Programmable RNA base editing with a single gRNA-free enzyme.

Programmable RNA editing enables rewriting gene expression without changing genome sequences. Current tools for specific RNA editing dependent on the assembly of guide RNA into an RNA/protein complex, causing delivery barrier and low editing efficiency. We report a new gRNA-free system, RNA editing with individual RNA-binding enzyme (REWIRE), to perform precise base editing with a single engineered protein. This artificial enzyme contains a human-originated programmable PUF domain to specifically recognize RNAs and different deaminase domains to achieve efficient A-to-I or C-to-U editing, which achieved 60-80% editing rate in human cells, with a few non-specific editing sites in the targeted region and a low level off-target effect globally. The RNA-binding domain in REWIREs was further optimized to improve editing efficiency and minimize off-target effects. We applied the REWIREs to correct disease-associated mutations and achieve both types of base editing in mice. As a single-component system originated from human proteins, REWIRE presents a precise and efficient RNA editing platform with broad applicability.

Comprehensive Identification of Translatable Circular RNAs Using Polysome Profiling.

Circular RNAs (circRNAs), a special type of RNAs without 5'- and 3'-ends, are widely present in eukaryotes and known to function as noncoding RNAs to regulate gene expression, including as miRNA sponges. Recent studies showed that many exonic circRNAs, generated by back-splicing of pre-mRNAs, can be translated in a cap-independent fashion through IRESs or m6A RNA methylation. However, the scope of the translatable circRNAs and the biological function of their translation products are still unclear in different cells and tissues. Ribosome footprinting and proteomic analysis were usually used to globally identify translatable circRNAs. However, both methods have low sensitivity due to the low efficiency in the discovery of circRNA specific reads or peptides (i.e., the back-splicing junctions are difficult to recover by the short reads of ribosome footprinting and the limitation of proteomic analysis). Here, we described an alternative method to identify translatable circRNAs using polysome profiling and circRNA-seq. Generally, polysome-associated RNAs were separated with sucrose gradients. Then polysome-bound circRNAs were enriched by an RNase R treatment and identified through paired-end deep sequencing. Thus, this method is more sensitive than ribosome footprint and proteomic analyses for the identification of translatable circRNAs.