Abstract
Despite considerable progress in understanding the molecular origins of hereditary human diseases, the molecular basis of several thousand genetic diseases still remains unknown. High-throughput phenotype studies are underway to systematically assess the phenotype outcome of targeted mutations in model organisms. Thus, comparing the similarity between experimentally identified phenotypes and the phenotypes associated with human diseases can be used to suggest causal genes underlying a disease. In this manuscript, we present a method for disease gene prioritization based on comparing phenotypes of mouse models with those of human diseases. For this purpose, either human disease phenotypes are “translated” into a mouse-based representation (using the Mammalian Phenotype Ontology), or mouse phenotypes are “translated” into a human-based representation (using the Human Phenotype Ontology). We apply a measure of semantic similarity and rank experimentally identified phenotypes in mice with respect to their phenotypic similarity to human diseases. Our method is evaluated on manually curated and experimentally verified gene–disease associations for human and for mouse. We evaluate our approach using a Receiver Operating Characteristic (ROC) analysis and obtain an area under the ROC curve of up to . Furthermore, we are able to confirm previous results that the Vax1 gene is involved in Septo-Optic Dysplasia and suggest Gdf6 and Marcks as further potential candidates. Our method significantly outperforms previous phenotype-based approaches of prioritizing gene–disease associations. To enable the adaption of our method to the analysis of other phenotype data, our software and prioritization results are freely available under a BSD licence at http://code.google.com/p/phenomeblast/wiki/CAMP. Furthermore, our method has been integrated in PhenomeNET and the results can be explored using the PhenomeBrowser at http://phenomebrowser.net.
Highlights
With the advent of whole-genome sequencing, researchers have focused on understanding the underlying molecular causes of hereditary human diseases to enable and improve their treatment
We utilized the three different mapping approaches between Human Phenotype Ontology (HPO) and MP to ‘‘translate’’ human disease phenotypes into an MP-based representation, and compared their semantic similarity with mouse phenotypes based on MP
We assume that mouse models with a phenotype that is similar to a disease phenotype may be a model of that disease [13,14,21]
Summary
With the advent of whole-genome sequencing, researchers have focused on understanding the underlying molecular causes of hereditary human diseases to enable and improve their treatment. One important tool to understand human hereditary diseases are animal models. Animal models of a human disease do provide insights into the pathogenesis of the disease and enable the evaluation of therapeutic strategies. Over the past few years, large-scale mutagenesis projects have been proposed to systematically identify the phenotypes of organisms resulting from targeted modifications to the organisms’ genetic markup. Large-scale mutagenesis experiments provide a thorough examination of species’ phenomes and with that constitute the tantalizing possibility for revealing valuable information about the molecular mechanisms underlying human disease [1]. Phenotype studies in mice have been demonstrated to provide insights into human disease mechanisms [2,3]
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