title: Interpreting human genetic variation with in vivo zebrafish assays.
abstract: Rapid advances and cost erosion in exome and genome analysis of patients with both rare and common genetic disorders have accelerated gene discovery and illuminated fundamental biological mechanisms. The thrill of discovery has been accompanied, however, with the sobering appreciation that human genomes are burdened with a large number of rare and ultra rare variants, thereby posing a significant challenge in dissecting both the effect of such alleles on protein function and also the biological relevance of these events to patient pathology. In an effort to develop model systems that are able to generate surrogates of human pathologies, a powerful suite of tools have been developed in zebrafish, taking advantage of the relatively small (compared to invertebrate models) evolutionary distance of that genome to humans, the orthology of several organs and signaling processes, and the suitability of this organism for medium and high throughput phenotypic screening. Here we will review the use of this model organism in dissecting human genetic disorders; we will highlight how diverse strategies have informed disease causality and genetic architecture; and we will discuss relative strengths and limitations of these approaches in the context of medical genome sequencing. This article is part of a Special Issue entitled: From Genome to Function.
authors.affiliation: Center for Human Disease Modeling, Duke University Medical Center, Durham, NC 27710, USA. Electronic address: erica.davis@duke.edu.
authors.forename: Erica E
authors.initials: EE
authors.lastname: Davis
authors.affiliation: Center for Human Disease Modeling, Duke University Medical Center, Durham, NC 27710, USA.
authors.forename: Stephan
authors.initials: S
authors.lastname: Frangakis
authors.affiliation: Center for Human Disease Modeling, Duke University Medical Center, Durham, NC 27710, USA. Electronic address: katsanis@cellbio.duke.edu.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Katsanis
keywords: Allele pathogenicity; Disease modeling; Genomics