Unknown

Dataset Information

0

Programmable RNA-Guided RNA Effector Proteins Built from Human Parts.


ABSTRACT: Epitranscriptomic regulation controls information flow through the central dogma and provides unique opportunities for manipulating cells at the RNA level. However, both fundamental studies and potential translational applications are impeded by a lack of methods to target specific RNAs with effector proteins. Here, we present CRISPR-Cas-inspired RNA targeting system (CIRTS), a protein engineering strategy for constructing programmable RNA control elements. We show that CIRTS is a simple and generalizable approach to deliver a range of effector proteins, including nucleases, degradation machinery, translational activators, and base editors to target transcripts. We further demonstrate that CIRTS is not only smaller than naturally occurring CRISPR-Cas programmable RNA binding systems but can also be built entirely from human protein parts. CIRTS provides a platform to probe fundamental RNA regulatory processes, and the human-derived nature of CIRTS provides a potential strategy to avoid immune issues when applied to epitranscriptome-modulating therapies.

SUBMITTER: Rauch S 

PROVIDER: S-EPMC6657360 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Programmable RNA-Guided RNA Effector Proteins Built from Human Parts.

Rauch Simone S   He Emily E   Srienc Michael M   Zhou Huiqing H   Zhang Zijie Z   Dickinson Bryan C BC  

Cell 20190620 1


Epitranscriptomic regulation controls information flow through the central dogma and provides unique opportunities for manipulating cells at the RNA level. However, both fundamental studies and potential translational applications are impeded by a lack of methods to target specific RNAs with effector proteins. Here, we present CRISPR-Cas-inspired RNA targeting system (CIRTS), a protein engineering strategy for constructing programmable RNA control elements. We show that CIRTS is a simple and gen  ...[more]

Similar Datasets

2020-04-13 | GSE128288 | GEO
| PRJNA527023 | ENA
| S-EPMC5127784 | biostudies-literature
| S-EPMC8612924 | biostudies-literature
| S-EPMC4747704 | biostudies-literature
| S-EPMC6286148 | biostudies-literature
| S-EPMC5940161 | biostudies-literature
| S-EPMC42239 | biostudies-other
| S-EPMC8692370 | biostudies-literature
| S-EPMC7667879 | biostudies-literature