ayout 1 - EMBL Grenoble

EMBL-EBI
The GO Editorial Office
Previous and current research
The Gene Ontology (GO) project (www.geneontology.org) is a collaborative effort to construct and
use ontologies to facilitate the biologically meaningful annotation of genes and their products in
a wide variety of organisms. At the EBI, the GO Editorial Office plays a key role in managing the
distributed task of developing and maintaining the GO vocabularies, and contributes to a number
of other GO project efforts, including documentation, web presence, software testing and user
support.
The Gene Ontology Consortium (GOC) provides the scientific community with a consistent and
robust infrastructure, in the form of biological ontologies, for describing, integrating, and comparing
the structures of genetic elements and the functional roles of gene products within and between
organisms. The GO ontologies cover three key biological domains that are shared by all
organisms:
• molecular function defines the tasks performed by individual gene products; examples
include aminoacyl-tRNA ligase activity and translation elongation factor activity;
Midori Harris
PhD 1997, Cornell University,
Ithaca, NY.
Scientific Curator,
Saccharomyces Genome
Database, Stanford
University, Stanford, CA.
GO Editor at EMBL-EBI since
2001.
• biological process defines broad biological goals, such as signal transduction or ribosome
assembly, that are accomplished by ordered assemblies of molecular functions;
• cellular component describes subcellular structures, locations and macromolecular complexes; examples include cytoplasm, ribosome
and translation release factor complex.
In addition, sequence features are covered by the Sequence Ontology, which is maintained separately from the three GO ontologies (Eilbeck
et al., 2005).
The ontologies in GO are structured as directed acyclic graphs
(DAGs), wherein any term may have one or more parents and
zero, one, or more children. Within each vocabulary, terms are
defined and parent–child relationships between terms are specified.
A child term is a subset of its parent(s). The GO vocabularies
have long defined two semantic relationships between
parent and child terms: is_a and part_of. The is_a relationship
means that a term is a subclass of its parent; part of may mean
‘physically part of ’ (as in the cellular component ontology) or
‘subprocess of ’ (as in the biological process ontology). New relationships
representing biological regulation have recently
been added, as described below. The figure shows a portion of
the GO cellular component DAG.
Future projects and goals
The GO Editorial Office will continue to work closely with the
rest of the GO Consortium and with biological experts to ensure
that the ontologies are comprehensive, logically rigorous
and biologically accurate. Improvements begun in 2008 on signal
transduction, transcription, and other topics will therefore
continue in 2009. The new regulates relationships will be used to
create the first links between the biological process and molecular
function ontologies, with additional types of links to follow.
Work on recasting many complex process terms as explicit crossproducts
with orthogonal ontologies such as the ChEBI ontology
and the cell ontology will also continue.
GO terms are organised in directed acyclic graphs (DAGs) – hierarchical
structures in which any ‘child’ (more specialised term) can have many
‘parents’ (less specialised terms). For example, the cellular component term
chloroplast envelope has two parents, reflecting the fact that it is a part of
the chloroplast and a type of envelope. Any gene that is annotated to this
term is automatically annotated to both chloroplast and envelope. Some
terms and relationships have been omitted for clarity.
Selected references
The Gene Ontology Consortium (2008). The Gene Ontology (GO)
Project in 2008. Nucleic Acids Res., 36, D0-D
Eilbeck, K. et al. (2005). The Sequence Ontology: a tool for the
unification of genome annotations. Genome Biol., 6, R
The Gene Ontology Consortium (2001). Creating the Gene Ontology
resource: design and implementation. Genome Res., 11, 125-133
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