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Decoding G0 somatic mutants through deep phenotyping and mosaic pattern analysis in the zebrafish skeleton

Claire J. Watson, Adrian T. Monstad-Rios, Rehaan M. Bhimani, Charlotte Gistelinck, Andy Willaert, Paul Coucke, Yi-Hsiang Hsu, Ronald Y. Kwon
doi: https://doi.org/10.1101/466185
Claire J. Watson
1Department of Orthopaedics and Sports Medicine, University of Washington, Seattle, Washington, USA
2Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington, USA
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  • For correspondence: cwalk1@uw.edu
Adrian T. Monstad-Rios
1Department of Orthopaedics and Sports Medicine, University of Washington, Seattle, Washington, USA
2Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington, USA
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Rehaan M. Bhimani
1Department of Orthopaedics and Sports Medicine, University of Washington, Seattle, Washington, USA
2Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington, USA
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Charlotte Gistelinck
1Department of Orthopaedics and Sports Medicine, University of Washington, Seattle, Washington, USA
4Center for Medical Genetics Ghent, Ghent University, Ghent, Belgium
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Andy Willaert
4Center for Medical Genetics Ghent, Ghent University, Ghent, Belgium
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Paul Coucke
4Center for Medical Genetics Ghent, Ghent University, Ghent, Belgium
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Yi-Hsiang Hsu
5Hebrew SeniorLife Institute for Aging Research, Boston, Massachusetts, USA
6Harvard Medical School, Boston, Massachusetts, USA
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Ronald Y. Kwon
1Department of Orthopaedics and Sports Medicine, University of Washington, Seattle, Washington, USA
2Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington, USA
3Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
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ABSTRACT

Genetic mosaicism manifests as spatially variable phenotypes, whose detection and interpretation remains challenging. This study identifies biological factors influencing spatial phenotypic patterns in the skeletons of somatic mutant zebrafish, and tests methods for their analysis using deep phenotyping. We explore characteristics of loss-of-function clusters in the skeleton of CRISPR-edited G0 ("crispant") zebrafish, and identify a distinctive size distribution shown to arise from clonal fragmentation and merger events. Using microCT-based phenomics, we describe diverse phenotypic manifestations in somatic mutants for genes implicated in monogenic (plod2 and bmp1a) and polygenic (wnt16) bone diseases, each showing convergence with germline mutant phenomes. Finally, we describe statistical frameworks for phenomic analysis which confers heightened sensitivity in discriminating somatic mutant populations, and quantifies spatial phenotypic variation. Our studies provide strategies for decoding spatially variable phenotypes which, paired with CRISPR-based screens, can identify genes contributing to skeletal disease.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 02, 2019.
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Decoding G0 somatic mutants through deep phenotyping and mosaic pattern analysis in the zebrafish skeleton
Claire J. Watson, Adrian T. Monstad-Rios, Rehaan M. Bhimani, Charlotte Gistelinck, Andy Willaert, Paul Coucke, Yi-Hsiang Hsu, Ronald Y. Kwon
bioRxiv 466185; doi: https://doi.org/10.1101/466185
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Decoding G0 somatic mutants through deep phenotyping and mosaic pattern analysis in the zebrafish skeleton
Claire J. Watson, Adrian T. Monstad-Rios, Rehaan M. Bhimani, Charlotte Gistelinck, Andy Willaert, Paul Coucke, Yi-Hsiang Hsu, Ronald Y. Kwon
bioRxiv 466185; doi: https://doi.org/10.1101/466185

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