Landscape of adenosine-to-inosine RNA recoding across human tissues.

RNA editing by adenosine deaminases changes the information encoded in the mRNA from its genomic blueprint. Editing of protein-coding sequences can introduce novel, functionally distinct, protein isoforms and diversify the proteome. The functional importance of a few recoding sites has been appreciated for decades. However, systematic methods to uncover these sites perform poorly, and the full repertoire of recoding in human and other mammals is unknown. Here we present a new detection approach, and analyze 9125 GTEx RNA-seq samples, to produce a highly-accurate atlas of 1517 editing sites within the coding region and their editing levels across human tissues. Single-cell RNA-seq data shows protein recoding contributes to the variability across cell subpopulations. Most highly edited sites are evolutionary conserved in non-primate mammals, attesting for adaptation. This comprehensive set can facilitate understanding of the role of recoding in human physiology and diseases.

Global quantification exposes abundant low-level off-target activity by base editors.

Base editors are dedicated engineered deaminases that enable directed conversion of specific bases in the genome or transcriptome in a precise and efficient manner, and hold promise for correcting pathogenic mutations. A major concern limiting application of this powerful approach is the issue of off-target edits. Several recent studies have shown substantial off-target RNA activity induced by base editors and demonstrated that off-target mutations may be suppressed by improved deaminases versions or optimized guide RNAs. Here, we describe a new class of off-target events that are invisible to the established methods for detection of genomic variations and were thus far overlooked. We show that nonspecific, seemingly stochastic, off-target events affect a large number of sites throughout the genome or the transcriptome, and account for the majority of off-target activity. We develop and employ a different, complementary approach that is sensitive to the stochastic off-target activity and use it to quantify the abundant off-target RNA mutations due to current, optimized deaminase editors. We provide a computational tool to quantify global off-target activity, which can be used to optimize future base editors. Engineered base editors enable directed manipulation of the genome or transcriptome at single-base resolution. We believe that implementation of this computational approach would facilitate design of more specific base editors.

Quantifying RNA Editing in Deep Transcriptome Datasets.

Massive transcriptome sequencing through the RNAseq technology has enabled quantitative transcriptome-wide investigation of co-/post-transcriptional mechanisms such as alternative splicing and RNA editing. The latter is abundant in human transcriptomes in which million adenosines are deaminated into inosines by the ADAR enzymes. RNA editing modulates the innate immune response and its deregulation has been associated with different human diseases including autoimmune and inflammatory pathologies, neurodegenerative and psychiatric disorders, and tumors. Accurate profiling of RNA editing using deep transcriptome data is still a challenge, and the results depend strongly on processing and alignment steps taken. Accurate calling of the inosinome repertoire, however, is required to reliably quantify RNA editing and, in turn, investigate its biological and functional role across multiple samples. Using real RNAseq data, we demonstrate the impact of different bioinformatics steps on RNA editing detection and describe the main metrics to quantify its level of activity.

Purifying selection of long dsRNA is the first line of defense against false activation of innate immunity.

BACKGROUND: Mobile elements comprise a large fraction of metazoan genomes. Accumulation of mobile elements is bound to produce multiple putative double-stranded RNA (dsRNA) structures within the transcriptome. These endogenous dsRNA structures resemble viral RNA and may trigger false activation of the innate immune response, leading to severe damage to the host cell. Adenosine to inosine (A-to-I) RNA editing is a common post-transcriptional modification, abundant within repetitive elements of all metazoans. It was recently shown that a key function of A-to-I RNA editing by ADAR1 is to suppress the immunogenic response by endogenous dsRNAs. RESULTS: Here, we analyze the transcriptomes of dozens of species across the Metazoa and identify a strong genomic selection against endogenous dsRNAs, resulting in their purification from the canonical transcriptome. This purifying selection is especially strong for long and nearly perfect dsRNAs. These are almost absent from mRNAs, but not pre-mRNAs, supporting the notion of selection due to cytoplasmic processes. The few long and nearly perfect structures found in human transcripts are weakly expressed and often heavily edited. CONCLUSION: Purifying selection of long dsRNA is an important defense mechanism against false activation of innate immunity. This newly identified principle governs the integration of mobile elements into the genome, a major driving force of genome evolution. Furthermore, we find that most ADAR1 activity is not required to prevent an immune response to endogenous dsRNAs. The critical targets of ADAR1 editing are, likely, to be found mostly in non-canonical transcripts.

Genome-wide quantification of ADAR adenosine-to-inosine RNA editing activity.

Adenosine-to-inosine (A-to-I) RNA editing by the adenosine deaminase that acts on RNA (ADAR) enzymes is a common RNA modification, preventing false activation of the innate immune system by endogenous double-stranded RNAs. Methods for quantification of ADAR activity are sought after, due to an increasing interest in the role of ADARs in cancer and autoimmune disorders, as well as attempts to harness the ADAR enzymes for RNA engineering. Here, we present the Alu editing index (AEI), a robust and simple-to-use computational tool devised for this purpose. We describe its properties and demonstrate its superiority to current quantification methods of ADAR activity. The AEI is used to map global editing across a large dataset of healthy human samples and identify putative regulators of ADAR, as well as previously unknown factors affecting the observed Alu editing levels. These should be taken into account in future comparative studies of ADAR activity. The AEI tool is available at https://github.com/a2iEditing/RNAEditingIndexer.

Increased RNA Editing May Provide a Source for Autoantigens in Systemic Lupus Erythematosus.

RNA-editing mechanisms, which induce nucleotide substitution in the RNA, increase transcript and protein diversities. Editing dysregulation has been shown to lead to grave outcomes, and transcriptome-wide aberrant RNA editing has been found in tumors. However, little is known about the involvement of editing in other diseases. Systemic lupus erythematosus (SLE) is a multisystemic autoimmune disease characterized by a loss of tolerance for autoantigens from various tissues and the production of multiple autoantibodies. Here, we show that blood samples from individuals with SLE have abnormally high levels of RNA editing, some of which affect proteins and potentially generate novel autoantigens. We suggest that elevated RNA editing, either by ADARs or APOBECs, may be involved in the pathophysiology of SLE, as well as in other autoimmune diseases, by generating or increasing the autoantigen load, a key requisite for the progression of autoimmunity.