One of the most prevalent epitranscriptomic modifications is RNA editing. In higher eukaryotes, RNA editing is catalyzed by one of two classes of deaminases: ADAR family enzymes that catalyze A-to-I (read as G) editing, and AID/APOBEC family enzymes that catalyze C-to-U. ADAR-catalyzed deamination has been studied extensively. Here we focus on AID/APOBEC-catalyzed editing, and review the emergent knowledge regarding C-to-U editing consequences in the context of human disease.

We present MultiEditR (Multiple Edit Deconvolution by Inference of Traces in R), the first algorithm specifically designed to detect and quantify RNA editing from Sanger sequencing ( z.umn.edu/multieditr ). Although RNA editing is routinely evaluated by measuring the heights of peaks from Sanger sequencing traces, the accuracy and precision of this approach has yet to be evaluated against gold standard next-generation sequencing methods. Through a comprehensive comparison to RNA sequencing (RNA-seq) and amplicon-based deep sequencing, we show that MultiEditR is accurate, precise, and reliable for detecting endogenous and programmable RNA editing.

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RNA editing is the base change that results from RNA deamination by two predominant classes of deaminases; the APOBEC family and the ADAR family. Respectively, deamination of nucleobases by these enzymes are responsible for endogenous editing of cytosine to uracil (Cto-U) and adenosine to inosine (A-to-I). RNA editing is known to play an essential role both in maintaining normal cellular function, as well as altered cellular physiology during oncogenesis and tumour progression. Analysis of RNA editing in these important processes, largely relies on RNA-seq technology for the detection and quantification of RNA editing sites. Despite the power of these technologies, multiple sources of error in detecting and measuring base editing still exist, therefore additional validation and quantification of editing through Sanger sequencing is still required for confirmation of editing. Depending on the number of RNA editing sites that are of interest, this validation step can be both expensive and time-consuming. To address this need we developed the tool MultiEditR which provides a simple, and cost-effective method of detecting and quantifying RNA editing form Sanger sequencing. We expect that MultiEditR will foster further discoveries in this rapidly expanding field.