Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Oct 18;4(1):30.
doi: 10.1186/2041-1480-4-30.

The Drosophila phenotype ontology

David Osumi-Sutherland  1 , Steven J Marygold, Gillian H Millburn, Peter A McQuilton, Laura Ponting, Raymund Stefancsik, Kathleen Falls, Nicholas H Brown, Georgios V Gkoutos
Affiliations

The Drosophila phenotype ontology

David Osumi-Sutherland et al. J Biomed Semantics. .

Abstract

Background: Phenotype ontologies are queryable classifications of phenotypes. They provide a widely-used means for annotating phenotypes in a form that is human-readable, programatically accessible and that can be used to group annotations in biologically meaningful ways. Accurate manual annotation requires clear textual definitions for terms. Accurate grouping and fruitful programatic usage require high-quality formal definitions that can be used to automate classification. The Drosophila phenotype ontology (DPO) has been used to annotate over 159,000 phenotypes in FlyBase to date, but until recently lacked textual or formal definitions.

Results: We have composed textual definitions for all DPO terms and formal definitions for 77% of them. Formal definitions reference terms from a range of widely-used ontologies including the Phenotype and Trait Ontology (PATO), the Gene Ontology (GO) and the Cell Ontology (CL). We also describe a generally applicable system, devised for the DPO, for recording and reasoning about the timing of death in populations. As a result of the new formalisations, 85% of classifications in the DPO are now inferred rather than asserted, with much of this classification leveraging the structure of the GO. This work has significantly improved the accuracy and completeness of classification and made further development of the DPO more sustainable.

Conclusions: The DPO provides a set of well-defined terms for annotating Drosophila phenotypes and for grouping and querying the resulting annotation sets in biologically meaningful ways. Such queries have already resulted in successful function predictions from phenotype annotation. Moreover, such formalisations make extended queries possible, including cross-species queries via the external ontologies used in formal definitions. The DPO is openly available under an open source license in both OBO and OWL formats. There is good potential for it to be used more broadly by the Drosophila community, which may ultimately result in its extension to cover a broader range of phenotypes.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Autoclassification of processual phenotypes. Auto-classification of processual phenotypes, leveraging the GO. Terms in bold have equivalent class definitions. Panel A shows classification of stress response phenotypes. Panel B shows a portion of the behavioral phenotype classification.
Figure 2
Figure 2
Lethal phase phenotypes. When do they die? - classes for recording and reasoning about the timing of death in lethal phenotypes. - Panel A shows the temporal relationships between Drosophila life stages from the Drosophila stage ontology. The P icon stands for immediately_preceded_by, which corresponds to the Allen relation 'meets’. Panel B shows a set of lethal phenotype terms prior to auto-classification. Panel C shows the same set of classes after auto-classification using the HermiT reasoner.
See this image and copyright information in PMC

References

    1. Costa M, Reeve S, Grumbling G, Osumi-Sutherland D. The Drosophila anatomy ontology. J Biomed Sem. 2013. in press. - PMC - PubMed
    1. Sprague J, Bayraktaroglu L, Bradford Y, Conlin T, Dunn N, Fashena D, Frazer K, Haendel M, Howe DG, Knight J, Mani P, Moxon SA, Pich C, Ramachandran S, Schaper K, Segerdell E, Shao X, Singer A, Song P, Sprunger B, Van Slyke CE, Westerfield M. The zebrafish information network: the zebrafish model organism database provides expanded support for genotypes and phenotypes. Nucleic Acids Res. 2008;36(Database issue):D768–D772. - PMC - PubMed
    1. Bult CJ, Eppig JT, Blake JA, Kadin JA, Richardson JE, Airey MT, Anagnostopoulos A, Babiuk R, Baldarelli RM, Beal JS, Bello SM, Butler NE, Campbell J, Corbani LE, Dene H, Drabkin HR, Forthofer KL, Giannatto SL, Knowlton M, Lewis JR, McAndrews M, McClatchy S, Miers DS, Ni L, Onda H, Ormsby JE, Recla JM, Reed DJ, Richards-Smith B, Shaw DR, Sitnikov D, Smith CL, Tomczuk M, Washburn LL, Zhu Y. The mouse genome database: genotypes, phenotypes, and models of human disease. Nucleic Acids Res. 2013;41(Database issue):D885–D891. - PMC - PubMed
    1. Grumbling G, Strelets V. FlyBase: anatomical data, images and queries. Nucleic Acids Res. 2006;34(Database issue):D484–D488. - PMC - PubMed
    1. Engel SR, Balakrishnan R, Binkley G, Christie KR, Costanzo MC, Dwight SS, Fisk DG, Hirschman JE, Hitz BC, Hong EL, Krieger CJ, Livstone MS, Miyasato SR, Nash R, Oughtred R, Park J, Skrzypek MS, Weng S, Wong ED, Dolinski K, Botstein D, Cherry JM. Saccharomyces genome database provides mutant phenotype data. Nucleic Acids Res. 2010;38(Database issue):D433–D436. - PMC - PubMed

LinkOut - more resources