EBI is an Outstation of the European Molecular Biology Laboratory.
Introduction to the Gene Ontologyand GO annotation resources
Rachael Huntley
UniProtKB-GOA Curator
EBI
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Talk Overview
• Intro to GO and GO terms
• Annotating to GO
• Practical use of GO
• GO analysis tools
• Precautions
• Accessing GO annotations
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Reasons for the Gene Ontology
www.geneontology.org
• Inconsistency in naming of biological concepts
• Large datasets need to be interpreted quickly
• Increasing amounts of biological data available
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Search on ‘DNA repair’...get over 60,000 results
Increasing amounts of biological data available
Expansion of sequence information
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Reasons for the Gene Ontology
• Inconsistency in naming of biological concepts
• Large datasets need to be interpreted quickly
• Increasing amounts of biological data available
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• Need to organise the data, analyse it, share it in a timely manner to benefit other researchers
• Inconsistencies in analyses make cross-species or cross-database comparison difficult
Large datasets need to be interpreted quickly
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Reasons for the Gene Ontology
• Inconsistency in naming of biological concepts
• Large datasets need to be interpreted quickly
• Increasing amounts of biological data available
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English is not a very precise language
• Same name for different concepts• Different names for the same concept
Inconsistency in naming of biological concepts
?
An example …
Tactition Tactile sense
Taction
Sensory perception of touch ; GO:0050975
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• A way to capture biological knowledge in a written and computable form
The Gene Ontology
• A set of concepts and their relationships to each other arrangedas a hierarchy
www.ebi.ac.uk/QuickGO
Less specific concepts
More specific concepts
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The Concepts in GO
1. Molecular Function
2. Biological Process
3. Cellular Component
An elemental activity or task or job
• protein kinase activity• insulin receptor activity
A commonly recognised series of events
• cell division
Where a gene product is located
• mitochondrion
• mitochondrial matrix
• mitochondrial inner membrane
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Anatomy of a GO term
Unique identifierUnique identifier
Term nameTerm name
DefinitionDefinitionSynonymsSynonyms
Cross-referencesCross-references
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Ontology structure
• Directed acyclic graph
Terms can have more than one parent
• Terms are linked by relationships
is_a
part_of
regulates
+ve regulates
-ve regulateswww.ebi.ac.uk/QuickGO
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http://amigo.geneontology.org/cgi-bin/amigo/go.cgi
… there are more browsers available on the GO Consortium Tools page:
http://www.geneontology.org/GO.tools.shtml
Searching for GO terms
The latest OBO format Gene Ontology file can be downloaded from:
http://www.geneontology.org/ontology/gene_ontology.obo
http://www.ebi.ac.uk/QuickGO
14 http://www.ebi.ac.uk/QuickGO
The EBI's QuickGO browser
Search GO terms or proteins
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GO Annotation
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Reactome
http://www.geneontology.org
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Aims of the GO project
• Compile the ontologies
- currently over 34,000 terms- constantly increasing and improving
• Annotate gene products using ontology terms
- around 30 groups provide annotations • Provide a public resource of data and tools
- regular releases of annotations- tools for browsing/querying annotations and editing the ontology
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Gene Ontology Annotation (UniProtKB-GOA) database at the EBI
• Largest open-source contributor of annotations to GO
• Member of the GO Consortium since 2001
• Provides annotation for more than 360,000 species
• UniProtKB-GOA’s priority is to annotate the human proteome
• UniProtKB-GOA is responsible for human, chicken and bovine annotations in the GO Consortium
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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
P00505
Accession Name GO ID GO term name Reference Evidence code
IDAPMID:2731362aspartate transaminase activityGO:0004069GOT2
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Electronic
Manual
GOA makes annotations using two methods;
• Quick way of producing large numbers of annotations• Annotations use less-specific GO terms
• Time-consuming process producing lower numbers of annotations
• Annotations are very detailed and accurate
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Electronic
Manual
Evidence Codes
Inferred from Direct Assay (IDA) – e.g. enzyme assay
Inferred from Physical Interaction (IPI) – e.g. yeast 2-hybrid
Inferred from Electronic Annotation (IEA) – e.g. UniProtKB keyword mapping
Some examples…
See the full list on the GO Consortium websitehttp://www.geneontology.org/GO.evidence.shtml
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1. Mapping of external concepts to GO terms
e.g. InterPro2GO, Swiss-Prot Keyword2GO, Enzyme Commission2GO
Annotations are high-quality and have an explanation of the method (GO_REF)
Electronic annotation by UniProtKB-GOA
Macaque
Mouse
Dog
e.g. Human
Cow
Guinea PigChimpanzee Rat
Chicken
Ensembl compara
2. Automatic transfer of annotations to orthologs
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Mapping of concepts from UniProtKB files
GO:0004715 ; non-membrane spanning protein tyrosine kinase activity
GO:0005856: cytoskeleton
GO:0007155 ; cell adhesion
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1. Mapping of external concepts to GO terms
e.g. InterPro2GO, Swiss-Prot Keyword2GO, Enzyme Commission2GO
Annotations are high-quality and have an explanation of the method (GO_REF)
Electronic annotation by UniProtKB-GOA
Macaque
Mouse
DogCow
Guinea PigChimpanzee Rat
Chicken
Ensembl compara
2. Automatic transfer of annotations to orthologs
...and more
e.g. Human
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Manual annotation by UniProtKB-GOA
High–quality, specific annotations made using:
• Peer-reviewed papers
• A range of evidence codes to categorise the types of evidence found in a
paper
http://www.ebi.ac.uk/GOA
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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:0009611
wound response
serine/threonine kinase activity,
Function: protein serine/threonine kinase activity GO:0004674
integral membrane protein
Component: integral to plasma membrane GO:0005887
…for B. napus PERK1 protein (Q9ARH1)
PubMed ID: 12374299
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Additional information
• QualifiersModify 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
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GO:0005739 Mitochondrion
HumanProteinAtlas
UniProtKB-GOA integrates manual annotations from external groups
LifeDB (subcellular locations)
Reactome (pathways)
also;
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* Includes manual annotations integrated from external model organism and multi-species databases
Status of UniProtKB-GOA Annotation
0.9%
66%
159,630 910,536Manual annotations*
11,261,38298,037,844Electronic annotations
Proteins Annotations Evidence Source UniProt
Coverage
Aug 2011 Statistics
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How to access and use
GO annotation data
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Where can you find annotations?
UniProtKB
Ensembl
Entrez gene
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GO Consortium website
UniProtKB-GOA website
Gene Association Files17 column files containing all information for each annotation
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GO browsers
34 http://www.ebi.ac.uk/QuickGO
The EBI's QuickGO browser
Search GO terms or proteins
Find sets of GO annotations
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• 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
How scientists use the GO
Some examples…
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Selected Gene Tree: pearson lw n3d ...Branch color classification:Set_LW_n3d_5p_...
Colored by: Copy of Copy of C5_RMA (Defa...Gene List: all genes (14010)
attacked
time
control
Puparial adhesionMolting cycleHemocyanin
Defense responseImmune responseResponse to stimulusToll regulated genesJAK-STAT regulated genes
Immune responseToll regulated genes
Amino acid catabolismLipid metobolism
Peptidase activityProtein catabolismImmune response
Selected Gene Tree: pearson lw n3d ...Branch color classification:Set_LW_n3d_5p_...
Colored by: Copy of Copy of C5_RMA (Defa...Gene List: all genes (14010)
Bregje Wertheim at the Centre for Evolutionary Genomics, Department of Biology, UCL and Eugene Schuster Group, EBI.
MicroArray data analysis
Analysis of high-throughput genomic datasets
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(Orrù et al., Molecular and Cellular Proteomics 2007)
Characterisation of proteins interacting with ribosomal protein S19
Analysis of high-throughput proteomic datasets
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Validation of experimental techniques
(Cao et al., Journal of Proteome Research 2006)
Rat liver plasma membrane isolation
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Obtain functional information for novel gene products
MPYVSQSQHIDRVRGAIEGRLPAPGNSSRLVSSWQRSYEQYRLDPGSVIGPRVLTSSELR DVQGKEEAFLRASGQCLARLHDMIRMADYCVMLTDAHGVTIDYRIDRDRRGDFKHAGLYI GSCWSEREEGTCGIASVLTDLAPITVHKTDHFRAAFTTLTCSASPIFAPTGELIGVLDAS AVQSPDNRDSQRLVFQLVRQSAALIEDGYFLNQTAQHWMIFGHASRNFVEAQPEVLIAFD ECGNIAASNRKAQECIAGLNGPRHVDEIFDTSAVHLHDVARTDTIMPLRLRATGAVLYAR IRAPLKRVSRSACAVSPSHSGQGTHDAHNDTNLDAISRFLHSRDSRIARNAEVALRIAGK HLPILILGETGVGKEVFAQALHASGARRAKPFVAVNCGAIPDSLIESELFGYAPGAFTGA RSRGARGKIAQAHGGTLFLDEIGDMPLNLQTRLLRVLAEGEVLPLGGDAPVRVDIDVICA THRDLARMVEEGTFREDLYYRLSGATLHMPPLRERADILDVVHAVFDEEAQSAGHVLTLD GRLAERLARFSWPGNIRQLRNVLRYACAVCDSTRVELRHVSPDVAALLAPDEAALRPALA LENDERARIVDALTRHHWRPNAAAEALGM
www.ebi.ac.uk/InterProScan
InterProScan
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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) http://amigo.geneontology.org/cgi-bin/amigo/blast.cgi
– searches the GO Consortium database
BLAST2GO (from Babelomics) http://www.blast2go.org/
– searches the NCBI database
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AmiGO BLAST
amigo.geneontology.org/cgi-bin/amigo/blast.cgi
Exportin-T from Pongo abelii (Sumatran orangutan)
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Analysis of large datasets using GO
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Using the GO to provide a functional overview for a large dataset
• Many GO analysis tools use GO slims to give a broad overview of the dataset
• GO slims are cut-down versions of the GO andcontain a subset of the terms in the whole GO
• GO slims usually contain less-specialised GO terms
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Slimming the GO using the ‘true path rule’ Many gene products are associated with a large number of descriptive, leaf GO nodes:
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Slimming the GO using the ‘true path rule’ …however annotations can be mapped up to a smaller set of parent GO terms:
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GO slims
or you can make your own using;
Custom slims are available for download;
http://www.geneontology.org/GO.slims.shtml
• AmiGO's GO slimmer
• QuickGOhttp://www.ebi.ac.uk/QuickGO
http://amigo.geneontology.org/cgi-bin/amigo/slimmer
47 www.ebi.ac.uk/QuickGO
Map-up annotations with GO slims
The EBI's QuickGO browser
Search GO terms or proteins
Find sets of GO annotations
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GO analysis tools
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Numerous Third Party Tools
www.geneontology.org/GO.tools.shtml
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Term enrichment
• Most popular type of GO analysis
• Determines which GO terms are more oftenassociated with a specified list of genes/proteins compared with a control list or rest of genome
• Many tools available to do this analysis
• User must decide which is best for their analysis
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Precautions when using GO annotations for analysis
• Recommended that ‘NOT’ annotations are removed before analysis - only ~5000 out of ~100 million annotations are ‘NOT’- can confuse the analysis
• The Gene Ontology is always changing and GO annotations are continually being created
- always use a current version of both
- if publishing your analyses please report the versions/dates you used
http://www.geneontology.org/GO.cite.shtml
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Precautions when using GO annotations for analysis
• Unannotated is not unknown
- where there is no evidence in the literature for a process, function orlocation the gene product is annotated to the appropriate ontology’sroot node with an ‘ND’ evidence code (no biological data), thereby distinguishing between unannotated and unknown
• Pay attention to under-represented GO terms- a strong under-representation of a pathway may mean that normalfunctioning of that pathway is necessary for the given condition
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The UniProtKB-GOA group
Curators:
Software developer:
Team leaders:
Emily DimmerRachael Huntley
Rolf Apweiler
Email: [email protected]
http://www.ebi.ac.uk/GOA
Claire O’Donovan
Tony Sawford
Yasmin Alam-Faruque
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Acknowledgements
GO ConsortiumMembers of;
UniProtKB
InterPro
IntAct
HAMAP
FundingNational Human Genome Research Institute (NHGRI)Kidney Research UKEMBL
