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Nucleic Acids Research
Article . 2020 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Nucleic Acids Research
Article
License: CC BY
Data sources: UnpayWall
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PubMed Central
Article . 2020
License: CC BY
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Capturing RNA–protein interaction via CRUIS

Authors: Ji-Long Liu; Min Zhuang; Pengfei Lu; Tiezhu Shi; Weiping Sun; Ziheng Zhang;

Capturing RNA–protein interaction via CRUIS

Abstract

Abstract No RNA is completely naked from birth to death. RNAs function with and are regulated by a range of proteins that bind to them. Therefore, the development of innovative methods for studying RNA–protein interactions is very important. Here, we developed a new tool, the CRISPR-based RNA-United Interacting System (CRUIS), which captures RNA–protein interactions in living cells by combining the power of CRISPR and PUP-IT, a novel proximity targeting system. In CRUIS, dCas13a is used as a tracker to target specific RNAs, while proximity enzyme PafA is fused to dCas13a to label the surrounding RNA-binding proteins, which are then identified by mass spectrometry. To identify the efficiency of CRUIS, we employed NORAD (Noncoding RNA activated by DNA damage) as a target, and the results show that a similar interactome profile of NORAD can be obtained as by using CLIP (crosslinking and immunoprecipitation)-based methods. Importantly, several novel NORAD RNA-binding proteins were also identified by CRUIS. The use of CRUIS facilitates the study of RNA–protein interactions in their natural environment, and provides new insights into RNA biology.

Related Organizations
Keywords

HEK293 Cells, Ribonucleases, CRISPR-Associated Proteins, Methods Online, Humans, Immunoprecipitation, RNA, RNA-Binding Proteins, CRISPR-Cas Systems, Mass Spectrometry

  • BIP!
    Impact byBIP!
    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).
    71
    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.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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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!
71
Top 1%
Top 10%
Top 1%
Green
gold