Targeting abnormal dysregulation of adenosine-to-inosine deamination by ADAR enzymes offers a promising therapeutic strategy in cancer research. However, the development of effective inhibitors is impeded by the incomplete structural information on ADAR1 complexes. In this study, we employ a combination of computational 3D modeling and high-speed atomic force microscopy to elucidate the atomic and molecular dynamics of ADAR1. Two distinct interface regions (IFx and IFy) on the surface of the deaminase domain and oligomerization structural models are identified. Single-molecule-level insights into the structural dynamics of ADAR1 reveal the oligomerization of ADAR1 monomers through the self-assembly of deaminase domains. In the presence of the substrate dsRNA, the N-terminal region, including RNA-binding domains, of ADAR1 dimer exhibits a controlled flexible conformation and promotes a stable dimeric interaction with dsRNA for RNA editing. These findings provide the basis for the development of targeted inhibitors to regulate ADAR1 activity in therapeutic applications.

Adenosine-to-inosine (A-to-I) RNA editing is a prevalent RNA modification essential for cell survival. The process is catalyzed by the adenosine deaminase acting on RNA (ADAR) enzyme family that converts adenosines in double-stranded RNAs (dsRNAs) into inosines, which are read as guanosines during translation. Deep sequencing has helped to reveal that A-to-I editing occurs across various types of RNAs, affecting their functions. RNA editing detection is now so sophisticated that we can achieve a high level of accuracy and sensitivity to identify low-abundance edited events. Consequently, A-to-I editing has been implicated in various biological processes, including immune and stress responses, cancer progression, and stem cell fate determination. In particular, a crucial role for this process has been recently reported in hematopoietic cell development and hematologic malignancy progression. Results from genetic mouse models have demonstrated the impact of ADARs' catalytic activity on hematopoietic cells, complemented by insights from human cell studies. Meanwhile, clinical studies have implicated ADAR enzymes and RNA editing events in hematologic malignancies and highlighted their potential as prognostic indicators. In this review, we outline the regulatory mechanisms of RNA editing in both normal hematopoiesis and hematologic malignancies. We then speculate on how targeting ADAR expression and site-specific RNA substrates might serve as a therapeutic avenue for affected patients.

The human genome encodes 19 adenosine and cytidine deaminase genes, classified as A-to-I versus C-to-U editors. A-to-I editors have been widely identified as a promising therapeutic target in various cancers. Conversely, the investigation into C-to-U editors is relatively limited. This study evaluated RNA-editing genes in prostate cancer (PCa). Notably, the APOBEC3 genes are clustered in terms of their chromosomal locations, and their transcriptional changes exhibit significant positive correlations in both primary PCa and castration-resistant prostate cancer (CRPC). One member of this family, APOBEC3C, is demonstrated here as an androgen receptor (AR)-repressed gene. Consistently, APOBEC3 loci are epigenetically inhibited in PCa progression, with APOBEC3C level lower in PSA-high patients. APOBEC3C-low PCa cohorts exhibit increased resistance to Abiraterone and Enzalutamide. Clinicopathological profiling further confirmed APOBEC3C downregulation along PCa progression to advanced phases (grade IV/V, stage III-IV, and pathological stage T3-4), underscoring its prognostic value. Additionally, APOBEC3C expression inversely correlates with PCa relapse and mortality, and low APOBEC3C levels are linked to unfavorable survival. Notably, integrated analyses identified APOBEC3C as the sole RNA-editing gene with significance in both differential expression and PCa prognosis, and APOBEC3C had the best diagnostic performance among 19 genes. Our efforts provide a foundation for further RNA editors research in PCa diagnosis and therapy, and grant APOBEC3C as a candidate tumor suppressor.

Epitranscriptomic changes in the transcripts of cancer related genes could modulate protein levels. RNA editing, particularly A-to-I(G) editing catalyzed by ADAR1, has been implicated in cancer progression. RNA editing events in the 3' untranslated region (3'UTR) can regulate mRNA stability, localization, and translation, underscoring the importance of exploring their impact in cancer. Here, we performed an in silico analysis to detect breast cancer enriched RNA editing sites using the TCGA breast cancer RNA-seq dataset. Notably, the majority of differential editing events mapped to 3' untranslated regions (3'UTRs). We confirmed A-to-I(G) editing in the 3'UTRs of MDM2 (Mouse Double Minute 2 homolog), GINS1 (GINS Complex Subunit 1), and F11R (Junctional Adhesion Molecule A) in breast cancer cells. RNA immunoprecipitation with ADAR1 antibody confirmed the interaction between ADAR1 and MDM2, GINS1, and F11R 3'UTRs. ADAR1 knockdown revealed decreased editing levels, establishing ADAR1 as the editing enzyme. A reporter assay for MDM2, an oncogene overexpressed mostly in luminal breast cancers, demonstrated that RNA editing enhances protein expression, in agreement with reduced MDM2 protein levels in ADAR1 knockdown cells. Further exploration into the mechanisms of 3'UTR editing events revealed an interaction between ADAR1 and CSTF2, a core component of the polyadenylation machinery, as identified through biotin-based proximity labeling mass spectroscopy, and co-immunoprecipitation experiments. Furthermore, CSTF2 knockdown reduced both ADAR1 and MDM2 protein levels. Our findings highlight implications for MDM2 regulation by ADAR1-dependent 3'UTR RNA editing and present an interplay between RNA editing on 3'UTRs and the mRNA polyadenylation machinery. These results improve our understanding of ADAR1's role in cancer-associated 3' UTR RNA editing and its potential as a therapeutic target.

Although the role of adenosine-to-inosine RNA editing (ATIRE) has gained widespread attention in multiple cancers, its predictive role in hepatocellular carcinoma (HCC) remains little known. We aimed to establish a predicting signature based on ATIRE for the prognosis of HCC.

A total of 200 HCC patients with survival data and ATIRE profiles from The Cancer Genome Atlas (TCGA) database were divided into training (n = 140) and validation (n = 60) cohorts. Survival-related ATIRE sites were identified by the least absolute shrinkage and selection operator algorithm. ATIRE-based risk score was then generated with these ATIRE sites. Cox proportional hazards regression was employed to construct the ATIRE-based nomogram signature. The receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of the signature. Harrell's C-index and calibration plot was utilized to evaluate the significant prognostic factors.

Nine ATIRE sites were screened to establish the ATIRE risk score, and it was found to be associated with prognosis of HCC. Survival analysis revealed that higher ATIRE-based risk scores were significantly associated with worse overall survival (OS) in both the training dataset (p < 0.001) and the validation dataset (p = 0.011), as well as in the combined dataset (p < 0.001). The ROC curve displayed a good predictive efficiency of the risk score regarding 1-year, 2-year, and 3-year OS. Furthermore, ATIRE sites were significantly correlated with the expression of host genes and were likely to be involved in certain cancer-related pathways.

Our findings provided a novel ATIRE-based nomogram, which could serve as a potential tool for predicting HCC prognosis.

RNA-DNA differences (RDDs) challenge the traditional view of RNA as a faithful copy of DNA, arising through RNA editing, transcriptional errors, and oxidative damage. Reactive oxygen species (ROS) play a central role, inducing lesions like 8-oxo-guanine that compromise transcription and translation, leading to dysfunctional proteins. This review explores the biochemical basis of RDDs, their exacerbation under oxidative stress, and their dual roles in cellular adaptation and disease. RDDs contribute to genomic instability and are implicated in cancers, neurodegenerative disorders, and autoimmune diseases, while also driving phenotypic diversity. Drawing on terrestrial and spaceflight studies, we highlight the intersection of oxidative stress, RDD formation, and cellular dysfunction, proposing innovative mitigation approaches. Advancements in RDD detection and quantification, along with ROS management therapies, offer new avenues to restore cellular homeostasis and promote resilience. By positioning RDDs as a hallmark of genomic entropy, this review underscores the limits of biological adaptation. Furthermore, the prevalence of guanine-rich codons in antioxidant genes increases their susceptibility to ROS-induced oxidative lesions, linking redox stress, genomic instability, and constrained adaptation. These insights have profound implications for understanding aging, disease progression, and adaptive mechanisms in both terrestrial and space environments.

RNA editing is a crucial post-transcriptional modification that alters the transcriptome and proteome and affects many cellular processes, including splicing, microRNA specificity, stability of RNA molecules, and protein structure. Enzymes from the adenosine deaminase acting on RNA (ADAR) and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) protein families mediate RNA editing and can alter a variety of non-coding and coding RNAs, including all regions of mRNA molecules, leading to tumor development and progression. This review provides novel insights into the potential use of RNA editing parameters, such as editing levels, expression of ADAR and APOBEC genes, and specifically edited genes, as biomarkers for cancer progression, distinguishing it from previous studies that focused on isolated aspects of RNA editing mechanisms. The methodological section offers clues to accelerate high-throughput analysis of RNA or DNA sequencing data for the identification of RNA editing events.

Endogenous, long double-stranded RNA (dsRNA) can resemble viral dsRNA and be recognized by cytosolic dsRNA sensors, triggering autoimmunity. Genetic studies of rare, inherited human diseases and experiments using mouse models have established the importance of adenosine-to-inosine RNA editing by the enzyme adenosine deaminase acting on RNA 1 (ADAR1) as a critical safeguard against autoinflammatory responses to cellular dsRNA. More recently, human genetic studies have revealed that dsRNA editing and sensing mechanisms are involved in common inflammatory diseases, emphasizing the broader role of dsRNA in modulating immune responses and disease pathogenesis. These findings have highlighted the therapeutic potential of targeting dsRNA editing and sensing, as exemplified by the emergence of ADAR1 inhibition in cancer therapy.

The double-stranded RNA editing enzyme ADAR1 connects two forms of genetic programming, one based on codons and the other on flipons. ADAR1 recodes codons in pre-mRNA by deaminating adenosine to form inosine, which is translated as guanosine. ADAR1 also plays essential roles in the immune defense against viruses and cancers by recognizing left-handed Z-DNA and Z-RNA (collectively called ZNA). Here, we review various aspects of ADAR1 biology, starting with codons and progressing to flipons. ADAR1 has two major isoforms, with the p110 protein lacking the p150 Zα domain that binds ZNAs with high affinity. The p150 isoform is induced by interferon and targets ALU inverted repeats, a class of endogenous retroelement that promotes their transcription and retrotransposition by incorporating Z-flipons that encode ZNAs and G-flipons that form G-quadruplexes (GQ). Both p150 and p110 include the Zβ domain that is related to Zα but does not bind ZNAs. Here we report strong evidence that Zβ binds the GQ that are formed co-transcriptionally by ALU repeats and within R-loops. By binding GQ, ADAR1 suppresses ALU-mediated alternative splicing, generates most of the reported nonsynonymous edits and promotes R-loop resolution. The recognition of the various alternative nucleic acid conformations by ADAR1 connects genetic programming by flipons with the encoding of information by codons. The findings suggest that incorporating G-flipons into editmers might improve the therapeutic editing efficacy of ADAR1.

A-to-I RNA editing is a pervasive mechanism in the human genome that affects the regulation of gene expression and is closely associated with the pathogenesis of numerous diseases. This study elucidates the regulatory mechanism of A-to-I edited miR-1304-3p in esophageal squamous cell carcinoma (ESCC). Western blot, immunohistochemistry, and RT-qPCR assays were employed to quantify protein and mRNA expression. Colony formation, Edu, wound healing, and Transwell assays were applied to determine miRNA function. Glycolysis was assessed using glucose uptake and lactate production assay. A dual-luciferase reporter assay confirmed the downstream targets of miRNA, and a xenograft assay demonstrated the efficacy of the miRNA. The A-to-I RNA editing level of miR-1304-3p was observed to increase in KYSE180 and KYSE140 ESCC cells following ADAR1 treatment. Following A-to-I editing, the function of miR-1304-3p in ESCC progression underwent a reversal, shifting from carcinogenic to inhibitory. Wild-type (WT) miR-1304-3p targets IRS1, whereas the edited version targets ROR2. The WT miR-1304-3p, but not the edited version, suppressed the expression and tumor-suppressive effect of IRS1 in ESCC. Conversely, ROR2, a specific downstream target of the edited miR-1304-3p, acted as a tumor promoter in ESCC. Furthermore, A-to-I editing of miR-1304-3p can inhibit glycolysis and inactivate the Wnt5a/ROR2 signaling pathway in ESCC. A-to-I RNA editing alters the function of miR-1304-3p in ESCC by changing its target gene. The edited miR-1304-3p hinders the development of ESCC by inhibiting glycolysis and inactivating the Wnt5a/ROR2 signaling pathway.

Adenosine-to-inosine (A-to-I) RNA editing is a key post-transcriptional modification that influences gene expression and various cellular processes. Advances in sequencing technologies have greatly contributed to the identification of A-to-I editing sites, providing insights into their distribution across coding and non-coding regions. These developments have facilitated the discovery of functionally relevant editing events and have advanced the understanding of their biological roles. This review presents the evolution of methodologies for RNA editing detection and examines recent advances, including chemically-assisted, enzyme-assisted, and quantitative approaches. By evaluating these techniques, we aim to help researchers select the most effective tools for investigating RNA editing and its broader implications in health and disease.

Editome Disease Knowledgebase (EDK) is a curated resource of knowledge between RNA editome and human diseases. Since its first release in 2018, a number of studies have discovered previously uncharacterized editome-disease associations and generated an abundance of RNA editing datasets. Thus, it is desirable to make significant updates for EDK by incorporating more editome-disease associations as well as their related editing profiles.

Here, we present EDK v2.0, an updated version of editome-disease associations based on both literature curation and integrative analysis. EDK v2.0 incorporates a curated collection of 1097 editome-disease associations involving 115 diseases from 321 publications. Meanwhile, based on a standardized pipeline, EDK v2.0 provides RNA editing profiles from 48 datasets covering 2536 samples across 55 diseases. Through differential analysis on RNA editing, it further identifies a total of 7190 differential edited genes and 86 242 differential editing sites (DESs), leading to 266 339 DES-disease associations. Moreover, a curated list of 28 160 cis-RNA editing QTL associations, 458 187 DES-RNA binding protein associations, and 21 DES-RNA secondary structure associations are annotated and added to EDK v2.0. Additionally, it is equipped with a series of user-friendly tools to facilitate RNA editing online analysis.

https://ngdc.cncb.ac.cn/edk/.

Triple-negative breast cancer (TNBC), lacking expression of estrogen, progesterone, and HER2 receptors, is aggressive and lacks targeted treatment options. An RNA editing enzyme, adenosine deaminase acting on RNA 1 (ADAR1), has been shown to play important roles in TNBC tumorigenesis. We posit that ADAR1 functions as a homeostatic factor protecting TNBC from internal and external pressure, including metabolic stress. We tested the hypothesis that the iron- dependent cell death pathway, ferroptosis, is a ADAR1-protected metabolic vulnerability in TNBC by showing that ADAR1 knockdown sensitizes TNBC cells to GPX4 inhibitors. By performing single-reaction monitoring-based liquid chromatography coupled to mass spectrometry (LC-MS) to measure intracellular lipid contents, we showed that ADAR1 loss increased the abundance of polyunsaturated fatty acid phospholipids (PUFA-PL), of which peroxidation is the primary driver of ferroptosis. Transcriptomic analyses led to the discovery of the proto-oncogene MDM2 contributing to the lipid remodeling in TNBC upon ADAR1 loss. A phenotypic drug screen using a ferroptosis-focused library was performed to identify FDA- approved cobimetinib as a drug-repurposing candidate to synergize with ADAR1 loss to suppress TNBC tumorigenesis. By demonstrating that ADAR1 regulates the metabolic fitness of TNBC through desensitizing ferroptosis, we aim to leverage this metabolic vulnerability to inform basic, pre-clinical, and clinical studies to develop novel therapeutic strategies for TNBC.

Despite the remarkable resistance of the nucleic acid phosphodiester backbone to degradation affording genetic stability, the P-O bond must be broken during DNA repair and RNA metabolism, among many other critical cellular processes. Nucleases are powerful enzymes that can enhance the uncatalyzed rate of phosphodiester bond cleavage by up to ∼1017-fold. Despite the most well accepted hydrolysis mechanism involving two metals (MA2+ to activate a water nucleophile and MB2+ to stabilize the leaving group), experimental evidence suggests that some nucleases can use a single metal to facilitate the chemical step, a controversial concept in the literature. The present perspective uses the case studies of four nucleases (I-PpoI, APE1, and bacterial and human EndoV) to highlight how computational approaches ranging from quantum mechanical (QM) cluster models to molecular dynamics (MD) simulations and combined quantum mechanics-molecular mechanics (QM/MM) calculations can reveal the atomic level details necessary to understand how a nuclease can use a single metal to facilitate this difficult chemistry. The representative nucleases showcase how different amino acid residues (e.g., histidine, aspartate) can fulfill the role of the first metal (MA2+) in the two-metal-mediated mechanisms. Nevertheless, differences in active site architectures afford diversity in the single-metal-mediated mechanism in terms of the metal-substrate coordination, the role of the metal, and the identities of the general acid and base. The greater understanding of the catalytic mechanisms of nucleases obtained from the body of work reviewed can be used to further explore the progression of diseases associated with nuclease (mis)activity and the development of novel nuclease applications such as disease diagnostics, gene engineering, and therapeutics.

Alzheimer's disease (AD) is the leading dementia among the elderly with complex origins. Despite extensive investigation into the AD-associated protein-coding genes, the involvement of noncoding RNAs (ncRNAs) and posttranscriptional modification (PTM) in AD pathogenesis remains unclear. Here, we comprehensively characterized the landscape of ncRNAs and PTM events in 1460 samples across six brain regions sourced from the Mount Sinai/JJ Peters VA Medical Center Brain Bank Study and Mayo cohorts, encompassing 33,321 long ncRNAs, 92,897 enhancer RNAs, 53,763 alternative polyadenylation events, and 900,221 A-to-I RNA editing events. We additionally identified 25,351 aberrantly expressed ncRNAs and altered PTM events associated with AD traits and further identified the corresponding protein-coding genes to construct regulatory networks. Furthermore, we developed a user-friendly data portal, ADatlas, facilitating users in exploring our results. Our study aims to establish a comprehensive data platform for ncRNAs and PTMs in AD to advance related research.

Exactly two decades ago, the ability to use high-throughput RNA sequencing technology to identify sites of editing by ADARs was employed for the first time. Since that time, RNA sequencing has become a standard tool for researchers studying RNA biology and led to the discovery of RNA editing sites present in a multitude of organisms, across tissue types, and in disease. However, transcriptome-wide sequencing is not without limitations. Most notably, RNA sequencing depth of a given transcript is correlated with expression, and sequencing depth impacts the ability to robustly detect RNA editing events. This chapter focuses on a method for enrichment of low-abundance transcripts that can facilitate more efficient sequencing and detection of RNA editing events. An important note is that while we describe aspects of the protocol important for capturing intron-containing transcripts, this probe-based enrichment method could be easily modified to assess editing within any low-abundance transcript. We also provide some perspectives on the current limitations as well as important future directions for expanding this technology to gain more insights into how RNA editing can impact transcript diversity.

Adenosine deaminase acting on RNA 1 (ADAR1) plays an essential role in the development of malignancies by modifying the expression of different oncogenes. ADAR1 presents three distinct activities: adenosine-to-inosine RNA editing, modulating IFN pathways, and response to cellular stress factors. Following stressors such as heat shock, ADAR1p110 isoform relocates from the nucleus to the cytoplasm, where it suppresses RNA degradation which leads to the arrest of apoptosis and cell survival. In this study, we assessed the expression of ADAR1 across different cancer cell lines. We revealed that the presence of ADAR1 varies between cells of different origins and that a high transcript level does not reflect protein abundance. Additionally, we subjected cells to a heat shock in order to evaluate how cellular stress factors affect the expression of ADAR1. Our results indicate that ADAR1 transcript and protein levels are relatively stable and do not change under heat shock in examined cell lines. This research lays a groundwork for future directions on ADAR1-related studies suggesting in which types of cancer ADAR1 may be a promising target for novel therapeutic approaches.

Adenosine-to-inosine (A-to-I) editing, catalyzed by adenosine deaminases acting on RNA (ADARs), is a prevalent post-transcriptional modification that is vital for numerous biological functions. Given that this modification impacts global gene expression, RNA localization, and innate cellular immunity, dysregulation of A-to-I editing has unsurprisingly been linked to a variety of cancers and other diseases. However, our current understanding of the underpinning mechanisms that connect dysregulated A-to-I editing and disease processes remains limited. Widely used methods require RNA extraction and pooling that ultimately erases subcellular localization and cell-to-cell variation, which may be critical to understanding misregulation. To overcome these challenges, we recently developed Endonuclease V Immunostaining Assay (EndoVIA) to selectively detect and visualize A-to-I edited RNA in situ. In this chapter, we describe in detail how to prepare cell samples, stain A-to-I edited transcripts with EndoVIA, quantify global inosine abundance, and visualize the subcellular localization of inosine-containing RNAs at the single molecule level.

The role of adenosine deaminase acting on RNA1 (ADAR1) in colorectal cancer (CRC) is poorly understood. This study investigated the roles and underlying molecular mechanisms of ADAR1 and its isoforms, explored the correlations between ADAR1 expression and the immune microenvironment and anticancer drug sensitivity, and examined the potential synergy of using ADAR1 expression and clinical parameters to determine the prognosis of CRC patients. CRC samples showed significant upregulation of ADAR1, and high ADAR1 expression was correlated with poor prognosis. Silencing ADAR1 inhibited the proliferation, invasion, and migration of CRC cells and induced ferroptosis by suppressing FAK/AKT activation, and the results of rescue assays were consistent with these mechanisms. Both ADAR1-p110 and ADAR1-p150 were demonstrated to regulate the FAK/AKT pathway, with ADAR1-p110 playing a particularly substantial role. In evaluating the prognosis of CRC patients, combining ADAR1 expression with clinical parameters produced a substantial synergistic effect. The in vivo tumorigenesis of CRC was significantly inhibited by silencing ADAR1. Furthermore, ADAR1 expression was positively correlated with tumor mutational burden (TMB) and microsatellite status (p < 0.05), indicating that ADAR1 plays a complex role in CRC immunotherapy. In conclusion, ADAR1 plays oncogenic roles in CRC both in vitro and in vivo, potentially by inhibiting ferroptosis via downregulation of the FAK/AKT pathway. Thus, ADAR1 serves as a potential prognostic biomarker and a promising target for CRC therapy.

Lower-grade glioma (LGG) refers to WHO grade 2 and 3 gliomas. Surgery combined with radiotherapy and chemotherapy can significantly improve the prognosis of LGG patients, but tumor progression is still unavoidable. As a form of posttranscriptional regulation, RNA editing (RE) has been reported to be involved in tumorigenesis and progression and has been intensively studied recently.

Survival data and RE data were subjected to univariate and multivariate Cox regression analysis and lasso regression analysis to establish an RE risk score model. A nomogram combining the risk score and clinicopathological features was built to predict the 1-, 3-, and 5-year survival probability of patients. The relationship among ADAR1, SOD2 and SOAT1 was verified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) RESULTS: A risk model associated with RE was constructed and patients were divided into different risk groups based on risk scores. The model demonstrated strong prognostic capability, with the area under the ROC curve (AUC) values of 0.882, 0.938, and 0.947 for 1-, 3-, and 5-year survival predictions, respectively. Through receiver operating characteristic curve (ROC) curves and calibration curves, it was verified that the constructed nomogram had better performance than age, grade, and risk score in predicting patient survival probability. Apart from this functional analysis, the results of correlation analyses between risk differentially expressed genes (RDEGs) and RE help us to understand the underlying mechanism of RE in LGG. ADAR may regulate the expression of SOD2 and SOAT1 through gene editing.

In conclusion, this study establishes a novel and accurate 17-RE model and a nomogram for predicting the survival probability of LGG patients. ADAR may affect the prognosis of glioma patients by influencing gene expression.

Dysregulation of adenosine-to-inosine (A-to-I) RNA editing has been implicated in cancer progression. However, a comprehensive understanding of how A-to-I RNA editing is incorporated into miRNA regulation to modulate gene expression in cancer remains unclear, given the lack of effective identification methods. To this end, we introduced an information theory-based algorithm named REMR to systematically identify 12,006 A-to-I RNA editing-mediated miRNA regulatory triplets (RNA editing sites, miRNAs, and genes) across ten major cancer types based on multi-omics profiling data from The Cancer Genome Atlas (TCGA). Through analyses of functional enrichment, transcriptional regulatory networks, and protein-protein interaction (PPI) networks, we showed that RNA editing-mediated miRNA regulation potentially affects critical cancer-related functions, such as apoptosis, cell cycle, drug resistance, and immunity. Furthermore, triplets can serve as biomarkers for classifying cancer subtypes with distinct prognoses or drug responses, highlighting the clinical relevance of such regulation. In addition, an online resource (http://www.jianglab.cn/REMR/) was constructed to support the convenient retrieval of our findings. In summary, our study systematically dissected the RNA editing-mediated miRNA regulations, thereby providing a valuable resource for understanding the mechanism of RNA editing as an epitranscriptomic regulator in cancer.

A-to-I RNA editing is an RNA modification that alters the RNA sequence relative to the its genomic blueprint. It is catalyzed by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes, and contributes to the complexity and diversification of the proteome. Advancement in the study of A-to-I RNA editing has been facilitated by computational approaches for accurate mapping and quantification of A-to-I RNA editing based on sequencing data. In this chapter we review some of the main computational approaches currently used, describe potential hurdles, challenges and pitfalls, and discuss possible ways to mitigate them.

Retrotransposons are self-replicating genomic elements that move from one genomic location to another using a "copy-and-paste" method involving RNA intermediaries. One family of retrotransposon that has garnered considerable attention for its association with age-related diseases and anti-aging interventions is the short interspersed nuclear elements (SINEs). This review summarizes current knowledge on the roles of SINEs in aging processes and therapies. To underscore the significant research on the involvement of SINEs in aging-related diseases, we commence by outlining compelling evidence on the classification and mechanism, highlighting implications in age-related phenomena. The intricate relationship between SINEs and diseases such as neurodegenerative disorders, heart failure, high blood pressure, atherosclerosis, type 2 diabetes mellitus, osteoporosis, visual system dysfunctions, and cancer is explored, emphasizing their roles in various age-related diseases. Recent investigations into the anti-aging potential of SINE-targeted treatments are examined, with particular attention to how SINE antisense RNA mitigate age-related alterations at the cellular and molecular levels, offering insights into potential therapeutic targets for age-related pathologies. This review aims to compile the most recent advances on the multifaceted roles of SINE retrotransposons in age-related diseases and anti-aging interventions, providing valuable insights into underlying mechanisms and therapeutic avenues for promoting healthy aging.

ADAR1 (Adenosine deaminase action on RNA1) is involved in post-transcriptional RNA editing. ADAR1 mutations have been identified in many cancers but its role in tumor formation is still not well understood. Here we used available cancer genomes deposited on CSOMIC and cBioPortal to identify and characterize mutations and changes in ADAR1 expression in cancer cells. We identify several high frequency substitutions including one at R767 which is located in one of the dsRNA interacting domains. In silico protein structure analysis suggest the R767 mutations affect the protein stability and are likely to destabilize interaction with dsRNA. Gene expression analysis shows that in samples with under-expressed ADAR1, there is a statistically significant increase in expression of BLCAP (Bladder Cancer Associated Protein). Although BLCAP was initially identified in bladder cancers, more recent evidence shows that it is a tumor suppressor and BLCAP mutations have been detected in many cancer cells. Epistatic analysis using the cBioPortal mutual exclusivity calculator for the TCGA pan-cancer data shows that co-mutations between ADAR1 and other genes regulated by it are likely in cancer cells except for PTEN, AKT1 and BLCAP. This suggests that when ADAR1 function is impaired, PTEN, AKT1 and BLCAP become essential for survival of cancer cells. We also identified several samples with high mutation burden between ADAR1 and other genes regulated primarily in endometrial cancers. Finally, we show that the deaminase domain is highly conserved in metazoans and mutations within conserved residues do occur in human cancers suggesting that destabilization of the enzyme function is contributing to cancer development.

RNA editing is a highly conserved process. Adenosine deaminase acting on RNA (ADAR) mediated deamination of adenosine (A-to-I editing) is associated with human disease and immune checkpoint control. Functional implications of A-to-I editing are currently of broad interest to academic and industrial research as underscored by the fast-growing number of clinical studies applying base editors as therapeutic tools. Analyzing the dynamics of A-to-I editing, in a biological or therapeutic context, requires the sensitive detection of differential A-to-I editing, a currently unmet need. We introduce the local differential editing index (LoDEI) to detect differential A-to-I editing in RNA-seq datasets using a sliding-window approach coupled with an empirical q value calculation that detects more A-to-I editing sites at the same false-discovery rate compared to existing methods. LoDEI is validated on known and novel datasets revealing that the oncogene MYCN increases and that a specific small non-coding RNA reduces A-to-I editing.

Human endonuclease V (EndoV) catalytically removes deaminated nucleobases by cleaving the phosphodiester bond as part of RNA metabolism. Despite being implicated in several diseases (cancers, cardiovascular diseases, and neurological disorders) and potentially being a useful tool in biotechnology, details of the human EndoV catalytic pathway remain unclear due to limited experimental information beyond a crystal structure of the apoenzyme and select mutational data. Since a mechanistic understanding is critical for further deciphering the central roles and expanding applications of human EndoV in medicine and biotechnology, molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations were used to unveil the atomistic details of the catalytic pathway. Due to controversies surrounding the number of metals required for nuclease activity, enzyme-substrate models with different numbers of active site metals and various metal-substrate binding configurations were built based on structural data for other nucleases. Subsequent MD simulations revealed the structure and stability of the human EndoV-substrate complex for a range of active site metal binding architectures. Four unique pathways were then characterized using QM/MM that vary in metal number (one versus two) and modes of substrate coordination [direct versus indirect (water-mediated)], with several mechanisms being fully consistent with experimental structural, kinetic, and mutational data for related nucleases, including members of the EndoV family. Beyond uncovering key roles for several active site amino acids (D240 and K155), our calculations highlight that while one metal is essential for human EndoV activity, the enzyme can benefit from using two metals due to the presence of two suitable metal binding sites. By directly comparing one- versus two-metal-mediated P-O bond cleavage reactions within the confines of the same active site, our work brings a fresh perspective to the "number of metals" controversy.

Adenosine deaminases acting on RNA 1(ADAR1), an RNA editing enzyme that converts adenosine to inosine by deamination in double-stranded RNAs, plays an important role in occurrence and progression of various types of cancer. Ferroptosis has emerged as a hot topic of cancer research in recent years. We have previously reported that ADAR1 promotes breast cancer progression by regulating miR-335-5p and METTL3. However, whether ADAR1 has effects on ferroptosis in breast cancer cells is largely unknown. In this study, we knocked down ADAR1 using CRISPR-Cas9 technology or over-expressed ADAR1 protein using plasmid expressing ADAR1 in MCF-7 and MDA-MB-231 breast cancer cell lines, then detected cell viability, and levels of ROS, MDA, GSH, Fe2+, GPX4 protein and miR-335-5p. We showed that the cell proliferation was inhibited, levels of ROS, MDA, Fe2+, and miR-335-5p were increased, while GSH and GPX4 levels were decreased after loss of ADAR1, compared to the control group. The opposite effects were observed after ADAR1 overexpression in the cells. Further, we demonstrated that ADAR1-controlled miR-335-5p targeted Sp1 transcription factor of GPX4, a known ferroptosis molecular marker, leading to inhibition of ferroptosis by ADAR1 in breast cancer cells. Moreover, RNA editing activity of ADAR1 is not essential for inducing ferroptosis. Collectively, loss of ADAR1 induces ferroptosis in breast cancer cells by regulating miR-335-5p/Sp1/GPX4 pathway. The findings may provide insights into the mechanism by which ADAR1 promotes breast cancer progression via inhibiting ferroptosis.

N4-acetylcytidine (ac4C) is a post-transcriptional modification in mRNA that is critical in mRNA translation in terms of stability and regulation. In the past few years, numerous approaches employing convolutional neural networks (CNN) and Transformer have been proposed for the identification of ac4C sites, with each variety of approaches processing distinct characteristics. CNN-based methods excel at extracting local features and positional information, whereas Transformer-based ones stands out in establishing long-range dependencies and generating global representations. Given the importance of both local and global features in mRNA ac4C sites identification, we propose a novel method termed TransC-ac4C which combines CNN and Transformer together for enhancing the feature extraction capability and improving the identification accuracy. Five different feature encoding strategies (One-hot, NCP, ND, EIIP, and K-mer) are employed to generate the mRNA sequence representations, in which way the sequence attributes and physical and chemical properties of the sequences can be embedded. To strengthen the relevance of features, we construct a novel feature fusion method. Firstly, the CNN is employed to process five single features, stitch them together and feed them to the Transformer layer. Then, our approach employs CNN to extract local features and Transformer subsequently to establish global long-range dependencies among extracted features. We use 5-fold cross-validation to evaluate the model, and the evaluation indicators are significantly improved. The prediction accuracy of the two datasets is as high as 81.42% and 80.69%, respectively. It demonstrates the stronger competitiveness and generalization performance of our model.

Transposable elements (TEs), comprising nearly 50% of the human genome, have transitioned from being perceived as "genomic junk" to key players in cancer progression. Contemporary research links TE regulatory disruptions with cancer development, underscoring their therapeutic potential. Advances in long-read sequencing, computational analytics, single-cell sequencing, proteomics, and CRISPR-Cas9 technologies have enriched our understanding of TEs' clinical implications, notably their impact on genome architecture, gene regulation, and evolutionary processes. In cancer, TEs, including long interspersed element-1 (LINE-1), Alus, and long terminal repeat (LTR) elements, demonstrate altered patterns, influencing both tumorigenic and tumor-suppressive mechanisms. TE-derived nucleic acids and tumor antigens play critical roles in tumor immunity, bridging innate and adaptive responses. Given their central role in oncology, TE-targeted therapies, particularly through reverse transcriptase inhibitors and epigenetic modulators, represent a novel avenue in cancer treatment. Combining these TE-focused strategies with existing chemotherapy or immunotherapy regimens could enhance efficacy and offer a new dimension in cancer treatment. This review delves into recent TE detection advancements, explores their multifaceted roles in tumorigenesis and immune regulation, discusses emerging diagnostic and therapeutic approaches centered on TEs, and anticipates future directions in cancer research.

Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated.

In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features.

An RNA processing-related prognostic risk model based on 10 genes including FXR1, MFAP1, RBM17, SAGE1, SNRPA1, SRRM4, ADAD1, DDX52, ERI1, and EXOSC7 was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8+ T cells and poorer clinical prognosis than the low-risk group.

This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.

The activation of cerebral endothelial cells (CECs) has recently been reported to be the earliest acute neuroinflammation event in the CNS during sepsis-associated encephalopathy (SAE). Importantly, adenosine-to-inosine (A-to-I) RNA editing mediated by ADARs has been associated with SAE, yet its role in acute neuroinflammation in SAE remains unclear.

Our current study systematically analyzed A-to-I RNA editing in cerebral vessels, cerebral endothelial cells (CECs), and microglia sampled during acute neuroinflammation after treatment in a lipopolysaccharide (LPS)-induced SAE mouse model.

Our results showed dynamic A-to-I RNA editing activity changes in cerebral vessels during acute neuroinflammation. Differential A-to-I RNA editing (DRE) associated with acute neuroinflammation were identified in these tissue or cells, especially missense editing events such as S367G in antizyme inhibitor 1 (Azin1) and editing events in lincRNAs such as maternally expressed gene 3 (Meg3), AW112010, and macrophage M2 polarization regulator (Mm2pr). Importantly, geranylgeranyl diphosphate synthase 1 (Ggps1) and another three genes were differentially edited across cerebral vessels, CECs, and microglia. Notably, Spearman correlation analysis also revealed dramatic time-dependent DRE during acute neuroinflammation, especially in GTP cyclohydrolase1 (Gch1) and non-coding RNA activated by DNA damage (Norad), both with the editing level positively correlated with both post-LPS treatment time and edited gene expression in cerebral vessels and CECs.

The findings in our current study demonstrate substantial A-to-I RNA editing changes during acute neuroinflammation in SAE, underlining its potential role in the disease.

Adenosine-to-inosine (A-to-I) editing is one of the most widespread post-transcriptional RNA modifications and is catalyzed by adenosine deaminases acting on RNA (ADARs). Varying across tissue types, A-to-I editing is essential for numerous biological functions, and dysregulation leads to autoimmune and neurological disorders, as well as cancer. Recent evidence has also revealed a link between RNA localization and A-to-I editing, yet understanding of the mechanisms underlying this relationship and its biological impact remains limited. Current methods rely primarily on in vitro characterization of extracted RNA that ultimately erases subcellular localization and cell-to-cell heterogeneity. To address these challenges, we have repurposed endonuclease V (EndoV), a magnesium-dependent ribonuclease that cleaves inosine bases in edited RNA, to selectively bind and detect A-to-I edited RNA in cells. The work herein introduces an endonuclease V immunostaining assay (EndoVIA), a workflow that provides spatial visualization of edited transcripts, enables rapid quantification of overall inosine abundance, and maps the landscape of A-to-I editing within the transcriptome at the nanoscopic level.

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer and currently lacks effective biomarkers. This research aims to analyze and identify RNA editing profile associated with ccRCC prognosis through bioinformatics and in vitro experiments.

Transcriptome data and clinical information for ccRCC were retrieved from the TCGA database, and RNA editing files were obtained from the Synapse database. Prognostic models were screened, developed, and assessed using consistency index analysis and independent prognostic analysis, etc. Internal validation models were also constructed for further evaluation. Differential genes were investigated using GO, KEGG, and GSEA enrichment analyses. Furthermore, qPCR was performed to determine gene expression in human renal tubular epithelial cells HK-2 and ccRCC cells A-498, 786-O, and Caki-2.

An RNA editing-based risk score, that effectively distinguishes between high and low-risk populations, has been identified. It includes CHD3| chr17:7815229, MYO19| chr17:34853704, OIP5-AS1| chr15:41590962, MRI1| chr19:13883962, GBP4| chr1:89649327, APOL1| chr22:36662830, FCF1| chr14:75203040 edited sites or genes and could serve as an independent prognostic factor for ccRCC patients. qPCR results showed significant up-regulation of CHD3, MYO19, MRI1, APOL1, and FCF1 in A-498, 786-O, and Caki-2 cells, while the expression of OIP5-AS1 and GBP4 was significantly down-regulated.

RNA editing site-based prognostic models are valuable in differentiating between high and low-risk populations. The seven identified RNA editing sites may be utilized as potential biomarkers for ccRCC.

Numerous variants, including both single-nucleotide variants (SNVs) in DNA and A>G RNA edits in mRNA as essential drivers of cellular proliferation and tumorigenesis, are commonly associated with cancer progression and growth. Thus, mining and summarizing single-cell variants will provide a refined and higher-resolution view of cancer and further contribute to precision medicine. Here, we established a database, CanCellVar, which aims to provide and visualize the comprehensive atlas of single-cell variants in tumor microenvironment. The current CanCellVar identified ∼3 million variants (∼1.4 million SNVs and ∼1.4 million A>G RNA edits) involved in 2,754,531 cells of 5 major cell types across 37 cancer types. CanCellVar provides the basic annotation information as well as cellular and molecular function properties of variants. In addition, the clinical relevance of variants can be obtained including tumor grade, treatment, metastasis, and others. Several flexible tools were also developed to aid retrieval and to analyze cell-cell interactions, gene expression, cell-development trajectories, regulation, and molecular structure affected by variants. Collectively, CanCellVar will serve as a valuable resource for investigating the functions and characteristics of single-cell variations and their roles in human tumor evolution and treatment.

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.

RNA-seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants (SNVs) in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme that mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung adenocarcinoma cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, the use of short-read RNA-seq has limited the community's ability to interrogate both forms of RNA variation simultaneously.

We employ long-read sequencing technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We develop a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generate nanopore data with high sequence accuracy from H1975 lung adenocarcinoma cells with and without knockdown of ADAR. We apply our workflow to identify key inosine isoform associations to help clarify the prominence of ADAR in tumorigenesis.

Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

Cancer is a complex and heterogeneous disease, in which a number of genetic and epigenetic changes occur in tumor onset and progression. Recent studies indicate that changes at the RNA level are also involved in tumorigenesis, such as adenosine-to-inosine (A-to-I) RNA editing. Here, we systematically investigate transcriptome-wide A-to-I editing events in a large number of samples from Non-Hodgkin lymphomas (NHLs). Using a computational pipeline that determines significant differences in editing level between NHL and normal samples at known A-to-I editing sites, we identify a number of differentially edited editing sites between NHL subtypes and normal samples. Most of the differentially edited sites are located in non-coding regions, and many such sites show a strong correlation between gene expression level and editing efficiency, indicating that RNA editing might have direct consequences for the cancer cell's aberrant gene regulation status in these cases. Moreover, we establish a strong link between RNA editing and NHL by demonstrating that NHL and normal samples and even NHL subtypes can be distinguished based on genome-wide RNA editing profiles alone. Our study establishes a strong link between RNA editing, cancer and aberrant gene regulation in NHL.

ARID1A, a subunit of the SWI/SNF chromatin remodeling complex, is thought to play a significant role both in tumor suppression and tumor initiation, which is highly dependent upon context. Previous studies have suggested that ARID1A deficiency may contribute to cancer development. The specific mechanisms of whether ARID1A loss affects tumorigenesis by RNA editing remain unclear.

Our findings indicate that the deficiency of ARID1A leads to an increase in RNA editing levels and alterations in RNA editing categories mediated by adenosine deaminases acting on RNA 1 (ADAR1). ADAR1 edits the CDK13 gene at two previously unidentified sites, namely Q113R and K117R. Given the crucial role of CDK13 as a cyclin-dependent kinase, we further observed that ADAR1 deficiency results in changes in the cell cycle. Importantly, the sensitivity of ARID1A-deficient tumor cells to SR-4835, a CDK12/CDK13 inhibitor, suggests a promising therapeutic approach for individuals with ARID1A-mutant tumors. Knockdown of ADAR1 restored the sensitivity of ARID1A deficient cells to SR-4835 treatment.

ARID1A deficiency promotes RNA editing of CDK13 by regulating ADAR1.

RNA modifications, also termed epitranscriptomic marks, encompass chemical alterations to individual nucleotides, including processes such as methylation and editing. These marks contribute to a wide range of biological processes, many of which are related to host immune system defense. The functions of immune-related RNA modifications can be categorized into three main groups: regulation of immunogenic RNAs, control of genes involved in innate immune response, and facilitation of adaptive immunity. Here, we provide an overview of recent research findings that elucidate the contributions of RNA modifications to each of these processes. We also discuss relevant methods for genome-wide identification of RNA modifications and their immunogenic substrates. Finally, we highlight recent advances in cancer immunotherapies that aim to reduce cancer cell viability by targeting the enzymes responsible for RNA modifications. Our presentation of these dynamic research avenues sets the stage for future investigations in this field.

RNA editing, as an epigenetic mechanism, exhibits a strong correlation with the occurrence and development of cancers. Nevertheless, few studies have been conducted to investigate the impact of RNA editing on cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). In order to study the connection between RNA editing and CESC patients' prognoses, we obtained CESC-related information from The Cancer Genome Atlas (TCGA) database and randomly allocated the patients into the training group or testing group. An RNA editing-based risk model for CESC patients was established by Cox regression analysis and least absolute shrinkage and selection operator (LASSO). According to the median score generated by this RNA editing-based risk model, patients were categorized into subgroups with high and low risks. We further constructed the nomogram by risk scores and clinical characteristics and analyzed the impact of RNA editing levels on host gene expression levels and adenosine deaminase acting on RNA. Finally, we also compared the biological functions and pathways of differentially expressed genes (DEGs) between different subgroups by enrichment analysis. In this risk model, we screened out 6 RNA editing sites with significant prognostic value. The constructed nomogram performed well in forecasting patients' prognoses. Furthermore, the level of RNA editing at the prognostic site exhibited a strong correlation with host gene expression. In the high-risk subgroup, we observed multiple biological functions and pathways associated with immune response, cell proliferation, and tumor progression. This study establishes an RNA editing-based risk model that helps forecast patients' prognoses and offers a new understanding of the underlying mechanism of RNA editing in CESC.

Intra-organism biodiversity is thought to arise from epigenetic modification of constituent genes and post-translational modifications of translated proteins. Here, we show that post-transcriptional modifications, like RNA editing, may also contribute. RNA editing enzymes APOBEC3A and APOBEC3G catalyze the deamination of cytosine to uracil. RNAsee (RNA site editing evaluation) is a computational tool developed to predict the cytosines edited by these enzymes. We find that 4.5% of non-synonymous DNA single nucleotide polymorphisms that result in cytosine to uracil changes in RNA are probable sites for APOBEC3A/G RNA editing; the variant proteins created by such polymorphisms may also result from transient RNA editing. These polymorphisms are associated with over 20% of Medical Subject Headings across ten categories of disease, including nutritional and metabolic, neoplastic, cardiovascular, and nervous system diseases. Because RNA editing is transient and not organism-wide, future work is necessary to confirm the extent and effects of such editing in humans.

X-chromosome inactivation (XCI) is an epigenetic process that occurs during early development in mammalian females by randomly silencing one of two copies of the X chromosome in each cell. The preferential inactivation of either the maternal or paternal copy of the X chromosome in a majority of cells results in a skewed or non-random pattern of X inactivation and is observed in over 25% of adult females. Identifying skewed X inactivation is of clinical significance in patients with suspected rare genetic diseases due to the possibility of biased expression of disease-causing genes present on the active X chromosome. The current clinical test for the detection of skewed XCI relies on the methylation status of the methylation-sensitive restriction enzyme (Hpall) binding site present in proximity of short tandem polymorphic repeats on the androgen receptor (AR) gene. This approach using one locus results in uninformative or inconclusive data for 10-20% of tests. Further, recent studies have shown inconsistency between methylation of the AR locus and the state of inactivation of the X chromosome. Herein, we develop a method for estimating X inactivation status, using exome and transcriptome sequencing data derived from blood in 227 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium. We tested and validated the model on 11 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique.

In comparison to the AR clinical test for identification of X inactivation, our method was concordant with the AR method in 9 samples, discordant in 1, and provided a measure of X inactivation in 1 sample with uninformative clinical results. We applied this method on an additional 81 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis.

This study presents the use of transcriptome and exome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in a cohort of female patients with different types of suspected rare genetic disease.