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Modular, programmable RNA sensing using ADAR editing in living cells

An Author Correction to this article was published on 23 November 2022

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With the increasing availability of single-cell transcriptomes, RNA signatures offer a promising basis for targeting living cells. Molecular RNA sensors would enable the study of and therapeutic interventions for specific cell types/states in diverse contexts, particularly in human patients and non-model organisms. Here we describe a modular, programmable system for live RNA sensing using adenosine deaminases acting on RNA (RADAR). We validate, and then expand, our basic design, characterize its performance, and analyze its compatibility with human and mouse transcriptomes. We identify strategies to boost output levels and improve the dynamic range. Additionally, we show that RADAR enables compact AND logic. In addition to responding to transcript levels, RADAR can distinguish disease-relevant sequence alterations of transcript identities, such as point mutations and fusions. Finally, we demonstrate that RADAR is a self-contained system with the potential to function in diverse organisms.

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Fig. 1: Characterizing RADAR.
Fig. 2: Expanding and enhancing RADAR.
Fig. 3: Unique features and potential applications of RADAR.

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Data availability

Plasmids and plasmid maps have been deposited to Addgene. Next-generation sequencing data have been submitted to the Sequencing Read Archive under BioProject accession PRJNA874842. Raw flow cytometry data is available upon request from the corresponding author.

Code availability

Code for designing sensors and the bioinformatics analysis of mouse and human transcriptomes are available at

Change history


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This work was funded by the National Institutes of Health (4R00EB027723-02; to X.J.G.), Seed Grant from Brain Research Foundation (to X.J.G.), NARSAD Young Investigator Grant from the Brain and Behavior Research Foundation (to X.J.G.), Longevity Impetus Grant (to X.J.G.), Stanford Bio-X Interdisciplinary Graduate Fellowship (to K.E.K.), Fulbright Foundation (to N.K.), National Science Foundation GRFP (to N.S.K.), Stanford ChEM-H CBI training program (to N.S.K.), EDGE Doctoral Fellowship Program (to N.S.K.). N.K. is an Awardee of the Weizmann Institute of Science—Israel National Postdoctoral Award Program for Advancing Women in Science. We thank the Gao lab members for their feedback. We thank L. Luo and Y. Wu for gifts of Cre-related plasmids, J.B. Li and S. Hu for ADAR plasmids and the ADAR1 knockout cell line and advice. We thank C. Liou for technical advice on qPCR and Q. Li for technical advice on NGS.

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Authors and Affiliations



K.E.K., N.K., N.S.K., and X.J.G. designed the study. K.E.K., N.K., N.S.K., and C.C.C. performed and analyzed most of the experiments, with support from D.L.W., W.B.C., and E.S.S. for the plant experiments. K.E.K. performed bioinformatic analysis. K.E.K. and X.J.G. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Xiaojing J. Gao.

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Competing interests

K.E.K., N.K., N.S.K, and X.J.G are co-inventors on a provisional patent filing related to RADAR sensors. All other authors declare no competing interests.

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Nature Biotechnology thanks Tzu-Chieh Tang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Note 1 and Supplementary Figs. 1–3.

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Supplementary Tables 1–3.

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Kaseniit, K.E., Katz, N., Kolber, N.S. et al. Modular, programmable RNA sensing using ADAR editing in living cells. Nat Biotechnol 41, 482–487 (2023).

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