Applications of GO. Goals of Gene Ontology Project.

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Presentation transcript:

Applications of GO

Goals of Gene Ontology Project

1. Create controlled vocabularies – terms and definitions

Goals of Gene Ontology Project 1. Create controlled vocabularies – terms and definitions 2. Produce annotations to terms – gene product -> GO terms

Goals of Gene Ontology Project 1. Create controlled vocabularies – terms and definitions 2. Produce annotations to terms – gene product -> GO terms 3. Produce GO tools – browsing, searching and editing

Goals of Gene Ontology Project 1. Create controlled vocabularies – terms and definitions 2. Produce annotations to terms – gene product -> GO terms 3. Produce GO tools – browsing, searching and editing Make everything publicly available

Annotations to GO ‘Gene associations’ Associations between a gene/gene product and GO terms Association made to each of the ontologies gene product cellular component biological process molecular function

Annotations to GO Three key parts: –gene name/id

Annotations to GO Three key parts: –gene name/id –GO term

Annotations to GO Three key parts: –gene name/id –GO term(s) –evidence for association

Gene association file Importin alpha-3 subunitIPI protein taxon: SPTR Importin alpha-3 subunitIPI protein taxon: SPTR Importin alpha-3 subunitIPI protein taxon: SPTR SPTRO00505IMA3_HUMANGO: GOA:interpro IEA P SPTRO00505IMA3_HUMANGO: GOA:spkw IEA C SPTRO00505IMA3_HUMANGO: PUBMED: TAS C intracellular protein transport nucleus nuclear pore

Types of GO annotation:  Electronic Annotation  Manual Annotation

Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

Evidence types ISS: Inferred from Sequence/structural Similarity IDA: Inferred from Direct Assay IPI: Inferred from Physical Interaction IMP: Inferred from Mutant Phenotype IGI: Inferred from Genetic Interaction IEP: Inferred from Expression Pattern TAS: Traceable Author Statement NAS: Non-traceable Author Statement IC: Inferred by Curator ND: No Data available IEA: Inferred from electronic annotation

Inferred by Electronic Annotation Annotation derived without human validation –mappings file e.g. interpro2go, ec2go. –Blast search ‘hits’ Lower ‘quality’ than experimental codes

Mappings files Fatty acid biosynthesis ( Swiss-Prot Keyword) EC: (EC number) IPR000438: Acetyl-CoA carboxylase carboxyl transferase beta subunit ( InterPro entry) GO:Fatty acid biosynthesis ( GO: ) GO:acetyl-CoA carboxylase activity ( GO: ) GO:acetyl-CoA carboxylase activity (GO: )

Gene association file Importin alpha-3 subunitIPI protein taxon: SPTR Importin alpha-3 subunitIPI protein taxon: SPTR Importin alpha-3 subunitIPI protein taxon: SPTR SPTRO00505IMA3_HUMANGO: GOA:interpro IEA P SPTRO00505IMA3_HUMANGO: GOA:spkw IEA C SPTRO00505IMA3_HUMANGO: PUBMED: TAS C using an InterPro to GO mappings file using a Swiss-Prot keyword to GO mappings file

Submitting gene associations Many model organism databases –Drosophila, mouse, Saccharomyces, rat, zebrafish, prokaryotes, Arabidopsis, slime mould, C. elegans, rice, parasites, viruses Swiss-Prot (UniProt) –Associations for >8000 species including human

Databases UniProt GOA-Human GO fly yeast worm man mouserat plants parasite bacteria fish UniProt GOA-SPTR All Species

Finding GO terms 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…

GO slims Restricted view of the ontologies Give broad view of gene function Can be organism-specific or generic –plant –mammal –microbe

GO slims

GO for microarray analysis Annotations give ‘function’ label to genes Ask meaningful questions of microarray data e.g. –genes involved in the same process, same/different expression patterns?

GO for microarray analysis experimental condition Gene component process function

The tutorial Part I –Navigating GO and its annotations using Part II –Analysing microarray data using GO with