A programmable system to methylate and demethylate m6A on specific mRNAs
Chang, C.; Ma, G.; Cheung, E.; Hutchins, A. P.
Show abstract
RNA N6-Methyladenosine (m6A) is the most abundant mRNA modification, and forms part of an epitranscriptomic system that modulates RNA function. RNA modifications can be reversibly catalyzed by several specific enzymes, and those modifications can be recognized by RNA binding proteins that in turn regulate biological processes. Although there are many reports demonstrating m6A participation in critical biological functions, this exploration has mainly been conducted through the global knockout or knockdown of the writers, erasers, or readers of m6A. Consequently, there is a lack of information about the role of m6A on single transcripts in biological processes, posing a challenge in understanding the biological functions of m6A. Here, we demonstrate a CRISPR/dCas13a-based RNA m6A-editor which can target mRNAs using single crRNA or multiple crRNAs array to methylate or demethylate m6A. We systematically assay its capabilities to enable the targeted rewriting of m6A dynamics, including modulation of circular RNA translation and transcript half-life. Finally, we demonstrate the utility of the system by specifically modulating XIST m6A levels, which can control X chromosome silencing and activation. Based on our editors, m6A on single and multiple transcripts can be modified to allow the exploration of the role of m6A on in biological processes.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Identification of Human Pathways Acting on Nuclear Non-Coding RNAs Using the Mirror Forward Genetic Approach 97%
- Expanded palette of RNA base editors for comprehensive RBP-RNA interactome studies 97%
- Transcriptional stochasticity reveals multiple mechanisms of long noncoding RNA regulation at the Xist - Tsix locus 97%
Similar papers in this journal
Similar papers in this journal
- A high-resolution map of functional miR-181 response elements in the thymus reveals the role of coding sequence targeting and an alternative seed match 97%
- DeepCLIP: Predicting the effect of mutations on protein-RNA binding with Deep Learning 96%
- Simultaneous multifunctional transcriptome engineering by CRISPR RNA scaffold 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.