Dr. Melissa Haendel, OHSU Library eagle-I team, has just published an article in the Public Library of Science Biology: Linking Human Diseases to Animal Models Using Ontology-Based Phenotype Annotation.
This paper describes methods of recording human and model organism phenotypes using ontologies that can be used for computational comparison. This allows computational comparison and identification of animal models that are similar to human diseases, and vice versa, even when the genetic basis is unknown.
This identification of animal models similar to human diseases helps in more quickly identifying genetic issues in disease research. Dr. Haendel is lead on the eagle-I team which helps bring this kind of information together.
Model organisms such as fruit flies, mice, and zebrafish are useful for investigating gene function because they are easy to grow, dissect, and genetically manipulate in the laboratory. By examining mutations in these organisms, one can identify candidate genes that cause disease in humans, and develop models to better understand human disease and gene function. A fundamental roadblock for analysis is, however, the lack of a computational method for describing and comparing phenotypes when the genetic basis is unknown.
We describe here a novel method using ontologies to record and quantify the similarity between phenotypes. We tested our method by using the annotated mutant phenotype of one member of the hedgehog signaling pathway in zebrafish to identify other pathway members with similar recorded phenotypes.
We also compare human disease phenotypes to those produced by mutation in model organisms, and show that orthologous and biologically relevant genes can be identified by this method. Since the genetic basis of human disease is often unknown, this method provides a means to identify candidate genes, pathway members, and disease models based on computationally identifying similar phenotypes within and across species.