RNA, like DNA and proteins, can undergo modifications. To date, over 170 RNA modifications have been identified, leading to the emergence of a new research area known as epitranscriptomics. RNA editing is the most frequent RNA modification in mammalian transcriptomes, and two types have been identified: (1) the most frequent, adenosine to inosine (A-to-I); and (2) the less frequent, cysteine to uracil (C-to-U) RNA editing. Unlike other epitranscriptomic marks, RNA editing can be readily detected from RNA sequencing (RNA-seq) data without any chemical conversions of RNA before sequencing library preparation. Furthermore, analyzing RNA editing patterns from transcriptomic data provides an additional layer of information about the epitranscriptome. As the significance of epitranscriptomics, particularly RNA editing, gains recognition in various fields of biology and medicine, there is a growing interest in detecting RNA editing sites (RES) by analyzing RNA-seq data. To cope with this increased interest, several bioinformatic tools are available. However, each tool has its advantages and disadvantages, which makes the choice of the most appropriate tool for bench scientists and clinicians difficult. Here, we have benchmarked bioinformatic tools to detect RES from RNA-seq data. We provide a comprehensive view of each tool and its performance using previously published RNA-seq data to suggest recommendations on the most appropriate for utilization in future studies.

Alu retroelements are specific to primates and abundant in the human genome. Through mutations that create functional splice sites within intronic Alus, these elements can become new exons in a process denoted exonization. It was recently shown that Alu elements are also heavily changed by RNA editing in the human genome.

The trypanosome RNA editing substrate binding complex (RESC) acts as the platform for mitochondrial uridine insertion/deletion RNA editing and facilitates the protein-protein and protein-RNA interactions required for the editing process. RESC is broadly comprised of two subcomplexes: GRBC (guide RNA binding complex) and REMC (RNA editing mediator complex). Here, we characterize the function and position in RESC organization of a previously unstudied RESC protein, MRB7260. We show that MRB7260 forms numerous RESC-related complexes, including a novel, small complex with the guide RNA binding protein, GAP1, which is a canonical GRBC component, and REMC components MRB8170 and TbRGG2. RNA immunoprecipitations in MRB7260-depleted cells show that MRB7260 is critical for normal RNA trafficking between REMC and GRBC. Analysis of protein-protein interactions also reveals an important role for MRB7260 in promoting stable association of the two subcomplexes. High-throughput sequencing analysis of RPS12 mRNAs from MRB7260 replete and depleted cells demonstrates that MRB7260 is critical for gRNA exchange and early gRNA utilization, with the exception of the initiating gRNA. Together, these data demonstrate that MRB7260 is essential for productive protein-RNA interactions with RESC during RNA editing.

MicroRNAs (miRNAs) are short RNAs of around 22 nucleotides that regulate gene expression. The primary transcripts of miRNAs contain double-stranded RNA and are therefore potential substrates for adenosine to inosine (A-to-I) RNA editing.

In eukaryotes, nascent RNA transcripts undergo an intricate series of RNA processing steps to achieve mRNA maturation. RNA editing and alternative splicing are two major RNA processing steps that can introduce significant modifications to the final gene products. By tackling these processes in isolation, recent studies have enabled substantial progress in understanding their global RNA targets and regulatory pathways. However, the interplay between individual steps of RNA processing, an essential aspect of gene regulation, remains poorly understood. By sequencing the RNA of different subcellular fractions, we examined the timing of adenosine-to-inosine (A-to-I) RNA editing and its impact on alternative splicing. We observed that >95% A-to-I RNA editing events occurred in the chromatin-associated RNA prior to polyadenylation. We report about 500 editing sites in the 3' acceptor sequences that can alter splicing of the associated exons. These exons are highly conserved during evolution and reside in genes with important cellular function. Furthermore, we identified a second class of exons whose splicing is likely modulated by RNA secondary structures that are recognized by the RNA editing machinery. The genome-wide analyses, supported by experimental validations, revealed remarkable interplay between RNA editing and splicing and expanded the repertoire of functional RNA editing sites.

The post-transcriptional sequence modification of transcripts through RNA editing is an important mechanism for regulating protein function and is associated with human disease phenotypes. The identification of RNA editing or RNA-DNA difference (RDD) sites is a fundamental step in the study of RNA editing. However, a substantial number of false-positive RDD sites have been identified recently. A major challenge in identifying RDD sites is to distinguish between the true RNA editing sites and the false positives. Furthermore, determining the location of condition-specific RDD sites and elucidating their functional roles will help toward understanding various biological phenomena that are mediated by RNA editing. The present study developed RNA-sequence comparison and annotation for RNA editing (RCARE) for searching, annotating, and visualizing RDD sites using thousands of previously known editing sites, which can be used for comparative analyses between multiple samples. RCARE also provides evidence for improving the reliability of identified RDD sites. RCARE is a web-based comparison, annotation, and visualization tool, which provides rich biological annotations and useful summary plots. The developers of previous tools that identify or annotate RNA-editing sites seldom mention the reliability of their respective tools. In order to address the issue, RCARE utilizes a number of scientific publications and databases to find specific documentations respective to a particular RNA-editing site, which generates evidence levels to convey the reliability of RCARE. Sequence-based alignment files can be converted into VCF files using a Python script and uploaded to the RCARE server for further analysis. RCARE is available for free at http://www.snubi.org/software/rcare/.

RNA-seq data can be mined for sequence differences relative to the reference genome to identify both genomic SNPs and RNA editing events. We analyzed the long, polyA-selected, unstranded, deeply sequenced RNA-seq data from the ENCODE Project across 14 human cell lines for candidate RNA editing events. On average, 43% of the RNA sequencing variants that are not in dbSNP and are within gene boundaries are A-to-G(I) RNA editing candidates. The vast majority of A-to-G(I) edits are located in introns and 3' UTRs, with only 123 located in protein-coding sequence. In contrast, the majority of non-A-to-G variants (60%-80%) map near exon boundaries and have the characteristics of splice-mapping artifacts. After filtering out all candidates with evidence of private genomic variation using genome resequencing or ChIP-seq data, we find that up to 85% of the high-confidence RNA variants are A-to-G(I) editing candidates. Genes with A-to-G(I) edits are enriched in Gene Ontology terms involving cell division, viral defense, and translation. The distribution and character of the remaining non-A-to-G variants closely resemble known SNPs. We find no reproducible A-to-G(I) edits that result in nonsynonymous substitutions in all three lymphoblastoid cell lines in our study, unlike RNA editing in the brain. Given that only a fraction of sites are reproducibly edited in multiple cell lines and that we find a stronger association of editing and specific genes suggests that the editing of the transcript is more important than the editing of any individual site.

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.

Compared to sites in protein-coding sequences many more targets undergoing adenosine to inosine (A-to-I) RNA editing were discovered in non-coding regions of human cerebral transcripts, particularly in genetic transposable elements called retrotransposons. We review here the interaction mechanisms of RNA editing and retrotransposons and their impact on normal function and human neurological diseases. Exemplarily, A-to-I editing of retrotransposons embedded in protein-coding mRNAs can contribute to protein abundance and function via circular RNA formation, alternative splicing, and exonization or silencing of retrotransposons. Interactions leading to disease are not very well understood. We describe human diseases with involvement of the central nervous system including inborn errors of metabolism, neurodevelopmental disorders, neuroinflammatory and neurodegenerative and paroxysmal diseases, in which retrotransposons (Alu and/or L1 elements) appear to be causally involved in genetic rearrangements. Sole binding of single-stranded retrotransposon transcripts by RNA editing enzymes rather than enzymatic deamination may have a homeostatic effect on retrotransposon turnover. We also review evidence in support of the emerging pathophysiological function of A-to-I editing of retrotransposons in inflammation and its implication for different neurological diseases including amyotrophic lateral sclerosis, frontotemporal dementia, Alzheimer's and Parkinson's disease, and epilepsy.

No abstract available

As an important regulatory mechanism at the posttranscriptional level in metazoans, adenosine deaminase acting on RNA (ADAR)-induced A-to-I RNA editing modification of double-stranded RNA has been widely detected and reported. Editing may lead to non-synonymous amino acid mutations, RNA secondary structure alterations, pre-mRNA processing changes, and microRNA-mRNA redirection, thereby affecting multiple cellular processes and functions. In recent years, researchers have successfully developed several bioinformatics software tools and pipelines to identify RNA editing sites. However, there are still no widely accepted editing site standards due to the variety of parallel optimization and RNA high-seq protocols and programs. It is also challenging to identify RNA editing by normal protocols in tumor samples due to the high DNA mutation rate. Numerous RNA editing sites have been reported to be located in non-coding regions and can affect the biosynthesis of ncRNAs, including miRNAs and circular RNAs. Predicting the function of RNA editing sites located in non-coding regions and ncRNAs is significantly difficult. In this review, we aim to provide a better understanding of bioinformatics strategies for human cancer A-to-I RNA editing identification and briefly discuss recent advances in related areas, such as the oncogenic and tumor suppressive effects of RNA editing.

RNA editing describes the process in which individual or short stretches of nucleotides in a messenger or structural RNA are inserted, deleted, or substituted. A high level of RNA editing has been observed in the mitochondrial genome of Physarum polycephalum. The most frequent editing type in Physarum is the insertion of individual Cs. RNA editing is extremely accurate in Physarum; however, little is known about its mechanism. Here, we demonstrate how analyzing two organisms from the Myxomycetes, namely Physarum polycephalum and Didymium iridis, allows us to test hypotheses about the editing mechanism that can not be tested from a single organism alone. First, we show that using the recently determined full transcriptome information of Physarum dramatically improves the accuracy of computational editing site prediction in Didymium. We use this approach to predict genes in the mitochondrial genome of Didymium and identify six new edited genes as well as one new gene that appears unedited. Next we investigate sequence conservation in the vicinity of editing sites between the two organisms in order to identify sites that harbor the information for the location of editing sites based on increased conservation. Our results imply that the information contained within only nine or ten nucleotides on either side of the editing site (a distance previously suggested through experiments) is not enough to locate the editing sites. Finally, we show that the codon position bias in C insertional RNA editing of these two organisms is correlated with the selection pressure on the respective genes thereby directly testing an evolutionary theory on the origin of this codon bias. Beyond revealing interesting properties of insertional RNA editing in Myxomycetes, our work suggests possible approaches to be used when finding sequence motifs for any biological process fails.

RNA editing is a post-transcriptional process that, in seed plants, involves a cytosine to uracil change in messenger RNA, causing the translated protein to differ from that predicted by the DNA sequence. RNA editing occurs extensively in plant mitochondria, but large differences in editing frequencies are found in some groups. The underlying processes responsible for the distribution of edited sites are largely unknown, but gene function, substitution rate, and gene conversion have been proposed to influence editing frequencies.

In the last two decades, RNA post-transcriptional modifications, including RNA editing, have been the subject of increasing interest among the scientific community. The efforts of the Human Genome Project combined with the development of new sequencing technologies and dedicated bioinformatic approaches created to detect and profile RNA transcripts have served to further our understanding of RNA editing. Investigators have determined that non-coding RNA (ncRNA) A-to-I editing is often deregulated in cancer. This discovery has led to an increased number of published studies in the field. However, the eventual clinical application for these findings remains a work in progress. In this review, we provide an overview of the ncRNA editing phenomenon in cancer. We discuss the bioinformatic strategies for RNA editing detection as well as the potential roles for ncRNA A to I editing in tumor immunity and as clinical biomarkers.

As previously demonstrated, the maize cox2 RNA is fully edited in cauliflower mitochondria. Use of constructs with a deleted cox2 intron, however, led to a loss of RNA editing at almost all editing sites, with only a few sites still partially edited. Likewise, one deletion in exon 1 and three in exon 2 abolish RNA editing at all cox2 sites analyzed. Furthermore, intron splicing is abolished using these deletions. Mutation of a cytosine residue, which is normally edited and localized directly adjacent to the intron, to thymidine did not result in restoration of splicing, indicating that the loss of splicing was not due to loss of RNA editing. One deletion in exon 2 did not lead to loss of splicing. Instead, most editing sites were found to be edited, only three were not edited. Unexpectedly, we observed additional RNA editing events at new sites. Thus it appears that deletions in the cox2 RNA sequence can have a strong effect on RNA processing, leading to loss of splicing, loss of editing at all sites, or even to a gain of new editing sites. As these effects are not limited to the vicinity of the respective deletions, but appear to be widespread or even affect all editing sites, they may not be explained by the loss of PPR binding sites. Instead, it appears that several parts of the cox2 transcript are required for proper RNA processing. This indicates the roles of the RNA sequence and structural elements in the recognition of the editing sites.

Plant regulatory circuits coordinating nuclear and plastid gene expression have evolved in response to external stimuli. RNA editing is one of such control mechanisms. We determined the Arabidopsis nuclear-encoded homeodomain-containing protein OCP3 is incorporated into the chloroplast, and contributes to control over the extent of ndhB transcript editing. ndhB encodes the B subunit of the chloroplast NADH dehydrogenase-like complex (NDH) involved in cyclic electron flow (CEF) around photosystem I. In ocp3 mutant strains, ndhB editing efficiency decays, CEF is impaired and disease resistance to fungal pathogens substantially enhanced, a process recapitulated in plants defective in editing plastid RNAs encoding NDH complex subunits due to mutations in previously described nuclear-encoded pentatricopeptide-related proteins (i.e. CRR21, CRR2). Furthermore, we observed that following a pathogenic challenge, wild type plants respond with editing inhibition of ndhB transcript. In parallel, rapid destabilization of the plastidial NDH complex is also observed in the plant following perception of a pathogenic cue. Therefore, NDH complex activity and plant immunity appear as interlinked processes.

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by ADAR enzymes, is an essential post-transcriptional modification. Although hundreds of thousands of RNA editing sites have been reported in mammals, brain-wide analysis of the RNA editing in the mammalian brain remains rare. Here, a genome-wide RNA-editing investigation is performed in 119 samples, representing 30 anatomically defined subregions in the pig brain. We identify a total of 682,037 A-to-I RNA editing sites of which 97% are not identified before. Within the pig brain, cerebellum and olfactory bulb are regions with most edited transcripts. The editing level of sites residing in protein-coding regions are similar across brain regions, whereas region-distinct editing is observed in repetitive sequences. Highly edited conserved recoding events in pig and human brain are found in neurotransmitter receptors, demonstrating the evolutionary importance of RNA editing in neurotransmission functions. Although potential data biases caused by age, sex or health status are not considered, this study provides a rich resource to better understand the evolutionary importance of post-transcriptional RNA editing.

RNA editing by adenosine deaminases acting on RNAs (ADARs) can be both specific and non-specific, depending on the substrate. Specific editing of particular adenosines may depend on the overall sequence and structural context. However, the detailed mechanisms underlying these preferences are not fully understood. Here, we show that duplex structures mimicking an editing site in the Gabra3 pre-mRNA unexpectedly fail to support RNA editing at the Gabra3 I/M site, although phylogenetic analysis suggest an evolutionarily conserved duplex structure essential for efficient RNA editing. These unusual results led us to revisit the structural requirement for this editing by mutagenesis analysis. In vivo nuclear injection experiments of mutated editing substrates demonstrate that a non-conserved structure is a determinant for editing. This structure contains bulges either on the same or the strand opposing the edited adenosine. The position of these bulges and the distance to the edited base regulate editing. Moreover, elevated folding temperature can lead to a switch in RNA editing suggesting an RNA structural change. Our results indicate the importance of RNA tertiary structure in determining RNA editing.

Thioredoxins (TRXs) occur in plant chloroplasts as complex disulphide oxidoreductases. Although many biological processes are regulated by thioredoxins, the regulatory mechanism of chloroplast TRXs are largely unknown. Here we report a rice white panicle2 mutant caused by a mutation in the thioredoxin z gene, an orthologue of AtTRX z in Arabidopsis. white panicle2 (wp2) seedlings exhibited a high-temperature-sensitive albinic phenotype. We found that plastid multiple organellar RNA editing factors (MORFs) were the regulatory targets of thioredoxin z. We showed that OsTRX z protein physically interacts with OsMORFs in a redox-dependent manner and that the redox state of a conserved cysteine in the MORF box is essential for MORF-MORF interactions. wp2 and OsTRX z knockout lines show reduced editing efficiencies in many plastidial-encoded genes especially under high-temperature conditions. An Arabidopsis trx z mutant also exhibited significantly reduced chloroplast RNA editing. Our combined results suggest that thioredoxin z regulates chloroplast RNA editing in plants by controlling the redox state of MORFs.

Type II CRISPR immune systems in bacteria use a dual RNA-guided DNA endonuclease, Cas9, to cleave foreign DNA at specific sites. We show here that Cas9 assembles with hybrid guide RNAs in human cells and can induce the formation of double-strand DNA breaks (DSBs) at a site complementary to the guide RNA sequence in genomic DNA. This cleavage activity requires both Cas9 and the complementary binding of the guide RNA. Experiments using extracts from transfected cells show that RNA expression and/or assembly into Cas9 is the limiting factor for Cas9-mediated DNA cleavage. In addition, we find that extension of the RNA sequence at the 3' end enhances DNA targeting activity in vivo. These results show that RNA-programmed genome editing is a facile strategy for introducing site-specific genetic changes in human cells.DOI:http://dx.doi.org/10.7554/eLife.00471.001.