Single-cell transcriptomics reveals specific RNA editing signatures in the human brain

REDInet: a temporal convolutional network-based classifier for A-to-I RNA editing detection harnessing million known events

A-to-I ribonucleic acid (RNA) editing detection is still a challenging task. Current bioinformatics tools rely on empirical filters and whole genome sequencing or whole exome sequencing data to remove background noise, sequencing errors, and artifacts. Sometimes they make use of cumbersome and time-consuming computational procedures. Here, we present REDInet, a temporal convolutional network-based deep learning algorithm, to profile RNA editing in human RNA sequencing (RNAseq) data. It has been trained on REDIportal RNA editing sites, the largest collection of human A-to-I changes from >8000 RNAseq data of the genotype-tissue expression project. REDInet can classify editing events with high accuracy harnessing RNAseq nucleotide frequencies of 101-base windows without the need for coupled genomic data.

Increased unedited Alu RNA patterns found in cortex extracellular vesicles in Alzheimer's disease resemble hippocampus vasculature Alu RNA editing patterns but not cortex Alu RNA editing patterns

BACKGROUND

Endogenous Alu RNAs form double-stranded RNAs recognized by double-stranded RNA sensors and activate IRF and NF-kB transcriptional paths and innate immunity. Deamination of adenosines to inosines by the ADAR family of enzymes, a process termed A-to-I editing, disrupts double-stranded RNA structure and prevents innate immune activation. Innate immune activation is observed in Alzheimer's disease, the most common form of dementia. We have previously reported loss of A-to-I editing in hippocampus vasculature, but no change in cortex or cortex vasculature, associated with Alzheimer's disease.

OBJECTIVE

Here, we investigated the status of Alu RNA A-to-I editing in cortex extracellular vesicles in Alzheimer's disease.

METHODS

We used existing RNA-seq data sets and the SPRINT software package to determine levels of Alu RNA A-to-I editing in cortex extracellular vesicles in Alzheimer's disease and control groups and compared these editing profiles to those found in both total cortex and hippocampus vasculature.

RESULTS

We find substantial loss of Alu A-to-I editing in cortex extracellular vesicles in Alzheimer's disease. By measuring editing patterns on a gene-by-gene basis, we determined that editing patterns in cortex extracellular vesicles resemble editing patterns in hippocampus vasculature rather than total cortex.

CONCLUSIONS

We conclude that hippocampus vasculature unedited Alu RNAs are packaged in extracellular vesicles, travel to the cortex, deliver their cargo and stimulate innate immunity and alter other basic biological processes contributing to Alzheimer's disease progression.

A de novo missense mutation in PPP2R5D alters dopamine pathways and morphology of iPSC-derived midbrain neurons

Induced pluripotent stem cell (iPSC) models of neurodevelopmental disorders (NDDs) have promoted an understanding of commonalities and differences within or across patient populations by revealing the underlying molecular and cellular mechanisms contributing to disease pathology. Here, we focus on developing a human model for PPP2R5D-related NDD, called Jordan syndrome, which has been linked to Early-Onset Parkinson's Disease (EOPD). Here we sought to understand the underlying molecular and cellular phenotypes across multiple cell states and neuronal subtypes in order to gain insight into Jordan syndrome pathology. Our work revealed that iPSC-derived midbrain neurons from Jordan syndrome patients display significant differences in dopamine-associated pathways and neuronal architecture. We then evaluated a CRISPR-based approach for editing heterozygous dominant G-to-A mutations at the transcript level in patient-derived neural stem cells. Our findings show that site-directed RNA editing is influenced by sgRNA length and cell type. These studies support the potential for a CRISPR RNA editor system to selectively edit mutant transcripts harboring G-to-A mutations in neural stem cells while providing an alternative editing technology for those suffering from NDDs.

Benchmarking bulk and single-cell variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries

Single-cell sequencing methodologies such as scRNA-seq and scATAC-seq have become widespread and effective tools to interrogate tissue composition. Increasingly, variant callers are being applied to these methodologies to resolve the genetic heterogeneity of a sample, especially in the case of detecting the clonal architecture of a tumor. Typically, traditional bulk DNA variant callers are applied to the pooled reads of a single-cell library to detect candidate mutations. Recently, multiple studies have applied such callers on reads from individual cells, with some citing the ability to detect rare variants with higher sensitivity. Many studies apply these two approaches to the Chromium (10x Genomics) scRNA-seq and scATAC-seq methodologies. However, Chromium-based libraries may offer additional challenges to variant calling compared with existing single-cell methodologies, raising questions regarding the validity of variants obtained from such a workflow. To determine the merits and challenges of various variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries, we use sample libraries with matched bulk whole-genome sequencing to evaluate the performance of callers. We review caller performance, finding that bulk callers applied on pooled reads significantly outperform individual-cell approaches. We also evaluate variants unique to scRNA-seq and scATAC-seq methodologies, finding patterns of noise but also potential capture of RNA-editing events. Finally, we review the notion that variant calling at the single-cell level can detect rare somatic variants, providing empirical results that suggest resolving such variants is infeasible in single-cell Chromium libraries.

Mitoclone2: an R package for elucidating clonal structure in single-cell RNA-sequencing data using mitochondrial variants

Clonal cell population dynamics play a critical role in both disease and development. Due to high mitochondrial mutation rates under both healthy and diseased conditions, mitochondrial genomic variability is a particularly useful resource in facilitating the identification of clonal population structure. Here we present mitoClone2, an all-inclusive R package allowing for the identification of clonal populations through integration of mitochondrial heteroplasmic variants discovered from single-cell sequencing experiments. Our package streamlines the investigation of this phenomenon by providing: built-in compatibility with commonly used tools for the delineation of clonal structure, the ability to directly use multiplexed BAM files as input, annotations for both human and mouse mitochondrial genomes, and helper functions for calling, filtering, clustering, and visualizing variants.

A stochastic RNA editing process targets a limited number of sites in individual Drosophila glutamatergic motoneurons

RNA editing is a post-transcriptional source of protein diversity and occurs across the animal kingdom. Given the complete profile of mRNA targets and their editing rate in individual cells is unclear, we analyzed single cell RNA transcriptomes from Drosophila larval tonic and phasic glutamatergic motoneuron subtypes to determine the most highly edited targets and identify cell-type specific editing. From ∼15,000 genes encoded in the genome, 316 high confidence A-to-I canonical RNA edit sites were identified, with 102 causing missense amino acid changes in proteins regulating membrane excitability, synaptic transmission, and cellular function. Some sites showed 100% editing in single neurons as observed with mRNAs encoding mammalian AMPA receptors. However, most sites were edited at lower levels and generated variable expression of edited and unedited mRNAs within individual neurons. Together, these data provide insights into how the RNA editing landscape alters protein function to modulate the properties of two well-characterized neuronal populations in Drosophila .

Differential microRNA editing may drive target pathway switching in human temporal lobe epilepsy

MicroRNAs have emerged as important regulators of the gene expression landscape in temporal lobe epilepsy. The mechanisms that control microRNA levels and influence target choice remain, however, poorly understood. RNA editing is a post-transcriptional mechanism mediated by the adenosine acting on RNA (ADAR) family of proteins that introduces base modification that diversifies the gene expression landscape. RNA editing has been studied for the mRNA landscape but the extent to which microRNA editing occurs in human temporal lobe epilepsy is unknown. Here, we used small RNA-sequencing data to characterize the identity and extent of microRNA editing in human temporal lobe epilepsy brain samples. This detected low-to-high editing in over 40 of the identified microRNAs. Among microRNA exhibiting the highest editing was miR-376a-3p, which was edited in the seed region and this was predicted to significantly change the target pool. The edited form was expressed at lower levels in human temporal lobe epilepsy samples. We modelled the shift in editing levels of miR-376a-3p in human-induced pluripotent stem cell-derived neurons. Reducing levels of the edited form of miR-376a-3p using antisense oligonucleotides resulted in extensive gene expression changes, including upregulation of mitochondrial and metabolism-associated pathways. Together, these results show that differential editing of microRNAs may re-direct targeting and result in altered functions relevant to the pathophysiology of temporal lobe epilepsy and perhaps other disorders of neuronal hyperexcitability.

Identification and Interpretation of A-to-I RNA Editing Events in Insect Transcriptomes

Adenosine-to-inosine (A-to-I) RNA editing is the most prevalent RNA modification in the nervous systems of metazoans. To study the biological significance of RNA editing, we first have to accurately identify these editing events from the transcriptome. The genome-wide identification of RNA editing sites remains a challenging task. In this review, we will first introduce the occurrence, regulation, and importance of A-to-I RNA editing and then describe the established bioinformatic procedures and difficulties in the accurate identification of these sit esespecially in small sized non-model insects. In brief, (1) to obtain an accurate profile of RNA editing sites, a transcriptome coupled with the DNA resequencing of a matched sample is favorable; (2) the single-cell sequencing technique is ready to be applied to RNA editing studies, but there are a few limitations to overcome; (3) during mapping and variant calling steps, various issues, like mapping and base quality, soft-clipping, and the positions of mismatches on reads, should be carefully considered; (4) Sanger sequencing of both RNA and the matched DNA is the best verification of RNA editing sites, but other auxiliary evidence, like the nonsynonymous-to-synonymous ratio or the linkage information, is also helpful for judging the reliability of editing sites. We have systematically reviewed the understanding of the biological significance of RNA editing and summarized the methodology for identifying such editing events. We also raised several promising aspects and challenges in this field. With insightful perspectives on both scientific and technical issues, our review will benefit the researchers in the broader RNA editing community.

Identification of Bona Fide RNA Editing Sites: History, Challenges, and Opportunities

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by the adenosine deaminase acting on the RNA (ADAR) family of enzymes of which there are three members (ADAR1, ADAR2, and ADAR3), is a major gene regulatory mechanism that diversifies the transcriptome. It is widespread in many metazoans, including humans. As inosine is interpreted by cellular machineries mainly as guanosine, A-to-I editing effectively gives A-to-G nucleotide changes. Depending on its location, an editing event can generate new protein isoforms or influence other RNA processing pathways. Researchers have found that ADAR-mediated editing performs diverse functions. For example, it enables living organisms such as cephalopods to adapt rapidly to fluctuating environmental conditions such as water temperature. In development, the loss of ADAR1 is embryonically lethal partly because endogenous double-stranded RNAs (dsRNAs) are no longer marked by inosines, which signal "self", and thus cause the melanoma differentiation-associated protein 5 (MDA5) sensor to trigger a deleterious interferon response. Hence, ADAR1 plays a key role in preventing aberrant activation of the innate immune system. Furthermore, ADAR enzymes have been implicated in myriad human diseases. Intriguingly, some cancer cells are known to exploit ADAR1 activity to dodge immune responses. However, the exact identities of immunogenic RNAs in different biological contexts have remained elusive. Consequently, there is tremendous interest in identifying inosine-containing RNAs in the cell.The identification of A-to-I RNA editing sites is dependent on the sequencing of nucleic acids. Technological and algorithmic advancements over the past decades have revolutionized the way editing events are detected. At the beginning, the discovery of editing sites relies on Sanger sequencing, a first-generation technology. Both RNA, which is reverse transcribed into complementary DNA (cDNA), and genomic DNA (gDNA) from the same source are analyzed. After sequence alignment, one would require an adenosine to be present in the genome but a guanosine to be detected in the RNA sample for a position to be declared as an editing site. However, an issue with Sanger sequencing is its low throughput. Subsequently, Illumina sequencing, a second-generation technology, was invented. By permitting the simultaneous interrogation of millions of molecules, it enables many editing sites to be identified rapidly. However, a key challenge is that the Illumina platform produces short sequencing reads that can be difficult to map accurately. To tackle the challenge, we and others developed computational workflows with a series of filters to discard sites that are likely to be false positives. When Illumina sequencing data sets are properly analyzed, A-to-G variants should emerge as the most dominant mismatch type. Moreover, the quantitative nature of the data allows us to build a comprehensive atlas of editing-level measurements across different biological contexts, providing deep insights into the spatiotemporal dynamics of RNA editing. However, difficulties remain in identifying true A-to-I editing sites in short protein-coding exons or in organisms and diseases where DNA mutations and genomic polymorphisms are prevalent and mostly unknown. Nanopore sequencing, a third-generation technology, promises to address the difficulties, as it allows native RNAs to be sequenced without conversion to cDNA, preserving base modifications that can be directly detected through machine learning. We recently demonstrated that nanopore sequencing could be used to identify A-to-I editing sites in native RNA directly. Although further work is needed to enhance the detection accuracy in single molecules from fewer cells, the nanopore technology holds the potential to revolutionize epitranscriptomic studies.

ADAR1-mediated RNA editing promotes B cell lymphomagenesis

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-κB signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-κB signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3'UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

Squid express conserved ADAR orthologs that possess novel features

The coleoid cephalopods display unusually extensive mRNA recoding by adenosine deamination, yet the underlying mechanisms are not well understood. Because the adenosine deaminases that act on RNA (ADAR) enzymes catalyze this form of RNA editing, the structure and function of the cephalopod orthologs may provide clues. Recent genome sequencing projects have provided blueprints for the full complement of coleoid cephalopod ADARs. Previous results from our laboratory have shown that squid express an ADAR2 homolog, with two splice variants named sqADAR2a and sqADAR2b and that these messages are extensively edited. Based on octopus and squid genomes, transcriptomes, and cDNA cloning, we discovered that two additional ADAR homologs are expressed in coleoids. The first is orthologous to vertebrate ADAR1. Unlike other ADAR1s, however, it contains a novel N-terminal domain of 641 aa that is predicted to be disordered, contains 67 phosphorylation motifs, and has an amino acid composition that is unusually high in serines and basic amino acids. mRNAs encoding sqADAR1 are themselves extensively edited. A third ADAR-like enzyme, sqADAR/D-like, which is not orthologous to any of the vertebrate isoforms, is also present. Messages encoding sqADAR/D-like are not edited. Studies using recombinant sqADARs suggest that only sqADAR1 and sqADAR2 are active adenosine deaminases, both on perfect duplex dsRNA and on a squid potassium channel mRNA substrate known to be edited in vivo. sqADAR/D-like shows no activity on these substrates. Overall, these results reveal some unique features in sqADARs that may contribute to the high-level RNA recoding observed in cephalopods.

Translational opportunities of single-cell biology in atherosclerosis

The advent of single-cell biology opens a new chapter for understanding human biological processes and for diagnosing, monitoring, and treating disease. This revolution now reaches the field of cardiovascular disease (CVD). New technologies to interrogate CVD samples at single-cell resolution are allowing the identification of novel cell communities that are important in shaping disease development and direct towards new therapeutic strategies. These approaches have begun to revolutionize atherosclerosis pathology and redraw our understanding of disease development. This review discusses the state-of-the-art of single-cell analysis of atherosclerotic plaques, with a particular focus on human lesions, and presents the current resolution of cellular subpopulations and their heterogeneity and plasticity in relation to clinically relevant features. Opportunities and pitfalls of current technologies as well as the clinical impact of single-cell technologies in CVD patient care are highlighted, advocating for multidisciplinary and international collaborative efforts to join the cellular dots of CVD.

Profiling RNA Editing in Single Cells

RNA editing is a widespread molecular phenomenon occurring in a variety of organisms. In humans, it mainly involves the deamination of adenosine to inosine (A-to-I) in double-stranded RNAs by ADAR enzymes. A-to-I RNA editing has been investigated in different tissues as well as in diverse experimental and pathological conditions. By contrast, its biological role in single cells has not been explored in depth. Recent methodologies for cell sorting in combination with deep sequencing technologies have enabled the study of eukaryotic transcriptomes at single cell resolution, paving the way to the profiling of their epitranscriptomic dynamics.Here we describe a step-by-step protocol to detect and characterize A-to-I events occurring in publicly available single-cell RNAseq experiments from human alpha and beta pancreatic cells.

RNA Editing Alterations Define Disease Manifestations in the Progression of Experimental Autoimmune Encephalomyelitis (EAE)

RNA editing is an epitranscriptomic modification, leading to targeted changes in RNA transcripts. It is mediated by the action of ADAR (adenosine deaminases acting on double-stranded (ds) RNA and APOBEC (apolipoprotein B mRNA editing enzyme catalytic polypeptide-like) deaminases and appears to play a major role in the pathogenesis of many diseases. Here, we assessed its role in experimental autoimmune encephalomyelitis (EAE), a widely used non-clinical model of autoimmune inflammatory diseases of the central nervous system (CNS), which resembles many aspects of human multiple sclerosis (MS). We have analyzed in silico data from microglia isolated at different timepoints through disease progression to identify the global editing events and validated the selected targets in murine tissue samples. To further evaluate the functional role of RNA editing, we induced EAE in transgenic animals lacking expression of APOBEC-1. We found that RNA-editing events, mediated by the APOBEC and ADAR deaminases, are significantly reduced throughout the course of disease, possibly affecting the protein expression necessary for normal neurological function. Moreover, the severity of the EAE model was significantly higher in APOBEC-1 knock-out mice, compared to wild-type controls. Our results implicate regulatory epitranscriptomic mechanisms in EAE pathogenesis that could be extrapolated to MS and other neurodegenerative disorders (NDs) with common clinical and molecular features.

Survey of the binding preferences of RNA-binding proteins to RNA editing events

BACKGROUND

Adenosine-to-inosine (A-to-I) editing is an important RNA posttranscriptional process related to a multitude of cellular and molecular activities. However, systematic characterizations of whether and how the events of RNA editing are associated with the binding preferences of RNA sequences to RNA-binding proteins (RBPs) are still lacking.

RESULTS

With the RNA-seq and RBP eCLIP-seq datasets from the ENCODE project, we quantitatively survey the binding preferences of 150 RBPs to RNA editing events, followed by experimental validations. Such analyses of the RBP-associated RNA editing at nucleotide resolution and genome-wide scale shed light on the involvement of RBPs specifically in RNA editing-related processes, such as RNA splicing, RNA secondary structures, RNA decay, and other posttranscriptional processes.

CONCLUSIONS

These results highlight the relevance of RNA editing in the functions of many RBPs and therefore serve as a resource for further characterization of the functional associations between various RNA editing events and RBPs.

Cellular and genetic drivers of RNA editing variation in the human brain

Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence-derived GABAergic neurons, and oligodendrocytes. We identify more selective editing and hyper-editing in neurons relative to oligodendrocytes. RNA editing patterns are highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites is confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites are enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing is largely explained by neuronal proportions in bulk brain tissue. Finally, we uncover 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.

Here the authors provide a deep catalogue of cell-specific A-to-I editing sites in the human cortex. Thousands of sites are enriched and elevated in neurons relative to glial cells, and are genetically regulated across multiple brain regions.

A Systematic Review of Common and Brain-Disease-Specific RNA Editing Alterations Providing Novel Insights into Neurological and Neurodegenerative Disease Manifestations

RNA editing contributes to transcriptome diversification through RNA modifications in relation to genome-encoded information (RNA–DNA differences, RDDs). The deamination of Adenosine (A) to Inosine (I) or Cytidine (C) to Uridine (U) is the most common type of mammalian RNA editing. It occurs as a nuclear co- and/or post-transcriptional event catalyzed by ADARs (Adenosine deaminases acting on RNA) and APOBECs (apolipoprotein B mRNA editing enzyme catalytic polypeptide-like genes). RNA editing may modify the structure, stability, and processing of a transcript. This review focuses on RNA editing in psychiatric, neurological, neurodegenerative (NDs), and autoimmune brain disorders in humans and rodent models. We discuss targeted studies that focus on RNA editing in specific neuron-enriched transcripts with well-established functions in neuronal activity, and transcriptome-wide studies, enabled by recent technological advances. We provide comparative editome analyses between human disease and corresponding animal models. Data suggest RNA editing to be an emerging mechanism in disease development, displaying common and disease-specific patterns. Commonly edited RNAs represent potential disease-associated targets for therapeutic and diagnostic values. Currently available data are primarily descriptive, calling for additional research to expand global editing profiles and to provide disease mechanistic insights. The potential use of RNA editing events as disease biomarkers and available tools for RNA editing identification, classification, ranking, and functional characterization that are being developed will enable comprehensive analyses for a better understanding of disease(s) pathogenesis and potential cures.

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.

Gabay et al. provide a highly-accurate atlas of recoding by A-to-I RNA editing in human, profiled across tissues and cell subpopulations. Most highly edited sites are evolutionary conserved in non-primate mammals, attesting for adaptation.

Detection of A-to-I RNA Editing in SARS-COV-2

ADAR1-mediated deamination of adenosines in long double-stranded RNAs plays an important role in modulating the innate immune response. However, recent investigations based on metatranscriptomic samples of COVID-19 patients and SARS-COV-2-infected Vero cells have recovered contrasting findings. Using RNAseq data from time course experiments of infected human cell lines and transcriptome data from Vero cells and clinical samples, we prove that A-to-G changes observed in SARS-COV-2 genomes represent genuine RNA editing events, likely mediated by ADAR1. While the A-to-I editing rate is generally low, changes are distributed along the entire viral genome, are overrepresented in exonic regions, and are (in the majority of cases) nonsynonymous. The impact of RNA editing on virus-host interactions could be relevant to identify potential targets for therapeutic interventions.

A survey of RNA editing at single-cell resolution links interneurons to schizophrenia and autism

Conversion of adenosine to inosine in RNA by ADAR enzymes, termed "RNA editing," is essential for healthy brain development. Editing is dysregulated in neuropsychiatric diseases, but has not yet been investigated at scale at the level of individual neurons. We quantified RNA editing sites in nuclear transcriptomes of 3055 neurons from six cortical regions of a neurotypical female donor, and found 41,930 sites present in at least ten nuclei. Most sites were located within Alu repeats in introns or 3' UTRs, and approximately 80% were cataloged in public RNA editing databases. We identified 9285 putative novel editing sites, 29% of which were also detectable in unrelated donors. Intersection with results from bulk RNA-seq studies provided cell-type and spatial context for 1730 sites that are differentially edited in schizophrenic brain donors, and 910 such sites in autistic donors. Autism-related genes were also enriched with editing sites predicted to modify RNA structure. Inhibitory neurons showed higher overall transcriptome editing than excitatory neurons, and the highest editing rates were observed in the frontal cortex. We used generalized linear models to identify differentially edited sites and genes between cell types. Twenty nine genes were preferentially edited in excitatory neurons, and 43 genes were edited more heavily in inhibitory neurons, including RBFOX1, its target genes, and genes in the autism-associated Prader-Willi locus (15q11). The abundance of SNORD115/116 genes from locus 15q11 was positively associated with editing activity across the transcriptome. We contend that insufficient editing of autism-related genes in inhibitory neurons may contribute to the specific perturbation of those cells in autism.

Accurate Single-Cell Clustering through Ensemble Similarity Learning

Single-cell sequencing provides novel means to interpret the transcriptomic profiles of individual cells. To obtain in-depth analysis of single-cell sequencing, it requires effective computational methods to accurately predict single-cell clusters because single-cell sequencing techniques only provide the transcriptomic profiles of each cell. Although an accurate estimation of the cell-to-cell similarity is an essential first step to derive reliable single-cell clustering results, it is challenging to obtain the accurate similarity measurement because it highly depends on a selection of genes for similarity evaluations and the optimal set of genes for the accurate similarity estimation is typically unknown. Moreover, due to technical limitations, single-cell sequencing includes a larger number of artificial zeros, and the technical noise makes it difficult to develop effective single-cell clustering algorithms. Here, we describe a novel single-cell clustering algorithm that can accurately predict single-cell clusters in large-scale single-cell sequencing by effectively reducing the zero-inflated noise and accurately estimating the cell-to-cell similarities. First, we construct an ensemble similarity network based on different similarity estimates, and reduce the artificial noise using a random walk with restart framework. Finally, starting from a larger number small size but highly consistent clusters, we iteratively merge a pair of clusters with the maximum similarities until it reaches the predicted number of clusters. Extensive performance evaluation shows that the proposed single-cell clustering algorithm can yield the accurate single-cell clustering results and it can help deciphering the key messages underlying complex biological mechanisms.

RNA Editing: A New Therapeutic Target in Amyotrophic Lateral Sclerosis and Other Neurological Diseases

The conversion of adenosine to inosine in RNA editing (A-to-I RNA editing) is recognized as a critical post-transcriptional modification of RNA by adenosine deaminases acting on RNAs (ADARs). A-to-I RNA editing occurs predominantly in mammalian and human central nervous systems and can alter the function of translated proteins, including neurotransmitter receptors and ion channels; therefore, the role of dysregulated RNA editing in the pathogenesis of neurological diseases has been speculated. Specifically, the failure of A-to-I RNA editing at the glutamine/arginine (Q/R) site of the GluA2 subunit causes excessive permeability of α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptors to Ca2+, inducing fatal status epilepticus and the neurodegeneration of motor neurons in mice. Therefore, an RNA editing deficiency at the Q/R site in GluA2 due to the downregulation of ADAR2 in the motor neurons of sporadic amyotrophic lateral sclerosis (ALS) patients suggests that Ca2+-permeable AMPA receptors and the dysregulation of RNA editing are suitable therapeutic targets for ALS. Gene therapy has recently emerged as a new therapeutic opportunity for many heretofore incurable diseases, and RNA editing dysregulation can be a target for gene therapy; therefore, we reviewed neurological diseases associated with dysregulated RNA editing and a new therapeutic approach targeting dysregulated RNA editing, especially one that is effective in ALS.

Adaptive Proteome Diversification by Nonsynonymous A-to-I RNA Editing in Coleoid Cephalopods

RNA editing by the ADAR enzymes converts selected adenosines into inosines, biological mimics for guanosines. By doing so, it alters protein-coding sequences, resulting in novel protein products that diversify the proteome beyond its genomic blueprint. Recoding is exceptionally abundant in the neural tissues of coleoid cephalopods (octopuses, squids, and cuttlefishes), with an over-representation of nonsynonymous edits suggesting positive selection. However, the extent to which proteome diversification by recoding provides an adaptive advantage is not known. It was recently suggested that the role of evolutionarily conserved edits is to compensate for harmful genomic substitutions, and that there is no added value in having an editable codon as compared with a restoration of the preferred genomic allele. Here, we show that this hypothesis fails to explain the evolutionary dynamics of recoding sites in coleoids. Instead, our results indicate that a large fraction of the shared, strongly recoded, sites in coleoids have been selected for proteome diversification, meaning that the fitness of an editable A is higher than an uneditable A or a genomically encoded G.

Proteome Diversification by RNA Editing

RNA editing is an RNA modification that alters the RNA sequence relative to its genomic blueprint. The most common type of RNA editing is A-to-I editing by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes. Editing of a protein-coding region within the RNA molecule may result in non-synonymous substitutions, leading to a modified protein product. These editing sites, also known as "recoding" sites, contribute to the complexity and diversification of the proteome. Recent computational transcriptomic studies have identified thousands of recoding sites in multiple species, many of which are conserved within (but not usually across) lineages and have functional and evolutionary importance. In this chapter we describe the recoding phenomenon across species, consider its potential utility for diversity and adaptation, and discuss its evolution.

A-to-I RNA Editing in Cancer: From Evaluating the Editing Level to Exploring the Editing Effects

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.

Adenosine-to-inosine RNA editing in neurological development and disease

Adenosine-to-inosine (A-to-I) editing is one of the most prevalent post-transcriptional RNA modifications in metazoan. This reaction is catalysed by enzymes called adenosine deaminases acting on RNA (ADARs). RNA editing is involved in the regulation of protein function and gene expression. The numerous A-to-I editing sites have been identified in both coding and non-coding RNA transcripts. These editing sites are also found in various genes expressed in the central nervous system (CNS) and play an important role in neurological development and brain function. Aberrant regulation of RNA editing has been associated with the pathogenesis of neurological and psychiatric disorders, suggesting the physiological significance of RNA editing in the CNS. In this review, we discuss the current knowledge of editing on neurological disease and development.

PRIME: a probabilistic imputation method to reduce dropout effects in single-cell RNA sequencing

SUMMARY

Single-cell RNA sequencing technology provides a novel means to analyze the transcriptomic profiles of individual cells. The technique is vulnerable, however, to a type of noise called dropout effects, which lead to zero-inflated distributions in the transcriptome profile and reduce the reliability of the results. Single-cell RNA sequencing data, therefore, need to be carefully processed before in-depth analysis. Here, we describe a novel imputation method that reduces dropout effects in single-cell sequencing. We construct a cell correspondence network and adjust gene expression estimates based on transcriptome profiles for the local subnetwork of cells of the same type. We comprehensively evaluated this method, called PRIME (PRobabilistic IMputation to reduce dropout effects in Expression profiles of single-cell sequencing), on synthetic and eight real single-cell sequencing datasets and verified that it improves the quality of visualization and accuracy of clustering analysis and can discover gene expression patterns hidden by noise.

AVAILABILITY AND IMPLEMENTATION

The source code for the proposed method is freely available at https://github.com/hyundoo/PRIME.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA processing in neurological tissue: development, aging and disease

Gene expression comprises a diverse array of enzymes, proteins, non-coding transcripts, and cellular structures to guide the transfer of genetic information to its various final products. In the brain, the coordination among genes, or lack thereof, characterizes individual brain regions, mediates a variety of brain-related disorders, and brings light to fundamental differences between species. RNA processing, occurring between transcription and translation, controls an essential portion of gene expression through splicing, editing, localization, stability, and interference. The machinery to regulate transcripts must operate with precision serving as a blueprint for proteins and non-coding RNAs to derive their identity. Therefore, RNA processing has a broad scope of influence in the brain, as it modulates cell morphogenesis during development and underlies mechanisms behind certain neurological diseases. Here, we present these ideas through recent findings on RNA processing in development and post-developmental maturity to advance therapeutic discoveries and the collective knowledge of the RNA life cycle.

RNA editing: an overlooked source of fine-scale adaptation in insect vectors?

RNA editing is a source of molecular diversity that regulates the functional repertoire of animal transcriptomes. Multiple studies in Drosophila have revealed that conserved editing events can be a source of evolutionary adaptations, and there is a solid body of evidence linking editing and the fine-tuning of neural genes, which are often targeted by insecticides used in vector control. Yet, despite these suggestive connections, genome-wide analyses of editing in insect vectors are conspicuously lacking. Future advances will require complementing the growing wealth of vector genomes with targeted transcriptome analyses. Here, we review recent investigations of the genetic footprints of adaptive RNA editing in insects and provide an overview of new methodologies applicable to studies of RNA editing in insect vectors.

RNA Editing and Modifications in Mood Disorders

Major depressive disorder (MDD) is a major health problem with significant limitations in functioning and well-being. The World Health Organization (WHO) evaluates MDD as one of the most disabling disorders in the world and with very high social cost. Great attention has been given to the study of the molecular mechanism underpinning MDD at the genetic, epigenetic and proteomic level. However, the importance of RNA modifications has attracted little attention until now in this field. RNA molecules are extensively and dynamically altered by a variety of mechanisms. Similar to "epigenomic" changes, which modify DNA structure or histones, RNA alterations are now termed "epitranscriptomic" changes and have been predicted to have profound consequences for gene expression and cellular functionality. Two of these modifications, adenosine to inosine (A-to-I) RNA editing and m6A methylations, have fascinated researchers over the last years, showing a new level of complexity in gene expression. In this review, we will summary the studies that focus on the role of RNA editing and m6A methylation in MDD, trying to underline their potential breakthroughs and pitfalls.

RNA editing contributes to epitranscriptome diversity in chronic lymphocytic leukemia

RNA editing-primarily conversion of adenosine to inosine (A > I)-is a widespread posttranscriptional mechanism, mediated by Adenosine Deaminases acting on RNA (ADAR) enzymes to alter the RNA sequence of primary transcripts. Hence, in addition to somatic mutations and alternative RNA splicing, RNA editing can be a further source for recoding events. Although RNA editing has been detected in many solid cancers and normal tissue, RNA editing in chronic lymphocytic leukemia (CLL) has not been addressed so far. We determined global RNA editing and recurrent, recoding RNA editing events from matched RNA-sequencing and whole exome sequencing data in CLL samples from 45 untreated patients. RNA editing was verified in a validation cohort of 98 CLL patients and revealed substantially altered RNA editing profiles in CLL compared with normal B cells. We further found that RNA editing patterns were prognostically relevant. Finally, we showed that ADAR knockout decreased steady state viability of MEC1 cells and made them more susceptible to treatment with fludarabine and ibrutinib in vitro. We propose that RNA editing contributes to the pathophysiology of CLL and targeting the RNA editing machinery could be a future strategy to maximize treatment efficacy.

Effective single-cell clustering through ensemble feature selection and similarity measurements

Single-cell RNA sequencing technologies have revolutionized biomedical research by providing an effective means to profile gene expressions in individual cells. One of the first fundamental steps to perform the in-depth analysis of single-cell sequencing data is cell type classification and identification. Computational methods such as clustering algorithms have been utilized and gaining in popularity because they can save considerable resources and time for experimental validations. Although selecting the optimal features (i.e., genes) is an essential process to obtain accurate and reliable single-cell clustering results, the computational complexity and dropout events that can introduce zero-inflated noise make this process very challenging. In this paper, we propose an effective single-cell clustering algorithm based on the ensemble feature selection and similarity measurements. We initially identify the set of potential features, then measure the cell-to-cell similarity based on the subset of the potentials through multiple feature sampling approaches. We construct the ensemble network based on cell-to-cell similarity. Finally, we apply a network-based clustering algorithm to obtain single-cell clusters. We evaluate the performance of our proposed algorithm through multiple assessments in real-world single-cell RNA sequencing datasets with known cell types. The results show that our proposed algorithm can identify accurate and consistent single-cell clustering. Moreover, the proposed algorithm takes relative expression as input, so it can easily be adopted by existing analysis pipelines. The source code has been made publicly available at https://github.com/jeonglab/scCLUE.

A new mouse line with reduced GluA2 Q/R site RNA editing exhibits loss of dendritic spines, hippocampal CA1-neuron loss, learning and memory impairments and NMDA receptor-independent seizure vulnerability

Calcium (Ca²⁺)-permeable AMPA receptors may, in certain circumstances, contribute to normal synaptic plasticity or to neurodegeneration. AMPA receptors are Ca²⁺-permeable if they lack the GluA2 subunit or if GluA2 is unedited at a single nucleic acid, known as the Q/R site. In this study, we examined mice engineered with a point mutation in the intronic editing complementary sequence (ECS) of the GluA2 gene, Gria2. Mice heterozygous for the ECS mutation (named GluA2^+/ECS(G)) had a ~ 20% reduction in GluA2 RNA editing at the Q/R site. We conducted an initial phenotypic analysis of these mice, finding altered current-voltage relations (confirming expression of Ca²⁺-permeable AMPA receptors at the synapse). Anatomically, we observed a loss of hippocampal CA1 neurons, altered dendritic morphology and reductions in CA1 pyramidal cell spine density. Behaviourally, GluA2^+/ECS(G) mice exhibited reduced motor coordination, and learning and memory impairments. Notably, the mice also exhibited both NMDA receptor-independent long-term potentiation (LTP) and vulnerability to NMDA receptor-independent seizures. These NMDA receptor-independent seizures were rescued by the Ca²⁺-permeable AMPA receptor antagonist IEM-1460. In summary, unedited GluA2(Q) may have the potential to drive NMDA receptor-independent processes in brain function and disease. Our study provides an initial characterisation of a new mouse model for studying the role of unedited GluA2(Q) in synaptic and dendritic spine plasticity in disorders where unedited GluA2(Q), synapse loss, neurodegeneration, behavioural impairments and/or seizures are observed, such as ischemia, seizures and epilepsy, Huntington’s disease, amyotrophic lateral sclerosis, astrocytoma, cocaine seeking behaviour and Alzheimer’s disease.

Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal

RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools.

Spatiotemporal mapping of RNA editing in the developing mouse brain using in situ sequencing reveals regional and cell-type-specific regulation

Background

Adenosine-to-inosine (A-to-I) RNA editing is a process that contributes to the diversification of proteins that has been shown to be essential for neurotransmission and other neuronal functions. However, the spatiotemporal and diversification properties of RNA editing in the brain are largely unknown. Here, we applied in situ sequencing to distinguish between edited and unedited transcripts in distinct regions of the mouse brain at four developmental stages, and investigate the diversity of the RNA landscape.

Results

We analyzed RNA editing at codon-altering sites using in situ sequencing at single-cell resolution, in combination with the detection of individual ADAR enzymes and specific cell type marker transcripts. This approach revealed cell-type-specific regulation of RNA editing of a set of transcripts, and developmental and regional variation in editing levels for many of the targeted sites. We found increasing editing diversity throughout development, which arises through regional- and cell type-specific regulation of ADAR enzymes and target transcripts.

Conclusions

Our single-cell in situ sequencing method has proved useful to study the complex landscape of RNA editing and our results indicate that this complexity arises due to distinct mechanisms of regulating individual RNA editing sites, acting both regionally and in specific cell types.

Electronic supplementary material

The online version of this article (10.1186/s12915-019-0736-3) contains supplementary material, which is available to authorized users.

Adenosine-to-Inosine RNA Editing in Mouse and Human Brain Proteomes

Proteogenomics is based on the use of customized genome or RNA sequencing databases for interrogation of shotgun proteomics data in search for proteome-level evidence of genome variations or RNA editing. In this work, the products of adenosine-to-inosine RNA editing in human and murine brain proteomes are identified using publicly available brain proteome LC-MS/MS datasets and an RNA editome database compiled from several sources. After filtering of false-positive results, 20 and 37 sites of editing in proteins belonging to 14 and 32 genes are identified for murine and human brain proteomes, respectively. Eight sites of editing identified with high spectral counts overlapped between human and mouse brain samples. Some of these sites have been previously reported using orthogonal methods, such as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptors, CYFIP2, coatomer alpha. Also, differential editing between neurons and microglia is demonstrated in this work for some of the proteins from primary murine brain cell cultures. Because many edited sites are still not characterized functionally at the protein level, the results provide a necessary background for their further analysis in normal and diseased cells and tissues using targeted proteomic approaches.

Elucidating the editome: bioinformatics approaches for RNA editing detection

RNA editing is a widespread co/posttranscriptional mechanism affecting primary RNAs by specific nucleotide modifications, which plays relevant roles in molecular processes including regulation of gene expression and/or the processing of noncoding RNAs. In recent years, the detection of editing sites has been improved through the availability of high-throughput RNA sequencing (RNA-Seq) technologies. Accurate bioinformatics pipelines are essential for the analysis of next-generation sequencing (NGS) data to ensure the correct identification of edited sites. Several pipelines, using various read mappers and variant callers with a wide range of adjustable parameters, are available for the detection of RNA editing events. In this review, we discuss some of the most recent and popular tools and provide guidelines for RNA-Seq data generation and analysis for the detection of RNA editing in massive transcriptome data. Using simulated and real data sets, we provide an overview of their behavior, emphasizing the fact that the RNA editing detection in NGS data sets remains a challenging task.

Uncovering the Transcriptional Correlates of Hub Connectivity in Neural Networks

Connections in nervous systems are disproportionately concentrated on a small subset of neural elements that act as network hubs. Hubs have been found across different species and scales ranging from C. elegans to mouse, rat, cat, macaque, and human, suggesting a role for genetic influences. The recent availability of brain-wide gene expression atlases provides new opportunities for mapping the transcriptional correlates of large-scale network-level phenotypes. Here we review studies that use these atlases to investigate gene expression patterns associated with hub connectivity in neural networks and present evidence that some of these patterns are conserved across species and scales.

A-to-I RNA editing - immune protector and transcriptome diversifier

Modifications of RNA affect its function and stability. RNA editing is unique among these modifications because it not only alters the cellular fate of RNA molecules but also alters their sequence relative to the genome. The most common type of RNA editing is A-to-I editing by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes. Recent transcriptomic studies have identified a number of 'recoding' sites at which A-to-I editing results in non-synonymous substitutions in protein-coding sequences. Many of these recoding sites are conserved within (but not usually across) lineages, are under positive selection and have functional and evolutionary importance. However, systematic mapping of the editome across the animal kingdom has revealed that most A-to-I editing sites are located within mobile elements in non-coding parts of the genome. Editing of these non-coding sites is thought to have a critical role in protecting against activation of innate immunity by self-transcripts. Both recoding and non-coding events have implications for genome evolution and, when deregulated, may lead to disease. Finally, ADARs are now being adapted for RNA engineering purposes.

Explaining Pathogenicity of Congenital Zika and Guillain-Barré Syndromes: Does Dysregulation of RNA Editing Play a Role?

Previous studies of Zika virus (ZIKV) pathogenesis have focused primarily on virus-driven pathology and neurotoxicity, as well as host-related changes in cell proliferation, autophagy, immunity, and uterine function. It is now hypothesized that ZIKV pathogenesis arises instead as an (unintended) consequence of host innate immunity, specifically, as the side effect of an otherwise well-functioning machine. The hypothesis presented here suggests a new way of thinking about the role of host immune mechanisms in disease pathogenesis, focusing on dysregulation of post-transcriptional RNA editing as a candidate driver of a broad range of observed neurodevelopmental defects and neurodegenerative clinical symptoms in both infants and adults linked with ZIKV infections. The authors collect and synthesize existing evidence of ZIKV-mediated changes in the expression of adenosine deaminases acting on RNA (ADARs), known links between abnormal RNA editing and pathogenesis, as well as ideas for future research directions, including potential treatment strategies.

Brain region-specific alterations of RNA editing in PDE8A mRNA in suicide decedents

Phosphodiesterases (PDE) are key modulators of signal transduction and are involved in inflammatory cell activation, memory and cognition. There is a two-fold decrease in the expression of phosphodiesterase 8A (PDE8A) in the temporal cortex of major depressive disorder (MDD) patients. Here, we studied PDE8A mRNA-editing profile in two architectonically distinct neocortical regions in a clinically well-characterized cohort of age- and sex-matched non-psychiatric drug-free controls and depressed suicide decedents. By using capillary electrophoresis single-stranded conformational polymorphism (CE-SSCP), a previously validated technique to identify A-to-I RNA modifications, we report the full editing profile of PDE8A in the brain, including identification of two novel editing sites. Editing of PDE8A mRNA displayed clear regional difference when comparing dorsolateral prefrontal cortex (BA9) and anterior cingulate cortex (BA24). Furthermore, we report significant intra-regional differences between non-psychiatric control individuals and depressed suicide decedents, which could discriminate the two populations. Taken together, our results (i) highlight the importance of immune/inflammatory markers in major depressive disorder and suicide and (ii) establish a direct relationship between A-to-I RNA modifications of peripheral markers and A-to-I RNA editing-related modifications in brain. This work provides the first immune response-related brain marker for suicide and could pave the way for the identification of a blood-based biomarker that predicts suicidal behavior.

Multiple Innovations in Genetic and Epigenetic Mechanisms Cooperate to Underpin Human Brain Evolution

Our knowledge of how the human brain differs from those of other species in terms of evolutionary adaptations and functionality is limited. Comparative genomics reveal valuable insight, especially the expansion of human-specific noncoding regulatory and repeat-containing regions. Recent studies add to our knowledge of evolving brain function by investigating cellular mechanisms such as protein emergence, extensive sequence editing, retrotransposon activity, dynamic epigenetic modifications, and multiple noncoding RNA functions. These findings present an opportunity to combine newly discovered genetic and epigenetic mechanisms with more established concepts into a more comprehensive picture to better understand the uniquely evolved human brain.

Adenosine-to-Inosine RNA Editing Within Corticolimbic Brain Regions Is Regulated in Response to Chronic Social Defeat Stress in Mice

Adenosine-to-inosine (A-to-I) RNA editing is a co-/posttranscriptional modification of double-stranded RNA, catalyzed by the adenosine deaminase acting on RNA (ADAR) family of enzymes, which results in recognition of inosine as guanosine by translational and splicing machinery causing potential recoding events in amino acid sequences. A-to-I editing is prominent within brain-specific transcripts, and dysregulation of editing at several well-studied loci (e.g., Gria2, Htr2c) has been implicated in acute and chronic stress in rodents as well as neurological (e.g., Alzheimer's) and psychopathological disorders such as schizophrenia and major depressive disorder. However, only a small fraction of recoding sites has been investigated within the brain following stress, and our understanding of the role of RNA editing in transcriptome regulation following environmental stimuli remains poorly understood. Thus, we aimed to investigate A-to-I editing at hundreds of loci following chronic social defeat stress (CSDS) in mice within corticolimbic regions responsive to chronic stress regulation. Adult male mice were subjected to CSDS or control conditions for 21 days and dynamic regulation of A-to-I editing was investigated 2 and 8 days following the final defeat within both the medial prefrontal cortex (mPFC) and basolateral amygdala (BLA). Employing a targeted resequencing approach, which utilizes microfluidics-based multiplex polymerase chain reaction (PCR) coupled with next-generation sequencing, we analyzed A-to-I editing at ∼100 high-confidence editing sites within the mouse brain. CSDS resulted in acute regulation of transcripts encoding several ADAR enzymes, which normalized 8 days following the final defeat and was specific for susceptible mice. In contrast, sequencing analysis revealed modest and dynamic regulation of A-to-I editing within numerous transcripts in both the mPFC and BLA of resilient and susceptible mice at both 2 and 8 days following CSDS with minimal overlap between regions and time points. Editing within the Htr2c transcript and relative abundance of Htr2c messenger RNA (mRNA)variants were also observed within the BLA of susceptible mice 2 days following CSDS. These results indicate dynamic RNA editing within discrete brain regions following CSDS in mice, further implicating A-to-I editing as a stress-sensitive molecular mechanism within the brain of potential relevance to resiliency and susceptibility to CSDS.

RNA Editors, Cofactors, and mRNA Targets: An Overview of the C-to-U RNA Editing Machinery and Its Implication in Human Disease

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.

Genome-wide analysis of consistently RNA edited sites in human blood reveals interactions with mRNA processing genes and suggests correlations with cell types and biological variables

BACKGROUND

A-to-I RNA editing is a co-/post-transcriptional modification catalyzed by ADAR enzymes, that deaminates Adenosines (A) into Inosines (I). Most of known editing events are located within inverted ALU repeats, but they also occur in coding sequences and may alter the function of encoded proteins. RNA editing contributes to generate transcriptomic diversity and it is found altered in cancer, autoimmune and neurological disorders. Emerging evidences indicate that editing process could be influenced by genetic variations, biological and environmental variables.

RESULTS

We analyzed RNA editing levels in human blood using RNA-seq data from 459 healthy individuals and identified 2079 sites consistently edited in this tissue. As expected, analysis of gene expression revealed that ADAR is the major contributor to editing on these sites, explaining ~ 13% of observed variability. After removing ADAR effect, we found significant associations for 1122 genes, mainly involved in RNA processing. These genes were significantly enriched in genes encoding proteins interacting with ADARs, including 276 potential ADARs interactors and 9 ADARs direct partners. In addition, our analysis revealed several factors potentially influencing RNA editing in blood, including cell composition, age, Body Mass Index, smoke and alcohol consumption. Finally, we identified genetic loci associated with editing levels, including known ADAR eQTLs and a small region on chromosome 7, containing LOC730338, a lincRNA gene that appears to modulate ADARs mRNA expression.

CONCLUSIONS

Our data provides a detailed picture of the most relevant RNA editing events and their variability in human blood, giving interesting insights on potential mechanisms behind this post-transcriptional modification and its regulation in this tissue.

Computational approaches for detection and quantification of A-to-I RNA-editing

Adenosine deaminases that act on RNA (ADARs) catalyze adenosine-to-inosine (A-to-I) RNA editing in double-stranded RNA. Such editing is important for protection against false activation of the immune system, but also confers plasticity on the transcriptome by generating several versions of a transcript from a single genomic locus. Recently, great efforts were made in developing computational methods for detecting editing events directly from RNA-sequencing (RNA-seq) data. These efforts have led to an improved understanding of the makeup of the editome in various genomes. Here we review recent advances in editing detection based on the data available to the researcher, with emphasis on the principles underlying the various methods and the limitations they were designed to overcome. We also discuss the available various methods for analyzing and quantifying editing levels. This review collects and organizes the available approaches for analyzing RNA editing and discuss the current status of the different A-to-I detection methods with possible directions for extending these approaches.

ADAR2-dependent A-to-I RNA editing in the extracellular linear and circular RNAs

Currently, no reliable biomarkers of amyotrophic lateral sclerosis (ALS) exist. In sporadic ALS, RNA editing at the glutamine/arginine site of GluA2 mRNA is specifically reduced in the motor neurons due to the downregulation of adenosine deaminase acting on RNA 2 (ADAR2). Furthermore, TDP-43 pathology, the pathological hallmark of ALS, is observed in the ADAR2-lacking motor neurons in ALS patients and conditional ADAR2 knockout mice, suggesting a pivotal role of ADAR2 downregulation in the ALS pathogenesis. Extracellular RNAs were shown to represent potential disease biomarkers and the editing efficiencies at their ADAR2-dependent sites may reflect cellular ADAR2 activity, suggesting that these RNAs isolated from the body fluids may represent the biomarkers of ALS. We searched for ADAR2-dependent sites in the mouse motor neurons and human-derived cultured cells and found 10 sites in five host RNAs expressed in SH-SY5Y cells and their culture medium. Of these, the arginine/glycine site of SON mRNA was newly identified as an ADAR2-dependent site. Furthermore, we detected a circular RNA with an ADAR2-dependent site in the SH-SY5Y cells and their culture medium. Therefore, the changes in the editing efficiencies at the identified host RNA sites isolated from the body fluids may represent potential biomarkers of ALS.

Organ-wide profiling in mouse reveals high editing levels of Filamin B mRNA in the musculoskeletal system

Adenosine to inosine RNA editing in protein-coding messenger RNAs (mRNAs) potentially leads to changes in the amino acid composition of the encoded proteins. The mRNAs encoding the ubiquitously expressed actin-crosslinking proteins Filamin A and Filamin B undergo RNA editing leading to a highly conserved glutamine to arginine exchange at the identical position in either protein. Here, by targeted amplicon sequencing we analysed the RNA editing of Filamin B across several mouse tissues during post-natal development. We find highest filamin B editing levels in skeletal muscles, cartilage and bones, tissues where Filamin B function seems most important. Through the analysis of Filamin B editing in mice deficient in either ADAR1 or 2, we identified ADAR2 as the enzyme responsible for Filamin B RNA editing. We show that in neuronal tissues Filamin B editing drops in spliced transcripts indicating regulated maturation of edited transcripts. We show further that the variability of Filamin B editing across several organs correlates with its mRNA expression.