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  5. Fast and efficient generation of knock-in human organoids using homology-independent CRISPR/Cas9 precision genome editing

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Preprint
en
2020

Fast and efficient generation of knock-in human organoids using homology-independent CRISPR/Cas9 precision genome editing

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0 Files

en
2020
DOI: 10.1101/2020.01.15.907766

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Hans Clevers
Hans Clevers

Utrecht University

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Benedetta Artegiani
Delilah Hendriks
Joep Beumer
+7 more

Abstract

Abstract CRISPR/Cas9 technology has revolutionized genome editing and is applicable to the organoid field. However, precise integration of exogenous DNA sequences in human organoids awaits robust knock-in approaches. Here, we describe CRISPR /Cas9-mediated H omology-independent O rganoid T ransgenesis (CRISPR-HOT), which allows efficient generation of knock-in human organoids representing different tissues. CRISPR-HOT avoids extensive cloning and outperforms homology directed repair (HDR) in achieving precise integration of exogenous DNA sequences at desired loci, without the necessity to inactivate TP53 in untransformed cells, previously used to increase HDR-mediated knock-in. CRISPR-HOT was employed to fluorescently tag and visualize subcellular structural molecules and to generate reporter lines for rare intestinal cell types. A double reporter labelling the mitotic spindle by tagged tubulin and the cell membrane by tagged E-cadherin uncovered modes of human hepatocyte division. Combining tubulin tagging with TP53 knock-out revealed TP53 involvement in controlling hepatocyte ploidy and mitotic spindle fidelity. CRISPR-HOT simplifies genome editing in human organoids.

How to cite this publication

Benedetta Artegiani, Delilah Hendriks, Joep Beumer, Rutger N.U. Kok, Xuan Zheng, Indi P. Joore, Susana M. Chuva de Sousa Lopes, Jeroen S. van Zon, Sander J. Tans, Hans Clevers (2020). Fast and efficient generation of knock-in human organoids using homology-independent CRISPR/Cas9 precision genome editing. , DOI: https://doi.org/10.1101/2020.01.15.907766.

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Publication Details

Type

Preprint

Year

2020

Authors

10

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1101/2020.01.15.907766

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