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  4. Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system

Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system

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Author(s)
Wang, Haoyi
•
Yang, Hui
•
Shi, Linyu
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Katz, Yarden
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Theunissen, Thorold W
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Rangarajan, Sudharshan
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Jaenisch, Rudolf
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Shivalila, Chikdu Shakti
•
Dadon, Daniel Benjamin
•
Cheng, Albert Wu
Date Issued
August 2013
Journal
Cell Research
Publisher
Nature Publishing Group
Citation
Cheng, Albert W, Haoyi Wang, Hui Yang, Linyu Shi, Yarden Katz, Thorold W Theunissen, Sudharshan Rangarajan, Chikdu S Shivalila, Daniel B Dadon, and Rudolf Jaenisch. “Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system.” Cell Research 23, no. 10 (August 27, 2013): 1163-1171. © 2013 IBCB, SIBS, CAS
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Final published version
Abstract
Technologies allowing for specific regulation of endogenous genes are valuable for the study of gene functions and have great potential in therapeutics. We created the CRISPR-on system, a two-component transcriptional activator consisting of a nuclease-dead Cas9 (dCas9) protein fused with a transcriptional activation domain and single guide RNAs (sgRNAs) with complementary sequence to gene promoters. We demonstrate that CRISPR-on can efficiently activate exogenous reporter genes in both human and mouse cells in a tunable manner. In addition, we show that robust reporter gene activation in vivo can be achieved by injecting the system components into mouse zygotes. Furthermore, we show that CRISPR-on can activate the endogenous IL1RN, SOX2, and OCT4 genes. The most efficient gene activation was achieved by clusters of 3-4 sgRNAs binding to the proximal promoters, suggesting their synergistic action in gene induction. Significantly, when sgRNAs targeting multiple genes were simultaneously introduced into cells, robust multiplexed endogenous gene activation was achieved. Genome-wide expression profiling demonstrated high specificity of the system.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Whitehead Institute for Biomedical Research
Terms of Use
Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 Unported License
http://creativecommons.org/licenses/by-nc-nd/3.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/84630
DOI of Published Version
https://doi.org/10.1038/cr.2013.122
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