Augmenting the disease ontology improves and unifies disease annotations across species

Abstract

Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making larger scale comparisons and inferences challenging at best. A single disease ontology that connects data annotated using diverse disease terminologies, and in which the terminology relationships applicable to human and animal models are continuously maintained, is needed. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment the DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD's OMIM and RGD's RDO disease term annotations identified new terms that when added to DO enhance DO's representation of human diseases for which model organism data exist. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO's disease domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms for users and facilitates application of the DO for computational research. A coherent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO for disease annotation by MGD and RGD demonstrates DO's potential use across organisms and increases interoperability between MGD, RGD and the wider model organism database (MOD) community at the disease annotation level. Further, the human genetics/genomics community will benefit from a consistent way to interrogate model organism disease associations.