Phenotype ontologies and cross-species analysis for translational research.
The use of model organisms as tools for the investigation of human genetic variation has significantly and rapidly advanced our understanding of the aetiologies underlying hereditary traits. However, while equivalences in the DNA sequence of two species may be readily inferred through evolutionary models, the identification of equivalence in the phenotypic consequences resulting from comparable genetic variation is far from straightforward, limiting the value of the modelling paradigm. In this review, we provide an overview of the emerging statistical and computational approaches to objectively identify phenotypic equivalence between human and model organisms with examples from the vertebrate models, mouse and zebrafish. Firstly, we discuss enrichment approaches, which deem the most frequent phenotype among the orthologues of a set of genes associated with a common human phenotype as the orthologous phenotype, or phenolog, in the model species. Secondly, we introduce and discuss computational reasoning approaches to identify phenotypic equivalences made possible through the development of intra- and interspecies ontologies. Finally, we consider the particular challenges involved in modelling neuropsychiatric disorders, which illustrate many of the remaining difficulties in developing comprehensive and unequivocal interspecies phenotype mappings.
Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany; Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany; Max Planck Institute for Molecular Genetics, Berlin, Germany; Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
Peter N
PN
Robinson
MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.
Caleb
C
Webber
D000818:Animals; D005075:Biological Evolution; D064229:Biological Ontologies; D019295:Computational Biology / Q000379:methods*; D014644:Genetic Variation / Q000235:genetics; D006801:Humans; D010641:Phenotype; D057170:Translational Research, Biomedical / Q000379:methods*