Abstract
Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species.We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases.This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.
Highlights
Research on model organisms is crucial for discovering the function of genes and DNA elements and for understanding the phenotypic effects of mutations on these genes, which is leading to a better understanding of the pathobiology of human disease[1,2]
We have previously demonstrated the power of this approach in determining likely pathogenicity of genes within the intervals of recurrent copy number variation (CNV) diseases[6] and it can be applied much more widely in, for example, prioritizing candidate genes identified through human genome wide association studies (GWAS)[7,8]
The generated build artifacts are available at http://purl.obolibrary.org/obo/hp/uberpheno/, whereas the file crossSpeciesPheno.obo contains the cross-species phenotype ontology in OBOformat
Summary
Research on model organisms is crucial for discovering the function of genes and DNA elements and for understanding the phenotypic effects of mutations on these genes, which is leading to a better understanding of the pathobiology of human disease[1,2]. As the ability of investigators to mobilise this growing collection of model organism data has become more important, it is crucial to develop appropriate ontologies and computational strategies to describe phenotypes such that phenotype descriptions can be objectively related to each other, both within and between species. This becomes even more important as the divergence between the number of human genes with phenotype information and the amount of systematically phenotyped model organism genes is expected to increase in the near future due to high throughput-screens[1]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
