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Event: Plant and Animal Genomes conference 2012
Speaker: Rachael Huntley

The Gene Ontology (GO) is a well-established, structured vocabulary used in the functional annotation of gene products. GO terms are used to replace the multiple nomenclatures used by scientific databases that can hamper data integration. Currently, GO consists of more than 35,000 terms describing the molecular function, biological process and subcellular location of a gene product in a generic cell. The UniProt-Gene Ontology Annotation (UniProt-GOA) database1 provides high-quality manual and electronic GO annotations to proteins within UniProt. By annotating well-studied proteins with GO terms and transferring this knowledge to less well-studied and novel proteins that are highly similar, we offer a valuable contribution to the understanding of all proteomes. UniProt-GOA provides annotated entries for over 387,000 species and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. Annotation files for various proteomes are released each month, including human, mouse, rat, zebrafish, cow, chicken, dog, pig, Arabidopsis and Dictyostelium, as well as a file for the multiple species within UniProt. The UniProt-GOA dataset can be queried through our user-friendly QuickGO browser2 or downloaded in a parsable format via the EBI3 and GO Consortium FTP4 sites. The UniProt-GOA dataset has increasingly been integrated into tools that aid in the analysis of large datasets resulting from high-throughput experiments thus assisting researchers in biological interpretation of their results. The annotations produced by UniProt-GOA are additionally cross-referenced in databases such as Ensembl and NCBI Entrez Gene.

1 http://www.ebi.ac.uk/GOA

2 http://www.ebi.ac.uk/QuickGO

3 ftp://ftp.ebi.ac.uk/pub/databases/GO/goa

4 ftp://ftp.geneontology.org/pub/go/gene-associations

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  • The English language is not precise
  • Electronic annotations are important for non-model species as these do not have a dedicated manual annotation effort
  • Genes differentially expressed during parasitoid attack versus control
  • UniProt-GOA

    1. 1. Introduction to the Gene Ontology and GO annotation resources Rachael Huntley UniProt-GOA EBI PAGXX January 2012
    2. 2. 2 Why do we need GO?
    3. 3. Reasons for the Gene Ontology www.geneontology.org • Inconsistency in English language
    4. 4. Inconsistency in English languauge • Same name for different concepts or ?? Cell
    5. 5.  Comparison is difficult – in particular across species or across databases Just one reason why the Gene Ontology (GO) is is needed… • Different names for the same concept Eggplant Aubergine Brinjal Melongene Same for biological concepts
    6. 6. Reasons for the Gene Ontology www.geneontology.org • Inconsistency in English language • Increasing amounts of biological data available • Increasing amounts of biological data to come
    7. 7. Search on ‘DNA repair’... get almost 65,000 results Increasing amounts of biological data available Expansion of sequence information
    8. 8. Reasons for the Gene Ontology www.geneontology.org • Inconsistency in English language • Large datasets need to be interpreted quickly • Increasing amounts of biological data available • Increasing amounts of biological data to come
    9. 9. • A way to capture biological knowledge for individual gene products in a written and computable form The Gene Ontology • A set of concepts and their relationships to each other arranged as a hierarchy www.ebi.ac.uk/QuickGO Less specific concepts More specific concepts
    10. 10. 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
    11. 11. Anatomy of a GO term Unique identifierUnique identifier Term nameTerm name DefinitionDefinitionSynonymsSynonyms Cross-referencesCross-references
    12. 12. Ontology structure • Directed acyclic graph Terms can have more than one parent • Terms are linked by relationships is_a part_of regulates (and +/- regulates) www.ebi.ac.uk/QuickGOoccurs_in has_part These relationships allow for complex analysis of large datasets
    13. 13. Reactome http://www.geneontology.org
    14. 14. • Compile the ontologies - currently over 35,000 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 Aims of the GO project
    15. 15. GO Annotation
    16. 16. UniProt-Gene Ontology Annotation (UniProt-GOA) database at the EBI • Largest open-source contributor of annotations to GO • Provides annotation for more than 397,000 species • Our priority is to annotate the human proteome
    17. 17. 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
    18. 18. Electronic Annotation Manual Annotation UniProt-GOA incorporates annotations made 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 tend to use very specific GO terms • Only source of annotation for many non-model organism species
    19. 19. 1. Mapping of external concepts to GO terms e.g. InterPro2GO, UniProt Keyword2GO, Enzyme Commission2GO Electronic annotation methods GO:0004715 ; non-membrane spanning protein tyrosine kinase activity
    20. 20. Annotations are high-quality and have an explanation of the method (GO_REF) Macaque Mouse DogCow Guinea PigChimpanzee Rat Chicken Ensembl compara 2. Automatic transfer of manual annotations to orthologs ...and more e.g. Human Arabidopsis Rice Brachypodium Maize Poplar Grape …and moreEnsembl compara Electronic annotation methods
    21. 21. Manual annotation by GOA High–quality, specific annotations made using: • Full text peer-reviewed papers • A range of evidence codes to categorise the types of evidence found in a paper e.g. IDA, IMP, IPI http://www.ebi.ac.uk/GOA
    22. 22. * Includes manual annotations integrated from external model organism and specialist groups 920,557Manual annotations* 110,247,289Electronic annotations Dec 2011 Statistics Number of annotations in UniProt-GOA database
    23. 23. How to access and use GO annotation data
    24. 24. Where can you find annotations? UniProtKB Ensembl Entrez gene
    25. 25. GO Consortium website Gene Association Files 17 column files containing all information for each annotation http://www.ebi.ac.uk/GOA/downloads.html UniProt-GOA website Numerous species-specific files
    26. 26. GO browsers
    27. 27. http://www.ebi.ac.uk/QuickGO The EBI's QuickGO browser Search GO terms or proteins Find sets of GO annotations
    28. 28. • 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…
    29. 29. Term enrichment • Most popular type of GO analysis • Determines which GO terms are more often associated 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
    30. 30. Numerous Third Party Tools www.geneontology.org/GO.tools.shtml
    31. 31. pears on lw n3d ... : Set_LW_n3d_5p_... Colored by: Copy of Copy of C5_RMA (Defa... Gene List: all genes (14010) 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 cted Gene Tree: pearson lw n3d ... ch 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
    32. 32. Validation of experimental techniques (Cao et al., Journal of Proteome Research 2006) Rat liver plasma membrane isolation
    33. 33. 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 – searches the GO Consortium database BLAST2GO – searches the NCBI database
    34. 34. 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 and contain a subset of the terms in the whole GO • GO slims usually contain less-specialised GO terms
    35. 35. Slimming the GO using the ‘true path rule’ Many gene products are associated with a large number of descriptive, leaf GO nodes:
    36. 36. Slimming the GO using the ‘true path rule’ …however annotations can be mapped up to a smaller set of parent GO terms:
    37. 37. 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 • QuickGO http://www.ebi.ac.uk/QuickGO http://amigo.geneontology.org/cgi-bin/amigo/slimmer
    38. 38. 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 Questions on how to use QuickGO? Contact goa@ebi.ac.uk
    39. 39. The UniProt-GOA group Curators: Software developer: Team leaders: Emily Dimmer Rachael Huntley Rolf Apweiler Email: goa@ebi.ac.uk http://www.ebi.ac.uk/GOA Claire O’Donovan Tony Sawford Yasmin Alam-Faruque Prudence Mutowo
    40. 40. Acknowledgements GO Consortium Members of; UniProtKB InterPro IntAct HAMAP Ensembl Ensembl Genomes Funding National Human Genome Research Institute (NHGRI) Kidney Research UK British Heart Foundation EMBL