Use of zebrafish models to investigate rare human disease

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Abstract

Rare diseases are collectively common and often extremely debilitating. Following the emergence of next-generation sequencing (NGS) technologies, the variants underpinning rare genetic disorders are being unearthed at an accelerating rate. However, many rare conditions lack effective treatments due to their poorly understood pathophysiology. There is therefore a growing demand for the development of novel experimental models of rare genetic diseases, so that potentially causative variants can be validated, pathogenic mechanisms can be investigated and therapeutic targets can be identified. Animal models of rare diseases need to be genetically and physiologically similar to humans, and well-suited to large-scale experimental manipulation, considering the vast number of novel variants that are being identified through NGS. The zebrafish has emerged as a popular model system for investigating these variants, combining conserved vertebrate characteristics with a capacity for large-scale phenotypic and therapeutic screening. In this review, we aim to highlight the unique advantages of the zebrafish over other in vivo model systems for the large-scale study of rare genetic variants. We will also consider the generation of zebrafish disease models from a practical standpoint, by discussing how genome editing technologies, particularly the recently developed clustered regularly interspaced repeat (CRISPR)/CRISPR-associated protein 9 system, can be used to model rare pathogenic variants in zebrafish. Finally, we will review examples in the literature where zebrafish models have played a pivotal role in confirming variant causality and revealing the underlying mechanisms of rare diseases, often with wider implications for our understanding of human biology.

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Adamson, K. I., Sheridan, E., & Grierson, A. J. (2018). Use of zebrafish models to investigate rare human disease. Journal of Medical Genetics, 55(10), 641–654. https://doi.org/10.1136/jmedgenet-2018-105358

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