Deciphering the regulatory code of RNA inosine through enzymatic precision mapping and explainable deep learning model

We previously reported Slic-seq, its unique terminal-blocking strategy, significantly enhances inosine detection accuracy. However, by capturing only inosine-modified RNA fragments, it lacks complete gene expression profiling and quantitative capability at editing sites.

These limitations hinder its broad application in transcriptome analysis. Here, we present REX-seq (RNA Endonuclease and XRN1 sequencing), a highly sensitive RNA editing detection technology based on the combined action of ENDOV enzyme-specific cleavage and XRN1 exonuclease. its unique design allows for comprehensive A-to-I editome characterization without compromising the accuracy of gene expression quantification.