Post-transcriptional RNA Modification Research Articles

Regulatory effect of m6 A modification on different viruses.

N6 -methyladenosine (m6 A) modification is the most common and reversible posttranscriptional modification of RNA in eukaryotes, which is mainly regulated by methyltransferase, demethylase, and specific binding protein. The replication of the virus and host immune response to the virus are affected by m6 A modification. In different kinds of viruses, m6 A modification has two completely opposite regulatory functions. This paper reviews the regulatory effects of m6 A modification on different viruses and provides a reference for studying the regulatory effects of RNA epitranscriptomic modification.

M5C-Related Signatures for Predicting Prognosis in Cutaneous Melanoma with Machine Learning.

Background Cutaneous melanoma (CM) is one of the most life-threatening primary skin cancers and is prone to distant metastases. A widespread presence of posttranscriptional modification of RNA, 5-methylcytosine (m5C), has been observed in human cancers. However, the potential mechanism of the tumorigenesis and prognosis in CM by dysregulated m5C-related regulators is obscure. Methods We use comprehensive bioinformatics analyses to explore the expression of m5C regulators in CM, the prognostic implications of the m5C regulators, the frequency of the copy number variant (CNV), and somatic mutations in m5C regulators. Additionally, the CM patients were divided into three clusters for better predicting clinical features and outcomes via consensus clustering of m5C regulators. Then, the risk score was established via Lasso Cox regression analysis. Next, the prognosis value and clinical characteristics of m5C-related signatures were further explored. Then, machine learning was used to recognize the outstanding m5C regulators to risk score. Finally, the expression level and clinical value of USUN6 were analyzed via the tissue microarray (TMA) cohort. Results We found that m5C regulators were dysregulated in CM, with a high frequency of somatic mutations and CNV alterations of the m5C regulatory gene in CM. Furthermore, 16 m5C-related proteins interacted with each other frequently, and we divided CM patients into three clusters to better predicting clinical features and outcomes. Then, five m5C regulators were selected as a risk score based on the LASSO model. The XGBoost algorithm recognized that NOP2 and NSUN6 were the most significant risk score contributors. Immunohistochemistry has verified that low expression of USUN6 was closely correlated with CM progression. Conclusion The m5C-related signatures can be used as new prognostic biomarkers and therapeutic targets for CM, and NSUN6 might play a vital role in tumorigenesis and malignant progression.

Active genic machinery for epigenetic RNA modifications in bees.

Epitranscriptomics is an emerging field of investigation dedicated to the study of post-transcriptional RNA modifications. RNA methylations regulate RNA metabolism and processing, including changes in response to environmental cues. Although RNA modifications are conserved from bacteria to eukaryotes, there is little evidence of an epitranscriptomic pathway in insects. Here we identified genes related to RNA m6 A (N6-methyladenine) and m5 C (5-methylcytosine) methylation machinery in seven bee genomes (Apis mellifera, Melipona quadrifasciata, Frieseomelitta varia, Eufriesea mexicana, Bombus terrestris, Megachile rotundata and Dufourea novaeangliae). In A. mellifera, we validated the expression of methyltransferase genes and found that the global levels of m6 A and m5 C measured in the fat body and brain of adult workers differ significantly. Also, m6 A levels were differed significantly mainly between the fourth larval instar of queens and workers. Moreover, we found a conserved m5 C site in the honeybee 28S rRNA. Taken together, we confirm the existence of epitranscriptomic machinery acting in bees and open avenues for future investigations on RNA epigenetics in a wide spectrum of hymenopteran species.

NSUN2-mediated RNA 5-methylcytosine promotes esophageal squamous cell carcinoma progression via LIN28B-dependent GRB2 mRNA stabilization

5-Methylcytosine (m5C) is a posttranscriptional RNA modification participating in many critical bioprocesses, but its functions in human cancer remain unclear. Here, by detecting the transcriptome-wide m5C profiling in esophageal squamous cell carcinoma (ESCC), we showed increased m5C methylation in ESCC tumors due to the overexpressed m5C methyltransferase NSUN2. Aberrant expression of NSUN2 was positively regulated by E2F Transcription Factor 1 (E2F1). High NSUN2 levels predicted poor survival of ESCC patients. Moreover, silencing NSUN2 suppressed ESCC tumorigenesis and progression in Nsun2 knockout mouse models. Mechanistically, NSUN2 induced m5C modification of growth factor receptor-bound protein 2 (GRB2) and stabilized its mRNA, which was mediated by a novel m5C mediator, protein lin-28 homolog B (LIN28B). Elevated GRB2 levels increased the activation of PI3K/AKT and ERK/MAPK signalling. These results demonstrate that NSUN2 enhances the initiation and progression of ESCC via m5C-LIN28B dependent stabilization of GRB2 transcript, providing a promising epitranscriptomic-targeted therapeutic strategy for ESCC.

The small Cajal body-specific RNA 15 (SCARNA15) directs p53 and redox homeostasis via selective splicing in cancer cells.

Small Cajal body-specific RNAs (scaRNAs) guide post-transcriptional modification of spliceosomal RNA and, while commonly altered in cancer, have poorly defined roles in tumorigenesis. Here, we uncover that SCARNA15 directs alternative splicing (AS) and stress adaptation in cancer cells. Specifically, we find that SCARNA15 guides critical pseudouridylation (Ψ) of U2 spliceosomal RNA to fine-tune AS of distinct transcripts enriched for chromatin and transcriptional regulators in malignant cells. This critically impacts the expression and function of the key tumor suppressors ATRX and p53. Significantly, SCARNA15 loss impairs p53-mediated redox homeostasis and hampers cancer cell survival, motility and anchorage-independent growth. In sum, these findings highlight an unanticipated role for SCARNA15 and Ψ in directing cancer-associated splicing programs.

Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications

Recent studies suggest that epi-transcriptome regulation via post-transcriptional RNA modifications is vital for all RNA types. Precise identification of RNA modification sites is essential for understanding the functions and regulatory mechanisms of RNAs. Here, we present MultiRM, a method for the integrated prediction and interpretation of post-transcriptional RNA modifications from RNA sequences. Built upon an attention-based multi-label deep learning framework, MultiRM not only simultaneously predicts the putative sites of twelve widely occurring transcriptome modifications (m6A, m1A, m5C, m5U, m6Am, m7G, Ψ, I, Am, Cm, Gm, and Um), but also returns the key sequence contents that contribute most to the positive predictions. Importantly, our model revealed a strong association among different types of RNA modifications from the perspective of their associated sequence contexts. Our work provides a solution for detecting multiple RNA modifications, enabling an integrated analysis of these RNA modifications, and gaining a better understanding of sequence-based RNA modification mechanisms.

Gamma-irradiation fluctuates the mRNA N6-methyladenosine (m6A) spectrum of bone marrow in hematopoietic injury

Humans benefit from nuclear technologies but consequently experience nuclear disasters or side effects of iatrogenic radiation. Hematopoietic system injury first arises upon radiation exposure. As an intricate new layer of genetic control, the posttranscriptional m6A modification of RNA has recently come under investigation and has been demonstrated to play pivotal roles in multiple physiological and pathological processes. However, how the m6A methylome functions in the hematopoietic system after irradiation remains ambiguous. Here, we uncovered the time-varying epitranscriptome-wide m6A methylome and transcriptome alterations in γ-ray-exposed mouse bone marrow. 4 Gy γ-irradiation rapidly (5 min and 2 h) and severely impaired the mouse hematopoietic system, including spleen and thymus weight, blood components, tissue inflammation and malondialdehyde (MDA) levels. The m6A content and expression of m6A related enzymes were altered. Gamma-irradiation triggered dynamic and reversible m6A modification profiles and altered mRNA expression, where both m6A fold-enrichment and mRNA expression most followed the (5 min_up/2 h_down) pattern. The CDS enrichment region preferentially upregulated m6A peaks at 5 min. Moreover, the main GO and KEGG pathways were closely related to metabolism and the classical radiation response. Finally, m6A modifications correlated with transcriptional regulation of genes in multiple aspects. Blocking the expression of m6A demethylases FTO and ALKBH5 mitigated radiation hematopoietic toxicity. Together, our findings present the comprehensive landscape of mRNA m6A methylation in the mouse hematopoietic system in response to γ-irradiation, shedding light on the significance of m6A modifications in mammalian radiobiology. Regulation of the epitranscriptome may be exploited as a strategy against radiation damage.

Downregulation of the FTO m6A RNA demethylase promotes EMT-mediated progression of epithelial tumors and sensitivity to Wnt inhibitors.

Post-transcriptional modifications of RNA constitute an emerging regulatory layer of gene expression. The demethylase fat mass- and obesity-associated protein (FTO), an eraser of N6-methyladenosine (m6A), has been shown to play a role in cancer, but its contribution to tumor progression and the underlying mechanisms remain unclear. Here, we report widespread FTO downregulation in epithelial cancers associated with increased invasion, metastasis and worse clinical outcome. Both in vitro and in vivo, FTO silencing promotes cancer growth, cell motility and invasion. In human-derived tumor xenografts (PDXs), FTO pharmacological inhibition favors tumorigenesis. Mechanistically, we demonstrate that FTO depletion elicits an epithelial-to-mesenchymal transition (EMT) program through increased m6A and altered 3'-end processing of key mRNAs along the Wnt signaling cascade. Accordingly, FTO knockdown acts via EMT to sensitize mouse xenografts to Wnt inhibition. We thus identify FTO as a key regulator, across epithelial cancers, of Wnt-triggered EMT and tumor progression and reveal a therapeutically exploitable vulnerability of FTO-low tumors.

Agnostic Framework for the Classification/Identification of Organisms Based on RNA Post-Transcriptional Modifications.

We propose a novel approach for building a classification/identification framework based on the full complement of RNA post-transcriptional modifications (rPTMs) expressed by an organism at basal conditions. The approach relies on advanced mass spectrometry techniques to characterize the products of exonuclease digestion of total RNA extracts. Sample profiles comprising identities and relative abundances of all detected rPTM were used to train and test the capabilities of different machine learning (ML) algorithms. Each algorithm proved capable of identifying rigorous decision rules for differentiating closely related classes and correctly assigning unlabeled samples. The ML classifiers resolved different members of the Enterobacteriaceae family, alternative Escherichia coli serotypes, a series of Saccharomyces cerevisiae knockout mutants, and primary cells of the Homo sapiens central nervous system, which shared very similar genetic backgrounds. The excellent levels of accuracy and resolving power achieved by training on a limited number of classes were successfully replicated when the number of classes was significantly increased to escalate complexity. A dendrogram generated from ML-curated data exhibited a hierarchical organization that closely resembled those afforded by established taxonomic systems. Finer clustering patterns revealed the extensive effects induced by the deletion of a single pivotal gene. This information provided a putative roadmap for exploring the roles of rPTMs in their respective regulatory networks, which will be essential to decipher the epitranscriptomics code. The ubiquitous presence of RNA in virtually all living organisms promises to enable the broadest possible range of applications, with significant implications in the diagnosis of RNA-related diseases.

M6AGE: A Predictor for N6-Methyladenosine Sites Identification Utilizing Sequence Characteristics and Graph Embedding-Based Geometrical Information.

N6-methyladenosine (m6A) is one of the most prevalent RNA post-transcriptional modifications and is involved in various vital biological processes such as mRNA splicing, exporting, stability, and so on. Identifying m6A sites contributes to understanding the functional mechanism and biological significance of m6A. The existing biological experimental methods for identifying m6A sites are time-consuming and costly. Thus, developing a high confidence computational method is significant to explore m6A intrinsic characters. In this study, we propose a predictor called m6AGE which utilizes sequence-derived and graph embedding features. To the best of our knowledge, our predictor is the first to combine sequence-derived features and graph embeddings for m6A site prediction. Comparison results show that our proposed predictor achieved the best performance compared with other predictors on four public datasets across three species. On the A101 dataset, our predictor outperformed 1.34% (accuracy), 0.0227 (Matthew’s correlation coefficient), 5.63% (specificity), and 0.0081 (AUC) than comparing predictors, which indicates that m6AGE is a useful tool for m6A site prediction. The source code of m6AGE is available at https://github.com/bokunoBike/m6AGE.

Transcriptome-Wide N6-Methyladenosine (m6A) Profiling of Susceptible and Resistant Wheat Varieties Reveals the Involvement of Variety-Specific m6A Modification Involved in Virus-Host Interaction Pathways.

N6-methyladenosine (m6A) methylation is the most prevalent internal modification of post-transcriptional modifications in mRNA, tRNA, miRNA, and long non-coding RNA in eukaryotes. m6A methylation has been proven to be involved in plant resistance to pathogens. However, there are no reports on wheat (Triticum aestivum) m6A transcriptome-wide map and its potential biological function in wheat resistance to wheat yellow mosaic virus (WYMV). To the best of our knowledge, this study is the first to determine the transcriptome-wide m6A profile of two wheat varieties with different resistances to WYMV. By analyzing m6A-sequencing (m6A-seq) data, we identified 25,752 common m6A peaks and 30,582 common m6A genes in two groups [WYMV-infected resistant wheat variety (WRV) and WYMV-infected sensitive wheat variety (WSV)], and all these peaks were mainly enriched in 3′ untranslated regions and stop codons of coding sequences. Gene Ontology analysis of m6A-seq and RNA-sequencing data revealed that genes that showed significant changes in both m6A and mRNA levels were associated with plant defense responses. Kyoto Encyclopedia of Genes and Genomes analysis revealed that these selected genes were enriched in the plant–pathogen interaction pathway. We further verified these changes in m6A and mRNA levels through gene-specific m6A real-time quantitative PCR (RT-qPCR) and normal RT-qPCR. This study highlights the role of m6A methylation in wheat resistance to WYMV, providing a solid basis for the potential functional role of m6A RNA methylation in wheat resistance to infection by RNA viruses.

RFhy-m2G: Identification of RNA N2-methylguanosine modification sites based on random forest and hybrid features.

N2-methylguanosine is a post-transcriptional modification of RNA that is found in eukaryotes and archaea. The biological function of m2G modification discovered so far is to control and stabilize the three-dimensional structure of tRNA and the dynamic barrier of reverse transcription. To discover additional biological functions of m2G, it is necessary to develop time-saving and labor-saving calculation tools to identify m2G. In this paper, based on hybrid features and a random forest, a novel predictor, RFhy-m2G, was developed to identify the m2G modification sites for three species. The hybrid feature used by the predictor is used to fuse the three features of ENAC, PseDNC, and NPPS. These three features include primary sequence derivation properties, physicochemical properties, and position-specific properties. Since there are redundant features in hybrid features, MRMD2.0 is used for optimal feature selection. Through feature analysis, it is found that the optimal hybrid features obtained still contain three kinds of properties, and the hybrid features can more accurately identify m2G modification sites and improve prediction performance. Based on five-fold cross-validation and independent testing to evaluate the prediction model, the accuracies obtained were 0.9982 and 0.9417, respectively. The robustness of the predictor is demonstrated by comparisons with other predictors.

From Antisense RNA to RNA Modification: Therapeutic Potential of RNA-Based Technologies.

Therapeutic oligonucleotides interact with a target RNA via Watson-Crick complementarity, affecting RNA-processing reactions such as mRNA degradation, pre-mRNA splicing, or mRNA translation. Since they were proposed decades ago, several have been approved for clinical use to correct genetic mutations. Three types of mechanisms of action (MoA) have emerged: RNase H-dependent degradation of mRNA directed by short chimeric antisense oligonucleotides (gapmers), correction of splicing defects via splice-modulation oligonucleotides, and interference of gene expression via short interfering RNAs (siRNAs). These antisense-based mechanisms can tackle several genetic disorders in a gene-specific manner, primarily by gene downregulation (gapmers and siRNAs) or splicing defects correction (exon-skipping oligos). Still, the challenge remains for the repair at the single-nucleotide level. The emerging field of epitranscriptomics and RNA modifications shows the enormous possibilities for recoding the transcriptome and repairing genetic mutations with high specificity while harnessing endogenously expressed RNA processing machinery. Some of these techniques have been proposed as alternatives to CRISPR-based technologies, where the exogenous gene-editing machinery needs to be delivered and expressed in the human cells to generate permanent (DNA) changes with unknown consequences. Here, we review the current FDA-approved antisense MoA (emphasizing some enabling technologies that contributed to their success) and three novel modalities based on post-transcriptional RNA modifications with therapeutic potential, including ADAR (Adenosine deaminases acting on RNA)-mediated RNA editing, targeted pseudouridylation, and 2′-O-methylation.

Advanced Sequencing of Kidney Tubule Hypoxia Regulated Epithelial‐to‐Mesenchymal Transition

Hypoxia is a known regulator of epithelial-to-mesenchymal transition in kidney tubule cells. However, culture systems have struggled to observe these transitions at high levels to capture transcriptional signatures due to the detachment of cells from culture vessels. Using the Renal Proximal Tubule Epithelial Cell stabile cell line (RPTEC-TERT1) we developed a shear stress culture system that when exposed to hypoxia (1% oxygen) result in cell dysmorphology instead of detachment, allowing for a large number of cells to be generated for transcriptomic studies. With these cells exposed to hypoxia, we performed both traditional polyA RNAseq using both Illumina and Nanopore technologies and newer direct RNAseq using Nanopore. The polyA RNAseq suggests regulation changes for HIF-1/hypoxia, Nonsense mediated decay, ruffle assembly, and energetic regulated genes. Direct RNAseq, a strategy of running mRNA molecules across Nanopore to detect RNA base modifications transcriptome wide, revealed genes that are acutely modified related to glycolysis, innate immunity, oxidation-reduction, and mitochondrial biology. Cells exposed to hypoxia for 48 hours followed by 48 hours of normoxia, return the modifications back to control levels suggesting there is a major source of hypoxia cell signaling through RNA posttranscriptional modifications. Using the differentially regulated genes of the hypoxia culture model we have also shown that it is possible to filter genetic models systems such as human chronic/acute kidney disease or rat heterogenous stock proteinuria to narrow down novel mechanisms for genetic influence to hypoxia response. In doing this, we nominated and validated the role of SEPTIN8 in hypoxia response cell integrity, where dysregulation of SEPTIN8 can further propagate complications of hypoxia to disease progression.

Aging through an epitranscriptomic lens.

The mechanistic causes of aging, the time-related decline in function and good health that leads to increased mortality, remain poorly understood. Here we propose that age-dependent alteration of the epitranscriptome, encompassing more than 150 chemically distinct post-transcriptional modifications or editing events, warrants exploration as an important modulator of aging. The epitranscriptome is a potent regulator of RNA function, diverse cellular processes and tissue regenerative capacity. To date, only a few studies link alterations in the epitranscriptome to molecular and physiological changes during aging; however, epitranscriptome dysfunction is associated with and underlies several age-associated pathologies, including cancer and neurodegenerative, cardiovascular and autoimmune diseases. For example, changes in RNA modifications (such as N6-methyladenosine and inosine) impact cardiac physiology and are linked to cardiac fibrosis. Although an uncharted research focus, mapping epitranscriptome alterations in the context of aging may elucidate novel predictors of both health and lifespan, and may identify therapeutic targets for attenuating aging and abrogating age-related diseases.

YTHDF1 Aggravates the Progression of Cervical Cancer Through m6A-Mediated Up-Regulation of RANBP2.

N6-methyladenosine (m6A) is the most common post-transcriptional modification of RNA in eukaryotes, which has been demonstrated to play important roles in various cancers. YTHDF1 acts as a crucial m6A “reader” and regulates the fate of m6A modified mRNA. However, its role in cervical cancer remains unknown. In this study, we showed that YTHDF1 was highly expressed in cervical cancer, and was closely associated with the poor prognosis of cervical cancer patients. YTHDF1 knockdown suppressed the growth, migration and invasion, and induced apoptosis of cervical cancer cells. Moreover, YTHDF1 knockdown inhibited tumorigenesis of cervical cancer cells in vivo. Through combined on-line data analysis of RIP-seq, meRIP-seq and Ribo-seq upon YTHDF1 knockdown, RANBP2 was identified as the key target of YTHDF1 in cervical cancer cells. YTHDF1 regulated RANBP2 translation in an m6A-dependent manner without effect on its mRNA expression. RANBP2 potentiated the growth, migration and invasion of cervical cancer cells. Our study demonstrated the oncogenic role of YTHDF1 in cervical cancer by regulating RANBP2 expression and YTHDF1 represents a potential target for cervical cancer therapy.

DNN-m6A: A Cross-Species Method for Identifying RNA N6-Methyladenosine Sites Based on Deep Neural Network with Multi-Information Fusion.

As a prevalent existing post-transcriptional modification of RNA, N6-methyladenosine (m6A) plays a crucial role in various biological processes. To better radically reveal its regulatory mechanism and provide new insights for drug design, the accurate identification of m6A sites in genome-wide is vital. As the traditional experimental methods are time-consuming and cost-prohibitive, it is necessary to design a more efficient computational method to detect the m6A sites. In this study, we propose a novel cross-species computational method DNN-m6A based on the deep neural network (DNN) to identify m6A sites in multiple tissues of human, mouse and rat. Firstly, binary encoding (BE), tri-nucleotide composition (TNC), enhanced nucleic acid composition (ENAC), K-spaced nucleotide pair frequencies (KSNPFs), nucleotide chemical property (NCP), pseudo dinucleotide composition (PseDNC), position-specific nucleotide propensity (PSNP) and position-specific dinucleotide propensity (PSDP) are employed to extract RNA sequence features which are subsequently fused to construct the initial feature vector set. Secondly, we use elastic net to eliminate redundant features while building the optimal feature subset. Finally, the hyper-parameters of DNN are tuned with Bayesian hyper-parameter optimization based on the selected feature subset. The five-fold cross-validation test on training datasets show that the proposed DNN-m6A method outperformed the state-of-the-art method for predicting m6A sites, with an accuracy (ACC) of 73.58–83.38% and an area under the curve (AUC) of 81.39–91.04%. Furthermore, the independent datasets achieved an ACC of 72.95–83.04% and an AUC of 80.79–91.09%, which shows an excellent generalization ability of our proposed method.

Characterizing RNA Pseudouridylation by Convolutional Neural Networks

Pseudouridine (Ψ) is the most prevalent post-transcriptional RNA modification and is widespread in small cellular RNAs and mRNAs. However, the functions, mechanisms, and precise distribution of Ψs (especially in mRNAs) still remain largely unclear. The landscape of Ψs across the transcriptome has not yet been fully delineated. Here, we present a highly effective model based on a convolutional neural network (CNN), called PseudoUridyLation Site Estimator (PULSE), to analyze large-scale profiling data of Ψ sites and characterize the contextual sequence features of pseudouridylation. PULSE, consisting of two alternatively-stacked convolution and pooling layers followed by a fully-connected neural network, can automatically learn the hidden patterns of pseudouridylation from the local sequence information. Extensive validation tests demonstrated that PULSE can outperform other state-of-the-art prediction methods and achieve high prediction accuracy, thus enabling us to further characterize the transcriptome-wide landscape of Ψ sites. We further showed that the prediction results derived from PULSE can provide novel insights into understanding the functional roles of pseudouridylation, such as the regulations of RNA secondary structure, codon usage, translation, and RNA stability, and the connection to single nucleotide variants. The source code and final model for PULSE are available at https://github.com/mlcb-thu/PULSE.

N6-methyladenosine modification of MALAT1 promotes metastasis via reshaping nuclear speckles.

N6-methyladenosine (m6A), one of the most prevalent RNA post-transcriptional modifications, is involved in numerous biological processes. In previous studies, the functions of m6A were typically identified by perturbing the activity of the methyltransferase complex. Here, we dissect the contribution of m6A to an individual-long noncoding RNA-metastasis-associated lung adenocarcinoma transcript 1 (MALAT1). The mutant MALAT1 lacking m6A-motifs significantly suppressed the metastatic potential of cancer cells both invitro and invivo in mouse. Super-resolution imaging showed that the concatenated m6A residues on MALAT1 acted as a scaffold for recruiting YTH-domain-containing protein 1 (YTHDC1) to nuclear speckles. We further reveal that the recognition of MALAT1-m6A by YTHDC1 played a critical role in maintaining the composition and genomic binding sites of nuclear speckles, which regulate the expression of several key oncogenes. Furthermore, artificially tethering YTHDC1 onto m6A-deficient MALAT1 largely rescues the metastatic potential of cancer cells.

Alteration of mRNA 5-Methylcytosine Modification in Neurons After OGD/R and Potential Roles in Cell Stress Response and Apoptosis.

Epigenetic modifications play an important role in central nervous system disorders. As a widespread posttranscriptional RNA modification, the role of the m5C modification in cerebral ischemia-reperfusion injury (IRI) remains poorly defined. Here, we successfully constructed a neuronal oxygen-glucose deprivation/reoxygenation (OGD/R) model and obtained an overview of the transcriptome-wide m5C profiles using RNA-BS-seq. We discovered that the distribution of neuronal m5C modifications was highly conserved, significantly enriched in CG-rich regions and concentrated in the mRNA translation initiation regions. After OGD/R, modification level of m5C increased, whereas the number of methylated mRNA genes decreased. The amount of overlap of m5C sites with the binding sites of most RNA-binding proteins increased significantly, except for that of the RBM3-binding protein. Moreover, hypermethylated genes in neurons were significantly enriched in pathological processes, and the hub hypermethylated genes RPL8 and RPS9 identified by the protein-protein interaction network were significantly related to cerebral injury. Furthermore, the upregulated transcripts with hypermethylated modification were enriched in the processes involved in response to stress and regulation of apoptosis, and these processes were not identified in hypomethylated transcripts. In final, we verified that OGD/R induced neuronal apoptosis in vitro using TUNEL and western blot assays. Our study identified novel m5C mRNAs associated with ischemia-reperfusion in neurons, providing valuable perspectives for future studies on the role of the RNA methylation in cerebral IRI.