A Rough Guide to GO Annotation

In simple terms, a GO annotation is the manual or electronic association of a GO term representing a biological process, cellular component, or molecular function term with a gene product. The evidence for the association is captured by recording the reference, and the nature of the evidence is classified using a code from the GO evidence code set. Every GO annotation created by the GO Consortium follows strict annotation guidelines; see the GO annotation guide for more information.

The process of annotation (the association of GO terms to gene products) can be carried out either manually or automatically. The large-scale assignment of gene products to GO terms using automatic methods is a fast and efficient way of creating a large set of annotations. However, in order for these associations to be correct many of these electronic GO annotations use high level (i.e. rather general) GO terms and often only provide the most minimal overview of the associated gene products functions. Details on the electronic methods applied can be found in Camon et al., 2004 and the GO References page. Manual, comprehensive GO annotations created by assessing experimental evidence from the latest published literature produces far more reliable and detailed GO annotation sets. Manual annotation is a slow, expensive activity, however, and annotation groups need to carefully prioritize their annotation target sets.

The cardiovascular GO annotation initiative will focus on manual annotation of human genes known, or thought, to be involved in cardiovascular processes. Since November 2007, two annotators skilled in GO curation have begun to manually and comprehensively annotate the experimental literature associated with the list of cardiovascular relevant genes. During the course of this project, 1500 well-known genes relevant to the cardiovascular system will be comprehensively annotated, with the close involvement of many cardiovascular groups.

An example of the improved information that can be supplied by carrying out GO annotation can be seen in the example below:

Manual annotation of the human SMAD3 gene before the start of the cardiovascular GO annotation initiative

GO term	Evidence code	Reference
Biological Process (2 terms)
GO:0006366 : transcription from RNA polymerase II promoter	TAS	PMID:10823886 [external website]
GO:0007179 : transforming growth factor beta receptor signaling pathway	TAS	PMID:8774881 [external website]
Molecular Function (2 terms)
GO:0003700 : transcription factor activity	TAS	PMID:10823886 [external website]
GO:0005515 : protein binding	IPI	PMID:14612439 [external website]
Cellular Component (1 term)
GO:0005622 : intracellular	IC	PMID:14612439 [external website]

Manual annotation of the human SMAD3 gene after GO annotation by cardiovascular GO annotation initiative curators (multiple GO term entries only represented once)

GO term	Evidence code	Reference
Biological Process (14 terms)
GO:0006366 : transcription from RNA polymerase II promoter	TAS	PMID:10823886 [external website]
GO:0000122 : negative regulation of transcription from RNA polymerase II promoter	IDA	PMID:8774881 [external website]
GO:0001666 : response to hypoxia	IMP	PMID:12411310 [external website]
GO:0006917 : induction of apoptosis	IMP	PMID:15334054 [external website]
GO:0006919 : caspase activation	IMP	PMID:15107418 [external website]
GO:0007050 : cell cycle arrest	IMP	PMID:14555988 [external website]
GO:0007183 : SMAD protein complex assembly	IDA	PMID:10823886 [external website]
GO:0017015 : regulation of transforming growth factor beta receptor signaling pathway	IMP	PMID:8774881 [external website]
GO:0019049 : evasion of host defenses by virus	IDA	PMID:15334054 [external website]
GO:0030308 : negative regulation of cell growth	IDA	PMID:8774881 [external website]
GO:0032909 : regulation of transforming growth factor-beta2 production	IMP	PMID:12411310 [external website]
GO:0042993 : positive regulation of transcription factor import into nucleus	IDA	PMID:15799969 [external website]
GO:0045930 : negative regulation of mitotic cell cycle	IMP	PMID:14555988 [external website]
GO:0045944 : positive regulation of transcription from RNA polymerase II promoter	IDA	PMID:8774881 [external website]
Molecular Function (6 terms)
GO:0003700 : transcription factor activity	TAS	PMID:10823886 [external website]
GO:0005515 : protein binding	IPI	PMID:14612439 [external website]
GO:0015460 : transport accessory protein activity	IDA	PMID:15799969 [external website]
GO:0042803 : protein homodimerization activity	IPI	PMID:8774881 [external website]
GO:0043565 : sequence-specific DNA binding	IDA	PMID:10823886 [external website]
GO:0046332 : SMAD binding	IPI	PMID:8774881 [external website]
Cellular Component (4 terms)
GO:0005622 : intracellular	IC	PMID:14612439 [external website]
GO:0005634 : nucleus	IDA	PMID:12446380 [external website]
GO:0005737 : cytoplasm	IDA	PMID:12446380 [external website]
GO:0043235 : receptor complex	IMP	PMID:8774881 [external website]

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Recommended reading

The following article provides a general introduction to GO for biologists:

Lomax J, The Gene Ontology Consortium
Get ready to GO! A biologist's guide to the Gene Ontology.
Brief Bioinform. 2005 ; 6: 298-304. (PubMed abstract [external website])

The following article provides a general introduction to the GOA database at EBI and explains electronic and manual annotation techniques:

Camon E, Magrane M, Barrell D, Lee V, Dimmer E, Maslen J, Binns D, Harte N, Lopez R, Apweiler R
The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology.
Nucleic Acids Res. 2004 ; 32: D262-D266. (PubMed abstract [external website]; full text [external website])

The following article provides a summary of the aims of the Cardiovascular GO Annotation Initiative:

Lovering RC, Dimmer E, Khodiyar VK, Barrell DG, Scambler P, Hubank M, Apweiler R, Talmud PJ.
Cardiovascular GO annotation initiative year 1 report: why cardiovascular GO?
Proteomics. 2008 ; 8(10):1950-3. (PubMed abstract [external website])

The following article provides an overview of GO, how to use GO and some of the tools available for the analysis of high-throughput data:

Dimmer EC, Huntley RP, Barrell DG, Binns D, Draghici S, Camon EB, Hubank M, Talmud PJ, Apweiler R, Lovering RC.
The Gene Ontology - Providing a Functional Role in Proteomic Studies.
Proteomics. 2008. (PubMed abstract [external website])

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