pathway Anatomy Physiology Phenotype
Beyond GO – Open Biomedical Ontologies
• Orthogonal to existing ontologies to facilitate combinatorial approaches - Share unique identifier space - Include definitions • Anatomies • Cell Types • Sequence Attributes • Temporal Attributes • Phenotypes • Diseases • More….
http://obo.sourceforge.net
Sequence Ontology
http://song.sourceforge.net
• Ontology of ‘small molecular entities’ http://www.ebi.ac.uk/chebi
http://www.fruitfly.org/cgi-bin/ex/go.cgi
Access to GO and its annotations
How to access the Gene ontology and its annotations
1. Downloads • Ontologies – (various – GO, OBO, XML, OWL MySQL) • Annotations – gene association files • Ontologies and Annotations – MySQL and XML 2. Web-based access • AmiGO
(http://www.godatabase.org)
• QuickGO (http://www.ebi.ac.uk/ego)
among others…
http://www.ncbi.nlm.nih.gov/entrez
www.
uniprot
.org/
http://www.ebi.ac.uk/intact
SRS view… http://srs.ebi.ac.uk
www.
ensembl
.org/ www.
ensembl
.org/
www.
ensembl
.org/
What can scientists do with GO?
•
Access gene product functional information
•
Provide a link between biological knowledge and …
•
gene expression profiles
•
proteomics data
•
Find how much of a proteome is involved in a process/ function/ component in the cell
• using a GO-Slim (a slimmed down version of GO to summarize biological attributes of a proteome) •
Map GO terms and incorporate manual GOA annotation into own databases
• to enhance your dataset • or to validate automated ways of deriving information about gene function (text-mining).
Selected Gene Tree:
…analysis of high-throughput data according to GO MicroArray data analysis
time
Defense response Immune response Response to stimulus Toll regulated genes JAK-STAT regulated genes Puparial adhesion Molting cycle hemocyanin Amino acid catabolism Lipid metobolism Peptidase activity Protein catabloism Immune response Immune response Toll regulated genes
attacked control
Bregje Wertheim at the Centre for Evolutionary Genomics, Department of Biology, UCL and Eugene Schuster Group, EBI.
…analysis of high-throughput data according to GO Proteomics data analysis GO classification
Kislinger T et al, Mol Cell Proteomics, 2003
Analysis of Data: Clustering
http://www.geneontology.org/GO.tools
Color indicates up/down regulation GoMiner Tool, John Weinstein
et al
, Genome Biol. 4 (R28) 2003
Example of VLAD Output
Compare annotations associated with the test set to the entire set of GO annotations….
DNA Repair seems to be a common theme.
…overview proteome with GO Slim http://www.ebi.ac.uk/integr8
Off-the-shelf GO slims
http://go.princeton.edu/cgi-bin/GOTermMapper map2slim.pl
• distributed as part of the go-perl package • maps a set of annotations up to their parent GO slim terms
Summary
The Gene Ontology project precipitated a generalized implementation for ontologies for molecular biology Bio-ontologies such as GO have facilitated development of systems for hypothesis generation in biological systems Further integration – creation of cross-products between different ontologies
Practical II – Creation of GO slims using the DAG-Edit tool.
http://sourceforge.net/projects/geneontology/
…loading the GO
…loading the GO
…loading the GO
…loading the GO
…loading the GO
…loading the GO ftp://ftp.geneontology.org/pub/go/ontology/gene_ontology.obo
…loading the GO
…loading the GO
…browsing the GO
…viewing GO terms
…searching for GO terms
…searching for GO terms
…searching for GO terms
…creating a new GO slim
…creating a new GO slim
…creating a new GO slim
…creating a new GO slim
…creating a new GO slim
…creating a renderer for the GO slim
…creating a renderer for the GO slim
…creating a renderer for the GO slim
…creating a renderer for the GO slim
…creating a renderer for the GO slim
…creating a renderer for the GO slim
…adding terms to the GO slim
…adding terms to the GO slim
…adding terms to the GO slim
…adding terms to the GO slim
…filtering GO for terms in the GO slim
…filtering GO for terms in the GO slim
…filtering GO for terms in the GO slim
…removing filters/renderers
…saving the newly created GO slim