Our proposal is to develop an ontology of qualities (i.e. distinguishing characteristics such as: long, short, increased, decreased, red, blue, and so on) and use it, in conjunction with ontologies of particular anatomies and biological processes, to describe phenotypic data from zebrafish, fruit fly, mouse, and human rigorously. This work will provide one of the integral components necessary for integrating phenotypic descriptions semantically with other aspects of biomedical knowledge. Currently these descriptions are recorded either as free text or using a terminology that is idiosyncratic to a single organism or research project. We have chosen these particular data sets because of the preliminary work that has already been carried out on these data, because they provide a wide spectrum of descriptive situations that will fully exercise the ontology, and particularly because, with the human data, we will be able to explore how unifying these data sets can enable translational research. We will also work with other database resources, such as BIRN [BIRN], WormBase [WormBase], dictyBase [dictyBase], and PhenoScape [PhenoScape], who are also adopting the approach we advocate (see letters of support). We will contribute PATO and the other ontologies that we develop to the OBO Foundry [OBO], and we will deposit our phenotypic annotations into the OBD [OBD] database of the National Center for Biomedical Ontology [NCBO] to facilitate comparisons between these and other data. The Quality Ontology [PATO] will provide one essential part of the unifying framework needed to surmount the difficult problem of integrating phenotypic data sets.

Public Health Relevance

The underlying principle of this proposal is that the comparative approach can be used to further our understanding of the genetic and molecular bases of human diseases. Experiments that study the phenotypic consequences of mutations in non-human organisms are justified by the fact that they provide valuable models for a better understanding of human diseases.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG004838-03
Application #
8127993
Study Section
Special Emphasis Panel (ZRG1-BST-G (50))
Program Officer
Bonazzi, Vivien
Project Start
2009-09-30
Project End
2013-06-30
Budget Start
2011-07-01
Budget End
2013-06-30
Support Year
3
Fiscal Year
2011
Total Cost
$524,903
Indirect Cost
Name
Lawrence Berkeley National Laboratory
Department
Genetics
Type
Organized Research Units
DUNS #
078576738
City
Berkeley
State
CA
Country
United States
Zip Code
94720
Fisher, Hannah M; Hoehndorf, Robert; Bazelato, Bruno S et al. (2016) DermO; an ontology for the description of dermatologic disease. J Biomed Semantics 7:38
Desvignes, T; Batzel, P; Berezikov, E et al. (2015) miRNA Nomenclature: A View Incorporating Genetic Origins, Biosynthetic Pathways, and Sequence Variants. Trends Genet 31:613-26
Köhler, Sebastian; Doelken, Sandra C; Mungall, Christopher J et al. (2014) The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res 42:D966-74
Hoehndorf, Robert; Hancock, John M; Hardy, Nigel W et al. (2014) Analyzing gene expression data in mice with the Neuro Behavior Ontology. Mamm Genome 25:32-40
Köhler, Sebastian; Doelken, Sandra C; Ruef, Barbara J et al. (2013) Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research. F1000Res 2:30
Hoehndorf, Robert; Hardy, Nigel W; Osumi-Sutherland, David et al. (2013) Systematic analysis of experimental phenotype data reveals gene functions. PLoS One 8:e60847
Smedley, Damian; Oellrich, Anika; Köhler, Sebastian et al. (2013) PhenoDigm: analyzing curated annotations to associate animal models with human diseases. Database (Oxford) 2013:bat025
Howe, Douglas G; Bradford, Yvonne M; Conlin, Tom et al. (2013) ZFIN, the Zebrafish Model Organism Database: increased support for mutants and transgenics. Nucleic Acids Res 41:D854-60
Doelken, Sandra C; Köhler, Sebastian; Mungall, Christopher J et al. (2013) Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish. Dis Model Mech 6:358-72
Hoehndorf, Robert; Dumontier, Michel; Gkoutos, Georgios V (2013) Evaluation of research in biomedical ontologies. Brief Bioinform 14:696-712

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