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Biochemical Society Transactions
Article . 2023 . Peer-reviewed
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Engineering CRISPR guide RNAs for programmable RNA sensors

Authors: Yang Liu; Wei Liu; Baojun Wang;

Engineering CRISPR guide RNAs for programmable RNA sensors

Abstract

As the most valuable feature of the CRISPR system, the programmability based on Watson–Crick base pairing has been widely exploited in engineering RNA sensors. The base pairing in these systems offers a connection between the RNA of interest and the CRISPR effector, providing a highly specific mechanism for RNA detection both in vivo and in vitro. In the last decade, despite the many successful RNA sensing approaches developed during the era of CRISPR explosion, a deeper understanding of the characteristics of CRISPR systems and the continuous expansion of the CRISPR family members indicates that the CRISPR-based RNA sensor remains a promising area from which a variety of new functions and applications can be engineered. Here, we present a systematic overview of the various strategies of engineering CRISPR gRNA for programmable RNA detection with an aim to clarify the role of gRNA's programmability among the present limitations and future development of CRISPR-enabled RNA sensors.

Related Organizations
Keywords

RNA sensor, programmability, CRISPR, gRNA, RNA, CRISPR-Cas Systems, RNA, Guide, CRISPR-Cas Systems, Review Articles, Base Pairing

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
hybrid