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The Gene Ontology, or GO, is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species[1]. The aims of the Gene Ontology project are threefold; firstly, to maintain and further develop its controlled vocabulary of gene and gene product attributes; secondly, to annotate genes and gene products, and assimilate and disseminate annotation data; and thirdly, to provide tools to facilitate access to all aspects of the data provided by the Gene Ontology project.

The GO is part of a larger classification effort, the Open Biomedical Ontologies (OBO).

Contents

GO terms and the GO ontology

The Gene Ontology project provides an ontology of defined terms representing gene product properties. The ontology covers three domains; cellular component, the parts of a cell or its extracellular environment; molecular function, the elemental activities of a gene product at the molecular level, such as binding or catalysis; and biological process, operations or sets of molecular events with a defined beginning and end, pertinent to the functioning of integrated living units: cells, tissues, organs, and organisms. Each GO term within the ontology has a term name, which may be a word or string of words; a unique alphanumeric identifier; a definition with cited sources; and a namespace indicating the domain to which it belongs. Terms may also have synonyms, which are classed as being exactly equivalent to the term name, broader, narrower, or related; references to equivalent concepts in other databases; and comments on term meaning or usage. The GO ontology is structured as a directed acyclic graph, and each term has defined relationships to one or more other terms in the same domain, and sometimes to other domains. The GO vocabulary is designed to be species-neutral, and includes terms applicable to prokaryotes and eukaryotes, single and multicellular organisms.

The GO ontology is not static, and additions, corrections and alterations are suggested by, and solicited from, members of the research and annotation communities, as well as by those directly involved in the GO project. For example, an annotator may request a specific term to represent a metabolic pathway, or a section of the ontology may be revised with the help of community experts (e.g. [2]). Suggested edits are reviewed by the ontology editors, and implemented where appropriate.


The GO ontology file is freely available from the GO website in a number of formats, or can be accessed online using the GO browser AmiGO. The Gene Ontology project also provides downloadable mappings of its terms to other classification systems.

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Example GO Term

id:         GO:0000016
name:       lactase activity
namespace:  molecular_function
def:        "Catalysis of the reaction: lactose + H2O = D-glucose + D-galactose." [EC:3.2.1.108]
synonym:    "lactase-phlorizin hydrolase activity" BROAD [EC:3.2.1.108]
synonym:    "lactose galactohydrolase activity" EXACT [EC:3.2.1.108]
xref:       EC:3.2.1.108
xref:       MetaCyc:LACTASE-RXN
xref:       Reactome:20536
is_a:       GO:0004553 ! hydrolase activity, hydrolyzing O-glycosyl compounds

Data source: [3]

GO annotation

Genome annotation is the practice of capturing data about a gene product, and GO annotations use terms from the GO ontology to do so. The members of the GO Consortium submit their annotation for integration and dissemination on the GO website, where they can be downloaded directly or viewed online using AmiGO. In addition to the gene product identifier and the relevant GO term, GO annotations have the following data:

  • The reference used to make the annotation (e.g. a journal article)
  • An evidence code denoting the type of evidence upon which the annotation is based
  • The date and the creator of the annotation

The evidence code comes from the Evidence Code Ontology, a controlled vocabulary of codes covering both manual and automated annotation methods. For example, Traceable Author Statement (TAS) means a curator has read a published scientific paper and the metadata for that annotation bears a citation to that paper; Inferred from Sequence Similarity (ISS) means a human curator has reviewed the output from a sequence similarity search and verified that it is biologically meaningful. Annotations from automated processes (for example, remapping annotations created using another annotation vocabulary) are given the code Inferred from Electronic Annotation (IEA). As these annotations are not checked by a human, the GO Consortium considers them to be less reliable and does not include them in the data available online in AmiGO. Full annotation data sets can be downloaded from the GO website.

Example GO Annotation

Gene product:    Actin, alpha cardiac muscle 1, UniProtKB:P68032
GO term:         heart contraction ; GO:0060047 (biological process)
Evidence code:   Inferred from Mutant Phenotype (IMP)
Reference:       PMID:17611253
Assigned by:     UniProtKB, June 06, 2008

Data source: [4]

GO Tools

There are a large number of tools available both online and to download that use the data provided by the GO project. The vast majority of these come from third parties; the GO Consortium develops and supports two tools, AmiGO and OBO-Edit.

AmiGO[5] is a web-based application that allows users to query, browse and visualize ontologies and gene product annotation data. In addition, it also has a BLAST tool[6], tools allowing analysis of larger data sets[7][8], and an interface to query the GO database directly[9].

AmiGO can be used online at the GO website to access the data provided by the GO Consortium, or can be downloaded and installed for local use on any database employing the GO database schema (e.g. [10]). It is free open source software and is available as part of the go-dev software distribution[11].


OBO-Edit[12] is an open source, platform-independent ontology editor developed and maintained by the Gene Ontology Consortium. It is implemented in Java, and uses a graph-oriented approach to display and edit ontologies. OBO-Edit includes a comprehensive search and filter interface, with the option to render subsets of terms to make them visually distinct; the user interface can also be customized according to user preferences. OBO-Edit also has a reasoner that can infer links that have not been explicitly stated, based on existing relationships and their properties. Although it was developed for biomedical ontologies, OBO-Edit can be used to view, search and edit any ontology. It is freely available to download[11].

The GO Consortium

The GO Consortium is the set of biological databases and research groups actively involved in the GO project[13]. This includes a number of model organism databases and multi-species protein databases, software development groups, and a dedicated editorial office.

History

The Gene Ontology was originally constructed in 1998 by a consortium of researchers studying the genome of three model organisms: Drosophila melanogaster (fruit fly), Mus musculus (mouse), and Saccharomyces cerevisiae (brewers' or bakers' yeast)[14]. Many other model organism databases have joined the Gene Ontology consortium, contributing not only annotation data, but also contributing to the development of the ontologies and tools to view and apply the data. As of January 2008, GO contains over 24,500 terms applicable to a wide variety of biological organisms. There is a significant body of literature on the development and use of GO, and it has become a standard tool in the bioinformatics arsenal.

See also

References

  1. ^ The Gene Ontology Consortium (Jan 2008). "The Gene Ontology project in 2008.". Nucleic acids research 36: D440–4. doi:10.1093/nar/gkm883. PMID 17984083.  
  2. ^ Diehl AD, Lee JA, Scheuermann RH, Blake JA (2007). "Ontology development for biological systems: immunology.". Bioinformatics 23: 913–915. doi:10.1093/bioinformatics/btm029. PMID 17267433.  
  3. ^ The GO Consortium (2009-03-16). "gene_ontology.1_2.obo" (OBO 1.2 flat file). http://www.geneontology.org/ontology/obo_format_1_2/gene_ontology.1_2.obo. Retrieved 2009-03-16.  
  4. ^ The GO Consortium (2009-03-16). "AmiGO: P68032 Associations". http://amigo.geneontology.org/cgi-bin/amigo/gp-assoc.cgi?gp=UniProtKB:P68032. Retrieved 2009-03-16.  
  5. ^ Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S; AmiGO Hub; Web Presence Working Group. (2008). "AmiGO: online access to ontology and annotation data.". Bioinformatics 25(2): 288–9. doi:10.1093/bioinformatics/btn615. PMID 19033274.  
  6. ^ AmiGO BLAST tool
  7. ^ AmiGO Term Enrichment tool; finds significant shared GO terms in an annotation set
  8. ^ AmiGO Slimmer; maps granular annotations up to high-level terms
  9. ^ GOOSE, GO Online SQL Environment; allows direct SQL querying of the GO database
  10. ^ The Plant Ontology Consortium (2009-03-16). "Plant Ontology Consortium". http://plantontology.org/amigo/go.cgi. Retrieved 2009-03-16.  
  11. ^ a b "Gene Ontology downloads at SourceForge". http://sourceforge.net/project/showfiles.php?group_id=36855. Retrieved 2009-03-16.  
  12. ^ Day-Richter J, Harris MA, Haendel M; Gene Ontology OBO-Edit Working Group, Lewis S. (2007). "OBO-Edit--an ontology editor for biologists.". Bioinformatics 23(16): 2189–200. doi:10.1093/bioinformatics/btm112. PMID 17545183.  
  13. ^ "The GO Consortium". http://www.geneontology.org/GO.consortiumlist.shtml. Retrieved 2009-03-16.  
  14. ^ The Gene Ontology Consortium (2000). "Gene Ontology: tool for the unification of biology". Nature Genetics 25: 25–29. doi:10.1038/75556. PMID 10802651.  

External links


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