DirectRMDB: a database of post-transcriptional RNA modifications unveiled from direct RNA sequencing technology

The roles of epigenetic regulation in graft-versus-host disease

Allogeneic hematopoietic stem cell transplantation (aHSCT) is utilized as a potential curative treatment for various hematologic malignancies. However, graft-versus-host disease (GVHD) post-aHSCT is a severe complication that significantly impacts patients' quality of life and overall survival, becoming a major cause of non-relapse mortality. In recent years, the association between epigenetics and GVHD has garnered increasing attention. Epigenetics focuses on studying mechanisms that affect gene expression without altering DNA sequences, primarily including DNA methylation, histone modifications, non-coding RNAs (ncRNAs) regulation, and RNA modifications. This review summarizes the role of epigenetic regulation in the pathogenesis of GVHD, with a focus on DNA methylation, histone modifications, ncRNA, RNA modifications and their involvement and applications in the occurrence and development of GVHD. It also highlights advancements in relevant diagnostic markers and drugs, aiming to provide new insights for the clinical diagnosis and treatment of GVHD.

NanoMUD: Profiling of pseudouridine and N1-methylpseudouridine using Oxford Nanopore direct RNA sequencing

Nanopore direct RNA sequencing provided a promising solution for unraveling the landscapes of modifications on single RNA molecules. Here, we proposed NanoMUD, a computational framework for predicting the RNA pseudouridine modification (Ψ) and its methylated analog N1-methylpseudouridine (m1Ψ), which have critical application in mRNA vaccination, at single-base and single-molecule resolution from direct RNA sequencing data. Electric signal features were fed into a bidirectional LSTM neural network to achieve improved accuracy and predictive capabilities. Motif-specific models (NNUNN, N = A, C, U or G) were trained based on features extracted from designed dataset and achieved superior performance on molecule-level modification prediction (Ψ models: min AUC = 0.86, max AUC = 0.99; m1Ψ models: min AUC = 0.87, max AUC = 0.99). We then aggregated read-level predictions for site stoichiometry estimation. Given the observed sequence-dependent bias in model performance, we trained regression models based on the distribution of modification probabilities for sites with known stoichiometry. The distribution-based site stoichiometry estimation method allows unbiased comparison between different contexts. To demonstrate the feasibility of our work, three case studies on both in vitro and in vivo transcribed RNAs were presented. NanoMUD will make a powerful tool to facilitate the research on modified therapeutic IVT RNAs and provides useful insight to the landscape and stoichiometry of pseudouridine and N1-pseudouridine on in vivo transcribed RNA species.

Quantitative profiling N1-methyladenosine (m1A) RNA methylation from Oxford nanopore direct RNA sequencing data

With the recent advanced direct RNA sequencing technique that proposed by the Oxford Nanopore Technologies, RNA modifications can be detected and profiled in a simple and straightforward manner. Majority nanopore-based modification studies were devoted to those popular types such as m6A and pseudouridine. To address current limitations on studying the crucial regulator, m1A modification, we conceived this study. We have developed an integrated computational workflow designed for the detection of m1A modifications from direct RNA sequencing data. This workflow comprises a feature extractor responsible for capturing signal characteristics (such as mean, standard deviations, and length of electric signals), a single molecule-level m1A predictor trained with features extracted from the IVT dataset using classical machine learning algorithms, a confident m1A site selector employing the binomial test to identify statistically significant m1A sites, and an m1A modification rate estimator. Our model achieved accurate molecule-level prediction (Average AUC = 0.9689) and reliable m1A site detection and quantification. To show the feasibility of our workflow, we conducted a study on in vivo transcribed human HEK293 cell line, and the results were carefully annotated and compared with other techniques (i.e., Illumina sequencing-based techniques). We believed that this tool will enabling a comprehensive understanding of the m1A modification and its functional mechanisms within cells and organisms.

Integrating Epigenetics, Proteomics, and Metabolomics to Reveal the Involvement of Wnt/β-Catenin Signaling Pathway in Oridonin-Induced Reproductive Toxicity

Oridonin is the primary active component in the traditional Chinese medicine Rabdosia rubescens, displaying anti-inflammatory, anti-tumor, and antibacterial effects. It is widely employed in clinical therapy for acute and chronic pharyngitis, tonsillitis, as well as bronchitis. Nevertheless, the clinical application of oridonin is significantly restricted due to its reproductive toxicity, with the exact mechanism remaining unclear. The aim of this study was to investigate the mechanism of oridonin-induced damage to HTR-8/SVneo cells. Through the integration of epigenetics, proteomics, and metabolomics methodologies, the mechanisms of oridonin-induced reproductive toxicity were discovered and confirmed through fluorescence imaging, RT-qPCR, and Western blotting. Experimental findings indicated that oridonin altered m6A levels, gene and protein expression levels, along with metabolite levels within the cells. Additionally, oridonin triggered oxidative stress and mitochondrial damage, leading to a notable decrease in WNT6, β-catenin, CLDN1, CCND1, and ZO-1 protein levels. This implied that the inhibition of the Wnt/β-catenin signaling pathway and disruption of tight junction might be attributed to the cytotoxicity induced by oridonin and mitochondrial dysfunction, ultimately resulting in damage to HTR-8/SVneo cells.

RNA modifications in pulmonary diseases

Threatening public health, pulmonary disease (PD) encompasses diverse lung injuries like chronic obstructive PD, pulmonary fibrosis, asthma, pulmonary infections due to pathogen invasion, and fatal lung cancer. The crucial involvement of RNA epigenetic modifications in PD pathogenesis is underscored by robust evidence. These modifications not only shape cell fates but also finely modulate the expression of genes linked to disease progression, suggesting their utility as biomarkers and targets for therapeutic strategies. The critical RNA modifications implicated in PDs are summarized in this review, including N6-methylation of adenosine, N1-methylation of adenosine, 5-methylcytosine, pseudouridine (5-ribosyl uracil), 7-methylguanosine, and adenosine to inosine editing, along with relevant regulatory mechanisms. By shedding light on the pathology of PDs, these summaries could spur the identification of new biomarkers and therapeutic strategies, ultimately paving the way for early PD diagnosis and treatment innovation.

Emerging role of N6-methyladenosine RNA modification in regulation of SARS-CoV-2 infection and virus-host interactions

Since December 2019, the infection caused by Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) has posed an enormous threat to human health security worldwide. Constant mutation of viral genome and varying therapeutic responses of patients infected with this virus prompted efforts to uncover more novel regulators in the pathogenesis. The involvement of N6-methyladenosine, a modified form of RNA, plays a crucial role in viral replication, viral pathogenicity, and intricate signaling pathways connected with immune responses. This review discusses research advances revealing the regulation of the life cycle of SARS-CoV-2 and antiviral responses of host cells by RNA m6A modification, highlights the biological functions of N6-methyladenosine components in SARS-CoV-2 infection and virus-host interactions, and outlines current challenges and future directions for exploring the potential clinical value of m6A modification in COVID-19.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

BiPSTP: Sequence feature encoding method for identifying different RNA modifications with bidirectional position-specific trinucleotides propensities

RNA modification, a posttranscriptional regulatory mechanism, significantly influences RNA biogenesis and function. The accurate identification of modification sites is paramount for investigating their biological implications. Methods for encoding RNA sequence into numerical data play a crucial role in developing robust models for predicting modification sites. However, existing techniques suffer from limitations, including inadequate information representation, challenges in effectively integrating positional and sequential information, and the generation of irrelevant or redundant features when combining multiple approaches. These deficiencies hinder the effectiveness of machine learning models in addressing the performance challenges associated with predicting RNA modification sites. Here, we introduce a novel RNA sequence feature representation method, named BiPSTP, which utilizes bidirectional trinucleotide position-specific propensities. We employ the parameter ξ to denote the interval between the current nucleotide and its adjacent forward or backward dinucleotide, enabling the extraction of positional and sequential information from RNA sequences. Leveraging the BiPSTP method, we have developed the prediction model mRNAPred using support vector machine classifier to identify multiple types of RNA modification sites. We evaluate the performance of our BiPSTP method and mRNAPred model across 12 distinct RNA modification types. Our experimental results demonstrate the superiority of the mRNAPred model compared to state-of-art models in the domain of RNA modification sites identification. Importantly, our BiPSTP method enhances the robustness and generalization performance of prediction models. Notably, it can be applied to feature extraction from DNA sequences to predict other biological modification sites.

Regulatory role of m6A epitranscriptomic modifications in normal development and congenital malformations during embryogenesis

The discovery of N6-methyladenosine (m6A) methylation and its role in translation has led to the emergence of a new field of research. Despite accumulating evidence suggesting that m6A methylation is essential for the pathogenesis of cancers and aging diseases by influencing RNA stability, localization, transformation, and translation efficiency, its role in normal and abnormal embryonic development remains unclear. An increasing number of studies are addressing the development of the nervous and gonadal systems during embryonic development, but only few are assessing that of the immune, hematopoietic, urinary, and respiratory systems. Additionally, these studies are limited by the requirement for reliable embryonic animal models and the difficulty in collecting tissue samples of fetuses during development. Multiple studies on the function of m6A methylation have used suitable cell lines to mimic the complex biological processes of fetal development or the early postnatal phase; hence, the research is still in the primary stage. Herein, we discuss current advances in the extensive biological functions of m6A methylation in the development and maldevelopment of embryos/fetuses and conclude that m6A modification occurs extensively during fetal development. Aberrant expression of m6A regulators is probably correlated with single or multiple defects in organogenesis during the intrauterine life. This comprehensive review will enhance our understanding of the pivotal role of m6A modifications involved in fetal development and examine future research directions in embryogenesis.

Unveiling the Impact of ApoF Deficiency on Liver and Lipid Metabolism: Insights from Transcriptome-Wide m6A Methylome Analysis in Mice

Lipid metabolism participates in various physiological processes and has been shown to be connected to the development and progression of multiple diseases, especially metabolic hepatopathy. Apolipoproteins (Apos) act as vectors that combine with lipids, such as cholesterol and triglycerides (TGs). Despite being involved in lipid transportation and metabolism, the critical role of Apos in the maintenance of lipid metabolism has still not been fully revealed. This study sought to clarify variations related to m6A methylome in ApoF gene knockout mice with disordered lipid metabolism based on the bioinformatics method of transcriptome-wide m6A methylome epitranscriptomics. High-throughput methylated RNA immunoprecipitation sequencing (MeRIP-seq) was conducted in both wild-type (WT) and ApoF knockout (KO) mice. As a result, the liver histopathology presented vacuolization and steatosis, and the serum biochemical assays reported abnormal lipid content in KO mice. The m6A-modified mRNAs were conformed consensus sequenced in eukaryotes, and the distribution was enriched within the coding sequences and 3' non-coding regions. In KO mice, the functional annotation terms of the differentially expressed genes (DEGs) included cholesterol, steroid and lipid metabolism, and lipid storage. In the differentially m6A-methylated mRNAs, the functional annotation terms included cholesterol, TG, and long-chain fatty acid metabolic processes; lipid transport; and liver development. The overlapping DEGs and differential m6A-modified mRNAs were also enriched in terms of lipid metabolism disorder. In conclusion, transcriptome-wide MeRIP sequencing in ApoF KO mice demonstrated the role of this crucial apolipoprotein in liver health and lipid metabolism.

Neutrophil extracellular trap-associated risk index for predicting outcomes and response to Wnt signaling inhibitors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a type of breast cancer with poor prognosis, which is prone to distant metastasis and therapy resistance. The presence of neutrophil extracellular traps (NETs) contributes to the progression of breast cancer and is an efficient predictor of TNBC. We obtained the bulk and single-cell RNA sequencing data from public databases. Firstly, we identified five NET-related genes and constructed NET-related subgroups. Then, we constructed a risk index with three pivotal genes based on the differentially expressed genes between subgroups. Patients in the high-risk group had worse prognosis, clinicopathological features, and therapy response than low-risk group. Functional enrichment analysis revealed that the low-risk group was enriched in Wnt signaling pathway, and surprisingly, the drug sensitivity prediction showed that Wnt signaling pathway inhibitors had higher drug sensitivity in the low-risk group. Finally, verification experiments in vitro based on MDA-MB-231 and BT-549 cells showed that tumor cells with low-risk scores had less migration, invasion, and proliferative abilities and high drug sensitivity to Wnt signaling pathway inhibitors. In this study, multi-omics analysis revealed that genes associated with NETs may influence the occurrence, progression, and treatment of TNBC. Moreover, the bioinformatics analysis and cell experiments demonstrated that the risk index could predict the population of TNBC likely to benefit from treatment with Wnt signaling pathway inhibitors.

A High-Throughput Workflow for Mass Spectrometry Analysis of Nucleic Acids by Nanoflow Desalting

Broad interest in nucleic acids, both their therapeutic capabilities and understanding the nuances of their structure and resulting function, has increased in recent years. Post-transcriptional modifications, in particular, have become an important analysis target, as these covalent modifications to the sugars, nitrogenous bases, and phosphate backbone impart differential functionality to synthetic and biological nucleic acids. Characterizing these post-transcriptional modifications can be difficult with traditional sequencing workflows; however, advancements in top-down mass spectrometry address these challenges. Online desalting platforms have enabled facile sample cleanup and reliable ionization of increasingly large (100 nt) oligonucleotides, and application of existing tandem mass spectrometry techniques has yielded information-rich spectra which can be used to interrogate primary sequences. To extend the capabilities of top-down MS and its analysis of nucleic acids, we have developed a nanoflow desalting platform for high-throughput and low sample-use desalting coupled with collision-induced dissociation (CID), 213 nm ultraviolet photodissociation (UVPD), and activated-ion electron photodetachment dissociation (a-EPD) to yield high-quality MS/MS spectra. Fragments identified using an m/z-domain isotope matching strategy yielded high sequence coverage (>70%) of a yeast phenylalanine tRNA.

Exploring N6-methyladenosine (m6A) modification in tree species: opportunities and challenges

N 6-methyladenosine (m6A) in eukaryotes is the most common and widespread internal modification in mRNA. The modification regulates mRNA stability, translation efficiency, and splicing, thereby fine-tuning gene regulation. In plants, m6A is dynamic and critical for various growth stages, embryonic development, morphogenesis, flowering, stress response, crop yield, and biomass. Although recent high-throughput sequencing approaches have enabled the rapid identification of m6A modification sites, the site-specific mechanism of this modification remains unclear in trees. In this review, we discuss the functional significance of m6A in trees under different stress conditions and discuss recent advancements in the quantification of m6A. Quantitative and functional insights into the dynamic aspect of m6A modification could assist researchers in engineering tree crops for better productivity and resistance to various stress conditions.

PRMD: an integrated database for plant RNA modifications

The scope and function of RNA modifications in model plant systems have been extensively studied, resulting in the identification of an increasing number of novel RNA modifications in recent years. Researchers have gradually revealed that RNA modifications, especially N6-methyladenosine (m6A), which is one of the most abundant and commonly studied RNA modifications in plants, have important roles in physiological and pathological processes. These modifications alter the structure of RNA, which affects its molecular complementarity and binding to specific proteins, thereby resulting in various of physiological effects. The increasing interest in plant RNA modifications has necessitated research into RNA modifications and associated datasets. However, there is a lack of a convenient and integrated database with comprehensive annotations and intuitive visualization of plant RNA modifications. Here, we developed the Plant RNA Modification Database (PRMD; http://bioinformatics.sc.cn/PRMD and http://rnainformatics.org.cn/PRMD) to facilitate RNA modification research. This database contains information regarding 20 plant species and provides an intuitive interface for displaying information. Moreover, PRMD offers multiple tools, including RMlevelDiff, RMplantVar, RNAmodNet and Blast (for functional analyses), and mRNAbrowse, RNAlollipop, JBrowse and Integrative Genomics Viewer (for displaying data). Furthermore, PRMD is freely available, making it useful for the rapid development and promotion of research on plant RNA modifications.

m6A-Atlas v2.0: updated resources for unraveling the N6-methyladenosine (m6A) epitranscriptome among multiple species

N 6-Methyladenosine (m6A) is one of the most abundant internal chemical modifications on eukaryote mRNA and is involved in numerous essential molecular functions and biological processes. To facilitate the study of this important post-transcriptional modification, we present here m6A-Atlas v2.0, an updated version of m6A-Atlas. It was expanded to include a total of 797 091 reliable m6A sites from 13 high-resolution technologies and two single-cell m6A profiles. Additionally, three methods (exomePeaks2, MACS2 and TRESS) were used to identify >16 million m6A enrichment peaks from 2712 MeRIP-seq experiments covering 651 conditions in 42 species. Quality control results of MeRIP-seq samples were also provided to help users to select reliable peaks. We also estimated the condition-specific quantitative m6A profiles (i.e. differential methylation) under 172 experimental conditions for 19 species. Further, to provide insights into potential functional circuitry, the m6A epitranscriptomics were annotated with various genomic features, interactions with RNA-binding proteins and microRNA, potentially linked splicing events and single nucleotide polymorphisms. The collected m6A sites and their functional annotations can be freely queried and downloaded via a user-friendly graphical interface at: http://rnamd.org/m6a.

m7GHub V2.0: an updated database for decoding the N7-methylguanosine (m7G) epitranscriptome

With recent progress in mapping N7-methylguanosine (m7G) RNA methylation sites, tens of thousands of experimentally validated m7G sites have been discovered in various species, shedding light on the significant role of m7G modification in regulating numerous biological processes including disease pathogenesis. An integrated resource that enables the sharing, annotation and customized analysis of m7G data will greatly facilitate m7G studies under various physiological contexts. We previously developed the m7GHub database to host mRNA m7G sites identified in the human transcriptome. Here, we present m7GHub v.2.0, an updated resource for a comprehensive collection of m7G modifications in various types of RNA across multiple species: an m7GDB database containing 430 898 putative m7G sites identified in 23 species, collected from both widely applied next-generation sequencing (NGS) and the emerging Oxford Nanopore direct RNA sequencing (ONT) techniques; an m7GDiseaseDB hosting 156 206 m7G-associated variants (involving addition or removal of an m7G site), including 3238 disease-relevant m7G-SNPs that may function through epitranscriptome disturbance; and two enhanced analysis modules to perform interactive analyses on the collections of m7G sites (m7GFinder) and functional variants (m7GSNPer). We expect that m7Ghub v.2.0 should serve as a valuable centralized resource for studying m7G modification. It is freely accessible at: www.rnamd.org/m7GHub2.

Global RNA modifications to the MALAT1 triple helix differentially affect thermostability and weaken binding to METTL16

Therapeutic mRNAs are generated using modified nucleotides, namely N1-methylpseudouridine (m1Ψ) triphosphate, so that the mRNA evades detection by the immune system. RNA modifications, even at a single-nucleotide position, perturb RNA structure, although it is not well understood how structure and function is impacted by globally modified RNAs. Therefore, we examined the metastasis-associated lung adenocarcinoma transcript 1 triple helix, a highly structured stability element that includes single-, double-, and triple-stranded RNA, globally modified with N6-methyladenosine (m6A), pseudouridine (Ψ), or m1Ψ. UV thermal denaturation assays showed that m6A destabilizes both the Hoogsteen and Watson-Crick faces of the RNA by ∼20 °C, Ψ stabilizes the Hoogsteen and Watson-Crick faces of the RNA by ∼12 °C, and m1Ψ has minimal effect on the stability of the Hoogsteen face of the RNA but increases the stability of the Watson-Crick face by ∼9 °C. Native gel-shift assays revealed that binding of the methyltransferase-like protein 16 to the metastasis-associated lung adenocarcinoma transcript 1 triple helix was weakened by at least 8-, 99-, and 23-fold, respectively, when RNA is globally modified with m6A, Ψ, or m1Ψ. These results demonstrate that a more thermostable RNA structure does not lead to tighter RNA-protein interactions, thereby highlighting the regulatory power of RNA modifications by multiple means.

The functions and mechanisms of post-translational modification in protein regulators of RNA methylation: Current status and future perspectives

RNA methylation, an epigenetic modification that does not alter gene sequence, may be important to diverse biological processes. Protein regulators of RNA methylation include "writers," "erasers," and "readers," which respectively deposit, remove, and recognize methylated RNA. RNA methylation, particularly N6-methyladenosine (m6A), 5-methylcytosine (m5C), N3-methylcytosine (m3C), N1-methyladenosine (m1A) and N7-methylguanosine (m7G), has been suggested as disease therapeutic targets. Despite advances in the structure and pharmacology of RNA methylation regulators that have improved drug discovery, regulating these proteins by various post-translational modifications (PTMs) has received little attention. PTM modifies protein structure and function, affecting all aspects of normal biology and pathogenesis, including immunology, cell differentiation, DNA damage repair, and tumors. It is becoming evident that RNA methylation regulators are also regulated by diverse PTMs. PTM of RNA methylation regulators induces their covalent linkage to new functional groups, hence modifying their activity and function. Mass spectrometry has identified many PTMs on protein regulators of RNA methylation. In this review, we describe the functions and PTM of protein regulators of RNA methylation and summarize the recent advances in the regulatory mode of human disease and its underlying mechanisms.

DPred_3S: identifying dihydrouridine (D) modification on three species epitranscriptome based on multiple sequence-derived features

Introduction: Dihydrouridine (D) is a conserved modification of tRNA among all three life domains. D modification enhances the flexibility of a single nucleotide base in the spatial structure and is disease- and evolution-associated. Recent studies have also suggested the presence of dihydrouridine on mRNA. Methods: To identify D in epitranscriptome, we provided a prediction framework named "DPred_3S" based on the machine learning approach for three species D epitranscriptome, which used epitranscriptome sequencing data as training data for the first time. Results: The optimal features were evaluated by the F-score and integration of different features; our model achieved area under the receiver operating characteristic curve (AUROC) scores 0.955, 0.946, and 0.905 for Saccharomyces cerevisiae, Escherichia coli, and Schizosaccharomyces pombe, respectively. The performances of different machine learning algorithms were also compared in this study. Discussion: The high performances of our model suggest the D sites can be distinguished based on their surrounding sequence, but the lower performance of cross-species prediction may be limited by technique preferences.

Molecular Characterization and Establishment of a Prognostic Model Based on Primary Immunodeficiency Features in Association with RNA Modifications in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Although immunotherapy is effective for some patients, most find it difficult to benefit from it. This study aims to explore the impact of specific immune pathways and their regulated molecular mechanisms in TNBC. The gene expression data of breast cancer patients were obtained from the TCGA and METABRIC databases. Gene set variation analysis (GSVA) revealed specific upregulation or abnormal expression of immunodeficiency pathways in TNBC patients. Multi-omics data showed significant differential expression of Primary Immunodeficiency Genes (PIDGs) in TNBC patients, who are prone to genomic-level variations. Consensus clustering was used in two datasets to classify patients into two distinct molecular subtypes based on PIDGs expression patterns, with each displaying different biological features and immune landscapes. To further explore the prognostic characteristics of PIDGs-regulated molecules, we constructed a four-gene prognostic PIDG score model and a nomogram using least absolute shrinkage and selection operator (LASSO) regression analysis in combination with clinicopathological parameters. The PIDG score was closely associated with the immune therapy and drug sensitivity of TNBC patients, providing potential guidance for clinical treatment. Particularly noteworthy is the close association of this scoring with RNA modifications; patients with different scores also exhibited different mutation landscapes. This study offers new insights for the clinical treatment of TNBC and for identifying novel prognostic markers and therapeutic targets in TNBC.

m5U-GEPred: prediction of RNA 5-methyluridine sites based on sequence-derived and graph embedding features

5-Methyluridine (m5U) is one of the most common post-transcriptional RNA modifications, which is involved in a variety of important biological processes and disease development. The precise identification of the m5U sites allows for a better understanding of the biological processes of RNA and contributes to the discovery of new RNA functional and therapeutic targets. Here, we present m5U-GEPred, a prediction framework, to combine sequence characteristics and graph embedding-based information for m5U identification. The graph embedding approach was introduced to extract the global information of training data that complemented the local information represented by conventional sequence features, thereby enhancing the prediction performance of m5U identification. m5U-GEPred outperformed the state-of-the-art m5U predictors built on two independent species, with an average AUROC of 0.984 and 0.985 tested on human and yeast transcriptomes, respectively. To further validate the performance of our newly proposed framework, the experimentally validated m5U sites identified from Oxford Nanopore Technology (ONT) were collected as independent testing data, and in this project, m5U-GEPred achieved reasonable prediction performance with ACC of 91.84%. We hope that m5U-GEPred should make a useful computational alternative for m5U identification.

Shining a spotlight on m6A and the vital role of RNA modification in endometrial cancer: a review

RNA modifications are mostly dynamically reversible post-transcriptional modifications, of which m6A is the most prevalent in eukaryotic mRNAs. A growing number of studies indicate that RNA modification can finely tune gene expression and modulate RNA metabolic homeostasis, which in turn affects the self-renewal, proliferation, apoptosis, migration, and invasion of tumor cells. Endometrial carcinoma (EC) is the most common gynecologic tumor in developed countries. Although it can be diagnosed early in the onset and have a preferable prognosis, some cases might develop and become metastatic or recurrent, with a worse prognosis. Fortunately, immunotherapy and targeted therapy are promising methods of treating endometrial cancer patients. Gene modifications may also contribute to these treatments, as is especially the case with recent developments of new targeted therapeutic genes and diagnostic biomarkers for EC, even though current findings on the relationship between RNA modification and EC are still very limited, especially m6A. For example, what is the elaborate mechanism by which RNA modification affects EC progression? Taking m6A modification as an example, what is the conversion mode of methylation and demethylation for RNAs, and how to achieve selective recognition of specific RNA? Understanding how they cope with various stimuli as part of in vivo and in vitro biological development, disease or tumor occurrence and development, and other processes is valuable and RNA modifications provide a distinctive insight into genetic information. The roles of these processes in coping with various stimuli, biological development, disease, or tumor development in vivo and in vitro are self-evident and may become a new direction for cancer in the future. In this review, we summarize the category, characteristics, and therapeutic precis of RNA modification, m6A in particular, with the purpose of seeking the systematic regulation axis related to RNA modification to provide a better solution for the treatment of EC.

Combined signature of N7-methylguanosine regulators with their related genes and the tumor microenvironment: a prognostic and therapeutic biomarker for breast cancer

Background

Identifying predictive markers for breast cancer (BC) prognosis and immunotherapeutic responses remains challenging. Recent findings indicate that N7-methylguanosine (m7G) modification and the tumor microenvironment (TME) are critical for BC tumorigenesis and metastasis, suggesting that integrating m7G modifications and TME cell characteristics could improve the predictive accuracy for prognosis and immunotherapeutic responses.

Methods

We utilized bulk RNA-sequencing data from The Cancer Genome Atlas Breast Cancer Cohort and the GSE42568 and GSE146558 datasets to identify BC-specific m7G-modification regulators and associated genes. We used multiple m7G databases and RNA interference to validate the relationships between BC-specific m7G-modification regulators (METTL1 and WDR4) and related genes. Single-cell RNA-sequencing data from GSE176078 confirmed the association between m7G modifications and TME cells. We constructed an m7G-TME classifier, validated the results using an independent BC cohort (GSE20685; n = 327), investigated the clinical significance of BC-specific m7G-modifying regulators by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, and performed tissue-microarray assays on 192 BC samples.

Results

Immunohistochemistry and RT-qPCR results indicated that METTL1 and WDR4 overexpression in BC correlated with poor patient prognosis. Moreover, single-cell analysis revealed relationships between m7G modification and TME cells, indicating their potential as indicators of BC prognosis and treatment responses. The m7G-TME classifier enabled patient subgrouping and revealed significantly better survival and treatment responses in the m7Glow+TMEhigh group. Significant differences in tumor biological functions and immunophenotypes occurred among the different subgroups.

Conclusions

The m7G-TME classifier offers a promising tool for predicting prognosis and immunotherapeutic responses in BC, which could support personalized therapeutic strategies.

XGBoost framework with feature selection for the prediction of RNA N5-methylcytosine sites

5-methylcytosine (m5C) is indeed a critical post-transcriptional alteration that is widely present in various kinds of RNAs and is crucial to the fundamental biological processes. By correctly identifying the m5C-methylation sites on RNA, clinicians can more clearly comprehend the precise function of these m5C-sites in different biological processes. Due to their effectiveness and affordability, computational methods have received greater attention over the last few years for the identification of methylation sites in various species. To precisely identify RNA m5C locations in five different species including Homo sapiens, Arabidopsis thaliana, Mus musculus, Drosophila melanogaster, and Danio rerio, we proposed a more effective and accurate model named m5C-pred. To create m5C-pred, five distinct feature encoding techniques were combined to extract features from the RNA sequence, and then we used SHapley Additive exPlanations to choose the best features among them, followed by XGBoost as a classifier. We applied the novel optimization method called Optuna to quickly and efficiently determine the best hyperparameters. Finally, the proposed model was evaluated using independent test datasets, and we compared the results with the previous methods. Our approach, m5C- pred, is anticipated to be useful for accurately identifying m5C sites, outperforming the currently available state-of-the-art techniques.

The hidden RNA code: implications of the RNA epitranscriptome in the context of viral infections

Emerging evidence highlights the multifaceted roles of the RNA epitranscriptome during viral infections. By modulating the modification landscape of viral and host RNAs, viruses enhance their propagation and elude host surveillance mechanisms. Here, we discuss how specific RNA modifications, in either host or viral RNA molecules, impact the virus-life cycle and host antiviral responses, highlighting the potential of targeting the RNA epitranscriptome for novel antiviral therapies.

EMDL-ac4C: identifying N4-acetylcytidine based on ensemble two-branch residual connection DenseNet and attention

Introduction: N4-acetylcytidine (ac4C) is a critical acetylation modification that has an essential function in protein translation and is associated with a number of human diseases. Methods: The process of identifying ac4C sites by biological experiments is too cumbersome and costly. And the performance of several existing computational models needs to be improved. Therefore, we propose a new deep learning tool EMDL-ac4C to predict ac4C sites, which uses a simple one-hot encoding for a unbalanced dataset using a downsampled ensemble deep learning network to extract important features to identify ac4C sites. The base learner of this ensemble model consists of a modified DenseNet and Squeeze-and-Excitation Networks. In addition, we innovatively add a convolutional residual structure in parallel with the dense block to achieve the effect of two-layer feature extraction. Results: The average accuracy (Acc), mathews correlation coefficient (MCC), and area under the curve Area under curve of EMDL-ac4C on ten independent testing sets are 80.84%, 61.77%, and 87.94%, respectively. Discussion: Multiple experimental comparisons indicate that EMDL-ac4C outperforms existing predictors and it greatly improved the predictive performance of the ac4C sites. At the same time, EMDL-ac4C could provide a valuable reference for the next part of the study. The source code and experimental data are available at: https://github.com/13133989982/EMDLac4C.

Novel insight into RNA modifications in tumor immunity: Promising targets to prevent tumor immune escape

An immunosuppressive state is a typical feature of the tumor microenvironment. Despite the dramatic success of immune checkpoint inhibitor (ICI) therapy in preventing tumor cell escape from immune surveillance, primary and acquired resistance have limited its clinical use. Notably, recent clinical trials have shown that epigenetic drugs can significantly improve the outcome of ICI therapy in various cancers, indicating the importance of epigenetic modifications in immune regulation of tumors. Recently, RNA modifications (N⁶-methyladenosine [m⁶A], N¹-methyladenosine [m¹A], 5-methylcytosine [m⁵C], etc.), novel hotspot areas of epigenetic research, have been shown to play crucial roles in protumor and antitumor immunity. In this review, we provide a comprehensive understanding of how m⁶A, m¹A, and m⁵C function in tumor immunity by directly regulating different immune cells as well as indirectly regulating tumor cells through different mechanisms, including modulating the expression of immune checkpoints, inducing metabolic reprogramming, and affecting the secretion of immune-related factors. Finally, we discuss the current status of strategies targeting RNA modifications to prevent tumor immune escape, highlighting their potential.

Analyses of m6A regulatory genes and subtype classification in atrial fibrillation

Objective

To explore the role of m6A regulatory genes in atrial fibrillation (AF), we classified atrial fibrillation patients into subtypes by two genotyping methods associated with m6A regulatory genes and explored their clinical significance.

Methods

We downloaded datasets from the Gene Expression Omnibus (GEO) database. The m6A regulatory gene expression levels were extracted. We constructed and compared random forest (RF) and support vector machine (SVM) models. Feature genes were selected to develop a nomogram model with the superior model. We identified m6A subtypes based on significantly differentially expressed m6A regulatory genes and identified m6A gene subtypes based on m6A-related differentially expressed genes (DEGs). Comprehensive evaluation of the two m6A modification patterns was performed.

Results

The data of 107 samples from three datasets, GSE115574, GSE14975 and GSE41177, were acquired from the GEO database for training models, comprising 65 AF samples and 42 sinus rhythm (SR) samples. The data of 26 samples from dataset GSE79768 comprising 14 AF samples and 12 SR samples were acquired from the GEO database for external validation. The expression levels of 23 regulatory genes of m6A were extracted. There were correlations among the m6A readers, erasers, and writers. Five feature m6A regulatory genes, ZC3H13, YTHDF1, HNRNPA2B1, IGFBP2, and IGFBP3, were determined (p < 0.05) to establish a nomogram model that can predict the incidence of atrial fibrillation with the RF model. We identified two m6A subtypes based on the five significant m6A regulatory genes (p < 0.05). Cluster B had a lower immune infiltration of immature dendritic cells than cluster A (p < 0.05). On the basis of six m6A-related DEGs between m6A subtypes (p < 0.05), two m6A gene subtypes were identified. Both cluster A and gene cluster A scored higher than the other clusters in terms of m6A score computed by principal component analysis (PCA) algorithms (p < 0.05). The m6A subtypes and m6A gene subtypes were highly consistent.

Conclusion

The m6A regulatory genes play non-negligible roles in atrial fibrillation. A nomogram model developed by five feature m6A regulatory genes could be used to predict the incidence of atrial fibrillation. Two m6A modification patterns were identified and evaluated comprehensively, which may provide insights into the classification of atrial fibrillation patients and guide treatment.

Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy

Post-transcriptionally RNA modifications, also known as the epitranscriptome, play crucial roles in the regulation of gene expression during development. Recently, deep learning (DL) has been employed for RNA modification site prediction and has shown promising results. However, due to the lack of relevant studies, it is unclear which DL architecture is best suited for some pyrimidine modifications, such as 5-methyluridine (m⁵U). To fill this knowledge gap, we first performed a comparative evaluation of various commonly used DL models for epigenetic studies with the help of autoBioSeqpy. We identified optimal architectural variations for m⁵U site classification, optimizing the layer depth and neuron width. Second, we used this knowledge to develop Deepm5U, an improved convolutional-recurrent neural network that accurately predicts m⁵U sites from RNA sequences. We successfully applied Deepm5U to transcriptomewide m⁵U profiling data across different sequencing technologies and cell types. Third, we showed that the techniques for interpreting deep neural networks, including LayerUMAP and DeepSHAP, can provide important insights into the internal operation and behavior of models. Overall, we offered practical guidance for the development, benchmark, and analysis of deep learning models when designing new algorithms for RNA modifications.

Epitranscriptomics in the development, functions, and disorders of cancer stem cells

Biomolecular modifications play an important role in the development of life, and previous studies have investigated the role of DNA and proteins. In the last decade, with the development of sequencing technology, the veil of epitranscriptomics has been gradually lifted. Transcriptomics focuses on RNA modifications that affect gene expression at the transcriptional level. With further research, scientists have found that changes in RNA modification proteins are closely linked to cancer tumorigenesis, progression, metastasis, and drug resistance. Cancer stem cells (CSCs) are considered powerful drivers of tumorigenesis and key factors for therapeutic resistance. In this article, we focus on describing RNA modifications associated with CSCs and summarize the associated research progress. The aim of this review is to identify new directions for cancer diagnosis and targeted therapy.

Modification and Expression of mRNA m6A in the Lateral Habenular of Rats after Long-Term Exposure to Blue Light during the Sleep Period

Artificial lighting, especially blue light, is becoming a public-health risk. Excessive exposure to blue light at night has been reported to be associated with brain diseases. However, the mechanisms underlying neuropathy induced by blue light remain unclear. An early anatomical tracing study described the projection of the retina to the lateral habenula (LHb), whereas more mechanistic reports are available on multiple brain functions and neuropsychiatric disorders in the LHb, which are rarely seen in epigenetic studies, particularly N6-methyladenosine (m6A). The purpose of our study was to first expose Sprague-Dawley rats to blue light (6.11 ± 0.05 mW/cm2, the same irradiance as 200 lx of white light in the control group) for 4 h, and simultaneously provide white light to the control group for the same time to enter a sleep period. The experiment was conducted over 12 weeks. RNA m6A modifications and different mRNA transcriptome profiles were observed in the LHb. We refer to this experimental group as BLS. High-throughput MeRIP-seq and mRNA-seq were performed, and we used bioinformatics to analyze the data. There were 188 genes in the LHb that overlapped between differentially m6A-modified mRNA and differentially expressed mRNA. The Kyoto Encyclopedia of Genes and Genomes and gene ontology analysis were used to enrich neuroactive ligand-receptor interaction, long-term depression, the cyclic guanosine monophosphate-dependent protein kinase G (cGMP-PKG) signaling pathway, and circadian entrainment. The m6A methylation level of the target genes in the BLS group was disordered. In conclusion, this study suggests that the mRNA expression and their m6A of the LHb were abnormal after blue light exposure during the sleep period, and the methylation levels of target genes related to synaptic plasticity were disturbed. This study offers a theoretical basis for the scientific use of light.

Overview of distinct 5-methylcytosine profiles of messenger RNA in normal and knock-down NSUN2 colorectal cancer cells

Background: Colorectal cancer (CRC) is a harmful cancer with high morbidity and poor prognosis. There is growing evidence that RNA methylation is closely related to the occurrence of cancer and its malignant biological behavior. N6-methyladenosine (m⁶A) methylation is the most common RNA modification in eukaryotes, and its multiple regulatory mechanisms in CRC have been elucidated from multiple perspectives. At the same time, the role of 5-methylcytosine (m5C), another important and widely distributed methylation modification, in CRC is far from being elucidated. Methods: In this study, we used RNA immunoprecipitation sequencing combined with bioinformatics methods to identify the m5C peaks on messenger RNA (mRNA) in HCT15 cells and sh-NSUN2 HCT15 cells, understand which transcripts are modified by m5C, and characterize the distribution of m5C modifications. In addition, we performed further bioinformatics analysis of the detected data to initially clarify the potential function of these m5C-modified transcripts. Results: We found significant differences in the distribution of m5C between HCT15 cells and sh-NSUN2 HCT15 cells, suggesting that m5C is likely to play a key role in the occurrence and development of CRC. Furthermore, Gene Ontology (GO) enrichment analysis showed that genes altered by m5C were mainly enriched in phylogeny, synaptic membrane, and transcription factor binding. The Kyoto Encyclopedia of Genes and Genomes (KEGG)pathway analysis showed that the genes altered by m5C are enriched in ECM receptor interaction pathway, the circadian pathway, and the cAMP signaling pathway. Conclusion: Here, our study preliminarily revealed the different distribution patterns of m5C between HCT15 cell and sh-NSUN2 HCT15 cell. Our results open a new window to understand the role of m5C RNA methylation of mRNA in the development of CRC.

Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells

Aflatoxin B1 (AFB1) is widely prevalent in foods and animal feeds and is one of the most toxic and carcinogenic aflatoxin subtypes. Existing studies have proved that the intestine is targeted by AFB1, and adverse organic effects have been observed. This study aimed to investigate the relationship between AFB1-induced intestinal toxicity and N6-methyladenosine (m6A) RNA methylation, which involves the post-transcriptional regulation of mRNA expression. The transcriptome-wide m6A methylome and transcriptome profiles in human intestinal cells treated with AFB1 are presented. Methylated RNA immunoprecipitation sequencing and mRNA sequencing were carried out to determine the distinctions in m6A methylation and different genes expressed in AFB1-induced intestinal toxicity. The results showed that there were 2289 overlapping genes of the differentially expressed mRNAs and differentially m6A-methylation-modified mRNAs. After enrichment of the signaling pathways and biological processes, these genes participated in the terms of the cell cycle, endoplasmic reticulum, tight junction, and mitophagy. In conclusion, the study demonstrated that AFB1-induced HCT116 injury was related to the disruptions to the levels of m6A methylation modifications of target genes and the abnormal expression of m6A regulators.

RNA Epigenetics in Chronic Lung Diseases

Chronic lung diseases are highly prevalent worldwide and cause significant mortality. Lung cancer is the end stage of many chronic lung diseases. RNA epigenetics can dynamically modulate gene expression and decide cell fate. Recently, studies have confirmed that RNA epigenetics plays a crucial role in the developing of chronic lung diseases. Further exploration of the underlying mechanisms of RNA epigenetics in chronic lung diseases, including lung cancer, may lead to a better understanding of the diseases and promote the development of new biomarkers and therapeutic strategies. This article reviews basic information on RNA modifications, including N⁶ methylation of adenosine (m⁶A), N¹ methylation of adenosine (m¹A), N⁷-methylguanosine (m⁷G), 5-methylcytosine (m⁵C), 2'O-methylation (2'-O-Me or Nm), pseudouridine (5-ribosyl uracil or Ψ), and adenosine to inosine RNA editing (A-to-I editing). We then show how they relate to different types of lung disease. This paper hopes to summarize the mechanisms of RNA modification in chronic lung disease and finds a new way to develop early diagnosis and treatment of chronic lung disease.