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Inducible Control of Subcellular RNA Localization Using a Synthetic Protein-RNA Aptamer Interaction

Overview of attention for article published in PLOS ONE, October 2012
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Title
Inducible Control of Subcellular RNA Localization Using a Synthetic Protein-RNA Aptamer Interaction
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0046868
Pubmed ID
Authors

Brian J. Belmont, Jacquin C. Niles

Abstract

Evidence is accumulating in support of the functional importance of subcellular RNA localization in diverse biological contexts. In different cell types, distinct RNA localization patterns are frequently observed, and the available data indicate that this is achieved through a series of highly coordinated events. Classically, cis-elements within the RNA to be localized are recognized by RNA-binding proteins (RBPs), which then direct specific localization of a target RNA. Until now, the precise control of the spatiotemporal parameters inherent to regulating RNA localization has not been experimentally possible. Here, we demonstrate the development and use of a chemically-inducible RNA-protein interaction to regulate subcellular RNA localization. Our system is composed primarily of two parts: (i) the Tet Repressor protein (TetR) genetically fused to proteins natively involved in localizing endogenous transcripts; and (ii) a target transcript containing genetically encoded TetR-binding RNA aptamers. TetR-fusion protein binding to the target RNA and subsequent localization of the latter are directly regulated by doxycycline. Using this platform, we demonstrate that enhanced and controlled subcellular localization of engineered transcripts are achievable. We also analyze rules for forward engineering this RNA localization system in an effort to facilitate its straightforward application to studying RNA localization more generally.

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Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 2%
China 1 2%
Unknown 52 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 26%
Student > Ph. D. Student 11 20%
Student > Master 9 17%
Student > Bachelor 7 13%
Student > Doctoral Student 3 6%
Other 6 11%
Unknown 4 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 37%
Biochemistry, Genetics and Molecular Biology 18 33%
Medicine and Dentistry 3 6%
Chemical Engineering 2 4%
Chemistry 2 4%
Other 5 9%
Unknown 4 7%