m6A Reader: Epitranscriptome Target Prediction and Functional Characterization of N 6-Methyladenosine (m6A) Readers

2OM-Pred: prediction of 2-O-methylation sites in ribonucleic acid using diverse classifiers

2-O-methylation (2OM) is a vital post-transcriptional modification which is formed by a functional group through the attachment of a methyl (-CH3) group to the second position of an aromatic ring hydroxyl group (-OH). It plays an active part in RNA physical configuration stability and the way different RNA molecules interrelate. Further, this modification plays a pivotal role in changing the epigenetic regulation of cellular processes. Previous approaches like mass spectrometry could not fully enhance the identification of RNA-modified sites. Sequence data were useful in the development of measures that meant the use of computationally intelligent system to identify 2OM sites quickly. This research proposed a new novel method of feature extraction and generation from the available sequences, and the feature dimensionality reduction has been done through the incorporation of statistical moments. The final feature vectors were developed and used to train prediction models. The assessment of prediction models was carried out through independent set tests and k-fold cross-validation. Through rigorous testing, the bagging ensemble model outperformed and revealed optimal accuracy scores. A publicly accessible web-based application has been developed which can be accessed via https://2om-pred-webapp.streamlit.app/.

The mRNA N6-Methyladenosine Response to Dehydration in Xenopus laevis

The African clawed frog, Xenopus laevis, exhibits remarkable adaptations to survive in its arid habitat, including behavioral and metabolic changes during periods of drought. During extreme dehydration, X. laevis undergoes estivation, a state characterized by increased urea and ammonia levels, depression of the metabolic rate, and tissue hypoxia. To understand the molecular mechanisms underlying these adaptations, we investigated the potential role of N6-methyladenosine (m6A), a widespread mRNA modification, in X. laevis during extreme dehydration. We analyzed the protein levels of key components in the m6A pathway, including writers (METTL3, METTL14, and WTAP), erasers (ALKBH5 and FTO), and readers (SRSF3, YTHDF1, YTHDF2, YTHDF3, and eIF3a), in the liver and kidneys of control frogs and frogs that had lost 35 ± 0.93% of their total body water. The relative protein levels generally decreased or remained unchanged, with the exception of YTHDF3, which depicted a protein level increase in the liver. Notable changes included eIF3a, which was downregulated by 26 ± 8% and 80 ± 8% in the dehydrated liver and kidney tissues, respectively. Additionally, the total m6A increased by 353 ± 30% and 177 ± 17% in dehydrated liver and kidney RNA samples, respectively. This study highlights the importance of epigenetic mechanisms in stress tolerance and provides a foundation for further exploration of the role of epigenetics in dehydration tolerance.

Integrated Biochemical and Computational Methods for Deciphering RNA-Processing Codes

RNA processing involves steps such as capping, splicing, polyadenylation, modification, and nuclear export. These steps are essential for transforming genetic information in DNA into proteins and contribute to RNA diversity and complexity. Many biochemical methods have been developed to profile and quantify RNAs, as well as to identify the interactions between RNAs and RNA-binding proteins (RBPs), especially when coupled with high-throughput sequencing technologies. With the rapid accumulation of diverse data, it is crucial to develop computational methods to convert the big data into biological knowledge. In particular, machine learning and deep learning models are commonly utilized to learn the rules or codes governing the transformation from DNA sequences to intriguing RNAs based on manually designed or automatically extracted features. When precise enough, the RNA codes can be incredibly useful for predicting RNA products, decoding the molecular mechanisms, forecasting the impact of disease variants on RNA processing events, and identifying driver mutations. In this review, we systematically summarize the biochemical and computational methods for deciphering five important RNA codes related to alternative splicing, alternative polyadenylation, RNA localization, RNA modifications, and RBP binding. For each code, we review the main types of experimental methods used to generate training data, as well as the key features, strategic model structures, and advantages of representative tools. We also discuss the challenges encountered in developing predictive models using large language models and extensive domain knowledge. Additionally, we highlight useful resources and propose ways to improve computational tools for studying RNA codes.

Regulation of m6A (N6-Methyladenosine) methylation modifiers in solid cancers

Solid cancers constitute a tremendous burden on global healthcare, requiring a deeper understanding of the molecular mechanisms underlying cancer development and progression. Epigenetic changes, notably N6-methyladenosine (m6A) RNA methylation, have emerged as important contributors to the biology of solid tumors in recent years. This epigenetic mark dynamically affects gene expression at the post-transcriptional level and modulates a variety of cellular processes, making it a focus of research in the context of solid tumors. m6A modification patterns are dysregulated in a variety of solid cancers, including ovarian, breast, lung, colorectal, pancreatic, and others. This dysregulated m6A landscape has been shown to induce significant changes in the expression of oncogenes, tumor suppressors, and genes involved in cancer stem cells, metastasis, and treatment resistance. In solid tumors, the interaction of m6A "writers" (e.g., METTL3, METTL14, and others), "erasers" (e.g., ALKBH5, FTO), and "readers" (e.g., members of YTHDF proteins and others) delicately changes the m6A methylome. Targeting m6A regulators as a potential therapeutic method to control gene expression and prevent tumor development seems a novel strategy. To enhance treatment results, advances in this area of research have led to the development of targeted treatments aiming at restoring or altering m6A alteration patterns in solid tumors.

Identification of m6A RNA methylation genes in Oryza sativa and expression profiling in response to different developmental and environmental stimuli

Eukaryotic messenger RNAs (mRNAs) transcend their predominant function of protein encoding by incorporating auxiliary components that ultimately contribute to their processing, transportation, translation, and decay. In doing so, additional layers of modifications are incorporated in mRNAs at post-transcriptional stage. Among them, N6-methyladenosine (m6A) is the most frequently found mRNA modification that plays crucial roles in plant development and stress response. In the overall mechanism of m6A methylation, key proteins classified based on their functions such as writers, readers, and erasers dynamically add, read, and subtract methyl groups respectively to deliver relevant functions in response to external stimuli. In this study, we identified 30 m6A regulatory genes (9 writers, 5 erasers, and 16 readers) in rice that encode 53 proteins (13 writers, 7 erasers, and 33 readers) where segmental duplication was found in one writer and four reader gene pairs. Reproductive cells such as sperm, anther and panicle showed high levels of expression for most of the m6A regulatory genes. Notably, writers like OsMTA, OsMTD, and OsMTC showed varied responses in different stress and infection contexts, with initial upregulation in response to early exposure followed by downregulation later. OsALKBH9A, a noteworthy eraser, displayed varied expression in response to different stresses at different time intervals, but upregulation in certain infections. Reader genes like OsECT5, OsCPSF30-L3, and OsECT8 showed continuous upregulation in exertion of all kinds of stress relevant here. Conversely, other reader genes along with OsECT11 and OsCPSF30-L2 were observed to be consistently downregulated. The apparent correlation between the expression patterns of m6A regulatory genes and stress modulation pathways in this study underscores the need for additional research to unravel their intricate regulatory mechanisms that could ultimately contribute to the substantial development of enhanced stress tolerance in rice through mRNA modification.

METTL3 promotes osteogenic differentiation of human umbilical cord mesenchymal stem cells by up-regulating m6A modification of circCTTN

BACKGROUND

Human umbilical cord mesenchymal stem cells (hUCMSCs) are promising seed cells in bone tissue engineering. circRNA and N6-methyladenosine (m6A) RNA methylation play important roles in osteogenic differentiation. Here, we investigated the potential relevance of a critical circRNA, hsa_circ_0003376 (circCTTN), and methyltransferase-like 3 (METTL3) in osteogenic differentiation of hUCMSCs.

METHODS

Expression of circCTTN after hUCMSC osteogenic induction was detected by qRT-PCR. Three databases (RMBase v2.0, BERMP, and SRAMP) were used to predict m6A sites of circCTTN. RNA was enriched by methylated RNA immunoprecipitation (MeRIP), followed by quantitative real-time polymerase chain reaction to detect m6A level of circCTTN after METTL3 overexpression and osteogenic induction. RNA pull-down, Western blotting, and protein mass spectrometry were performed to investigate the potential mechanisms by which METTL3 promoted m6A modification of circCTTN. Bioinformatic analyses based on database (STRING) search and co-immunoprecipitation were used to analyze the proteins that interacted with METTL3.

RESULTS

Overexpression of METTL3 promoted osteogenic differentiation of hUCMSCs and increased m6A level of circCTTN. Two potential m6A modification sites of circCTTN were predicted. No direct interaction between METTL3 and circCTTN was observed. Thirty-one proteins were pulled down by probes specific for circCTTN, including NOP2, and two m6A reading proteins, EIF3A and SND1. Bioinformatics analysis and co-immunoprecipitation showed that METTL3 interacted with EIF3A indirectly through NOP2.

CONCLUSIONS

METTL3 promotes the osteogenic differentiation of hUCMSCs by increasing the m6A level of circCTTN. However, METTL3 does not bind directly to circCTTN. METTL3 interacts with circCTTN indirectly through NOP2 and EIF3A.

Epigenetic Restriction Factors (eRFs) in Virus Infection

The ongoing arms race between viruses and their hosts is constantly evolving. One of the ways in which cells defend themselves against invading viruses is by using restriction factors (RFs), which are cell-intrinsic antiviral mechanisms that block viral replication and transcription. Recent research has identified a specific group of RFs that belong to the cellular epigenetic machinery and are able to restrict the gene expression of certain viruses. These RFs can be referred to as epigenetic restriction factors or eRFs. In this review, eRFs have been classified into two categories. The first category includes eRFs that target viral chromatin. So far, the identified eRFs in this category include the PML-NBs, the KRAB/KAP1 complex, IFI16, and the HUSH complex. The second category includes eRFs that target viral RNA or, more specifically, the viral epitranscriptome. These epitranscriptomic eRFs have been further classified into two types: those that edit RNA bases-adenosine deaminase acting on RNA (ADAR) and pseudouridine synthases (PUS), and those that covalently modify viral RNA-the N6-methyladenosine (m6A) writers, readers, and erasers. We delve into the molecular machinery of eRFs, their role in limiting various viruses, and the mechanisms by which viruses have evolved to counteract them. We also examine the crosstalk between different eRFs, including the common effectors that connect them. Finally, we explore the potential for new discoveries in the realm of epigenetic networks that restrict viral gene expression, as well as the future research directions in this area.

Bromodomain-Containing Protein 9 Regulates Signaling Pathways and Reprograms the Epigenome in Immortalized Human Uterine Fibroid Cells

Bromodomain-containing proteins (BRDs) are involved in many biological processes, most notably epigenetic regulation of transcription, and BRD dysfunction has been linked to many diseases, including tumorigenesis. However, the role of BRDs in the pathogenesis of uterine fibroids (UFs) is entirely unknown. The present study aimed to determine the expression pattern of BRD9 in UFs and matched myometrium and further assess the impact of a BRD9 inhibitor on UF phenotype and epigenetic/epitranscriptomic changes. Our studies demonstrated that the levels of BRD9 were significantly upregulated in UFs compared to matched myometrium, suggesting that the aberrant BRD expression may contribute to the pathogenesis of UFs. We then evaluated the potential roles of BRD9 using its specific inhibitor, I-BRD9. Targeted inhibition of BRD9 suppressed UF tumorigenesis with increased apoptosis and cell cycle arrest, decreased cell proliferation, and extracellular matrix deposition in UF cells. The latter is the key hallmark of UFs. Unbiased transcriptomic profiling coupled with downstream bioinformatics analysis further and extensively demonstrated that targeted inhibition of BRD9 impacted the cell cycle- and ECM-related biological pathways and reprogrammed the UF cell epigenome and epitranscriptome in UFs. Taken together, our studies support the critical role of BRD9 in UF cells and the strong interconnection between BRD9 and other pathways controlling the UF progression. Targeted inhibition of BRDs might provide a non-hormonal treatment option for this most common benign tumor in women of reproductive age.

RNA m6A methylation regulators in liver cancer

Liver cancer is one of the most common cancers in the world and a primary cause of cancer-related death. In recent years, despite the great development of diagnostic methods and targeted therapies for liver cancer, the incidence and mortality of liver cancer are still on the rise. As a universal post-transcriptional modification, N6-methyladenosine (m6A) modification accomplishes a dynamic and reversible m6A modification process, which is executed by three types of regulators, methyltransferases (called writers), demethylases (called erasers) and m6A-binding proteins (called readers). Many studies have shown that m6A RNA methylation has an important impact on RNA metabolism, whereas its regulation exception is bound up with the occurrence of human malignant tumors. Aberrant methylation of m6A RNA and the expression of related regulatory factors may be of the essence in the pathogenesis and progression of liver cancer, yet the precise molecular mechanism remains unclear. In this paper, we review the current research situations of m6A methylation in liver cancer. Among the rest, we detail the mechanism by which methyltransferases, demethylases and m6A binding proteins regulate the occurrence and development of liver cancer by modifying mRNA. As well as the potential effect of m6A regulators in hepatocarcinogenesis and progression. New ideas and approaches will be given to the prevention and treatment of liver cancer through the following relevant research results.

RNA m6A reader YTHDF2 facilitates precursor miR-126 maturation to promote acute myeloid leukemia progression

As the most common internal modification of mRNA, N6-methyladenosine (m6A) and its regulators modulate gene expression and play critical roles in various biological and pathological processes including tumorigenesis. It was reported previously that m6A methyltransferase (writer), methyltransferase-like 3 (METTL3) adds m6A in primary microRNAs (pri-miRNAs) and facilitates its processing into precursor miRNAs (pre-miRNAs). However, it is unknown whether m6A modification also plays a role in the maturation process of pre-miRNAs and (if so) whether such a function contributes to tumorigenesis. Here, we found that YTHDF2 is aberrantly overexpressed in acute myeloid leukemia (AML) patients, especially in relapsed patients, and plays an oncogenic role in AML. Moreover, YTHDF2 promotes expression of miR-126-3p (also known as miR-126, as it is the main product of precursor miR-126 (pre-miR-126)), a miRNA that was reported as an oncomiRNA in AML, through facilitating the processing of pre-miR-126 into mature miR-126. Mechanistically, YTHDF2 recognizes m6A modification in pre-miR-126 and recruits AGO2, a regulator of pre-miRNA processing, to promote the maturation of pre-miR-126. YTHDF2 positively and negatively correlates with miR-126 and miR-126's downstream target genes, respectively, in AML patients, and forced expression of miR-126 could largely rescue YTHDF2/Ythdf2 depletion-mediated suppression on AML cell growth/proliferation and leukemogenesis, indicating that miR-126 is a functionally important target of YTHDF2 in AML. Overall, our studies not only reveal a previously unappreciated YTHDF2/miR-126 axis in AML and highlight the therapeutic potential of targeting this axis for AML treatment, but also suggest that m6A plays a role in pre-miRNA processing that contributes to tumorigenesis.

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.

The predictive significance of a 5-m6A RNA methylation regulator signature in colorectal cancer

Colorectal cancer attacks the colon or rectum, with increasing morbidity and mortality globally. The RNA modification 6-methyladenine (m6A) is related to RNA modifications, playing a critical role in colorectal cancer. We aimed to identify prognostic signatures for colorectal cancer using risk prediction algorithms, and to validate these signatures using independent datasets and clinical samples. In this study, 175 cases in GSE17536 were assigned into two clusters using consistent clustering and PCA analysis. A multivariate Cox risk regression model revealed that among 21 m6A RNA methylation regulators, RBM15B, FTO, IGF2BP2, ZCCHC4, and KIAA1429 were remarkably associated with colorectal cancer patients' overall survival (OS); however, Kaplan-Meier (KM) survival assessment showed no significant association between these five regulators and colorectal cancer patients' prognosis. A 5-m6A RNA methylation regulator signature was established using LASSO algorithm. Risk scores of cases in GSE17536, GSE17537 and GSE75500 were calculated, and lower risk scores were associated with better DSS/OS. receiver operating characteristic (ROC) curve and the nomogram revealed the satisfactory predictive efficiency of the risk score model. The risk score could distinguish cases in Cluster1 and Cluster2 and normal and tumor tissues based on GSE37182. The prognostic variables for colorectal cancer patients were assessed using both univariate and multivariate Cox's proportional hazard regression models, which revealed that the stage and risk score were significant risk factors. In this study, a comprehensive set of integrative bioinformatics analyses was conducted to investigate the prognostic and diagnostic potential of a panel of 5 m6A RNA methylated regulators in colorectal cancer patients. The conducted studies included the use of several statistical methods, such as the LASSO regression model, KM survival evaluation, ROC curve, and univariate and multivariate Cox's proportional hazard regression analyses. The findings from these analyses collectively established the prognostic marker, highlighting its significance in predicting patient outcomes and diagnosing colorectal cancer.

The RNA m6A modification might participate in microglial activation during hypoxic-ischemic brain damage in neonatal mice

BACKGROUND

The RNA m6A modification has been implicated in multiple neurological diseases as well as macrophage activation. However, whether it regulates microglial activation during hypoxic-ischemic brain damage (HIBD) in neonates remains unknown. Here, we aim to examine whether the m6A modification is involved in modulating microglial activation during HIBD. We employed an oxygen and glucose deprivation microglial model for in vitro studies and a neonatal mouse model of HIBD. The brain tissue was subjected to RNA-seq to screen for significant changes in the mRNA m6A regulator. Thereafter, we performed validation and bioinformatics analysis of the major m6A regulators.

RESULTS

RNA-seq analysis revealed that, among 141 m6A regulators, 31 exhibited significant differential expression (FC (abs) ≥ 2) in HIBD mice. We then subjected the major m6A regulators Mettl3, Mettl14, Fto, Alkbh5, Ythdf1, and Ythdf2 to further validation, and the results showed that all were significantly downregulated in vitro and in vivo. GO analysis reveals that regulators are mainly involved in the regulation of cellular and metabolic processes. The KEGG results indicate the involvement of the signal transduction pathway.

CONCLUSIONS

Our findings demonstrate that m6A modification of mRNA plays a crucial role in the regulation of microglial activation in HIBD, with m6A-associated regulators acting as key modulators of microglial activation.

Modulation of translational decoding by m6A modification of mRNA

N6-methyladenosine (m6A) is an abundant, dynamic mRNA modification that regulates key steps of cellular mRNA metabolism. m6A in the mRNA coding regions inhibits translation elongation. Here, we show how m6A modulates decoding in the bacterial translation system using a combination of rapid kinetics, smFRET and single-particle cryo-EM. We show that, while the modification does not impair the initial binding of aminoacyl-tRNA to the ribosome, in the presence of m6A fewer ribosomes complete the decoding process due to the lower stability of the complexes and enhanced tRNA drop-off. The mRNA codon adopts a π-stacked codon conformation that is remodeled upon aminoacyl-tRNA binding. m6A does not exclude canonical codon-anticodon geometry, but favors alternative more dynamic conformations that are rejected by the ribosome. These results highlight how modifications outside the Watson-Crick edge can still interfere with codon-anticodon base pairing and complex recognition by the ribosome, thereby modulating the translational efficiency of modified mRNAs.

Characterization of epitranscriptome reader proteins experimentally and in silico: Current knowledge and future perspectives beyond the YTH domain

To date, over 150 chemical modifications to the four canonical RNA bases have been discovered, known collectively as the epitranscriptome. Many of these modifications have been implicated in a variety of cellular processes and disease states. Additional work has been done to identify proteins known as "readers" that selectively interact with RNAs that contain specific chemical modifications. Protein interactomes with N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), N5-methylcytosine (m⁵C), and 8-oxo-7,8-dihydroguanosine (8-oxoG) have been determined, mainly through experimental advances in proteomics techniques. However, relatively few proteins have been confirmed to bind directly to RNA containing these modifications. Furthermore, for many of these protein readers, the exact binding mechanisms as well as the exclusivity for recognition of modified RNA species remain elusive, leading to questions regarding their roles within different cellular processes. In the case of the YT-521B homology (YTH) family of proteins, both experimental and in silico techniques have been leveraged to provide valuable biophysical insights into the mechanisms of m⁶A recognition at atomic resolution. To date, the YTH family is one of the best characterized classes of readers. Here, we review current knowledge about epitranscriptome recognition of the YTH domain proteins from previously published experimental and computational studies. We additionally outline knowledge gaps for proteins beyond the well-studied human YTH domains and the current in silico techniques and resources that can enable investigation of protein interactions with modified RNA outside of the YTH-m⁶A context.

Random Forest model reveals the interaction between N6-methyladenosine modifications and RNA-binding proteins

RNA-binding proteins (RBPs) have critical roles in N6-methyladenosine (m6A) modification process. We designed a Random Forest (RF) model to systematically analyze the interaction among RBPs and m6A modifications by integrating the binding signals from hundreds of RBPs. Accurate prediction of m6A sites demonstrated significant connections between RBP bindings and m6A modifications. The relative importance of different RBPs from the model provided a quantitative metric to evaluate their interactions with m6A modifications. Redundancy analysis showed that several RBPs may have similar binding patterns with m6A sites. The RF model exhibited fairly high prediction accuracy across cell lines, suggesting a conservative RBP interaction network regulates m6A occupancy. Specific RBPs can engage to the corresponding regional m6A sites and deploy distinct regulatory processes, such as cleavage site selection of the alternative polyadenylation (APA). We also integrated histone modifications into our RF model, which demonstrated H3K36me3 and H3K27me3 as determining features for m6A distribution.

Characterization of m6A methylation modifications and tumor microenvironment infiltration in thyroid cancer

BACKGROUND

Thyroid cancer (TC) is the most common endocrine malignancy worldwide, and immunotherapy is a new cancer treatment that stimulates and enhances the natural ability of the immune system to fight cancer cells. The role of RNA N6-methyladenosine (m6A) related genes in these challenges has recently become a research hotspot, but he potential role of m6A modifications in tumor microenvironment (TME) cell infiltration remains unknown.

PURPOSE

There is growing evidence that m6A plays a critical role in the regulation of gene expression by participating in important biological processes. A comprehensive analysis of the m6A regulator-mediated infiltration characteristics of the TME will help advance the understanding of immune regulation in thyroid tumors.

METHODS

This study assessed m6A modification modes in 510 thyroid cancer samples from the Cancer Genome Atlas (TCGA) databases according to a comprehensive set of 24 m6A regulators. In this study, we analyzed the biological characteristics and m6A methylation modification patterns. Based on this, we constructed m6A signatures and analyzed m6A modification features in tumor somatic mutations and TCGA molecular subtypes.

RESULTS

These modification modes were systematically linked to TME cell infiltration signatures. m6A modification patterns were comprehensively assessed and correlated with immune cell infiltration features in the TME. An unsupervised clustering approach was applied and three distinct m6A modification subtypes and three m6A-associated gene subtypes were identified. Additionally, three distinct m6A methylation modification modes were identified in the thyroid cancer samples. The TME profiles of the identified genetic subtypes were strongly congruent with the immuno-heat and immuno-cold phenotypes.

CONCLUSIONS

The results revealed that m6A modifications play an integral role in the diversity and complexity of thyroid carcinomas. Evaluating the m6A modification patterns of individual tumors will create more efficient immunotherapeutic strategies. A comprehensive analysis of the role of TME in thyroid cancer provides a research idea for studying the effect of m6A epigenetics on thyroid tumors and their immune microenvironment.

Dynamic regulation and key roles of ribonucleic acid methylation

Ribonucleic acid (RNA) methylation is the most abundant modification in biological systems, accounting for 60% of all RNA modifications, and affects multiple aspects of RNA (including mRNAs, tRNAs, rRNAs, microRNAs, and long non-coding RNAs). Dysregulation of RNA methylation causes many developmental diseases through various mechanisms mediated by N ⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C), N ¹-methyladenosine (m¹A), 5-hydroxymethylcytosine (hm⁵C), and pseudouridine (Ψ). The emerging tools of RNA methylation can be used as diagnostic, preventive, and therapeutic markers. Here, we review the accumulated discoveries to date regarding the biological function and dynamic regulation of RNA methylation/modification, as well as the most popularly used techniques applied for profiling RNA epitranscriptome, to provide new ideas for growth and development.

Interaction preferences between protein side chains and key epigenetic modifications 5-methylcytosine, 5-hydroxymethycytosine and N6-methyladenine

Covalent modifications of standard DNA/RNA nucleobases affect epigenetic regulation of gene expression by modulating interactions between nucleic acids and protein readers. We derive here the absolute binding free energies and analyze the binding modalities between key modified nucleobases 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) and N⁶-methyladenine (m⁶A) and all non-prolyl/non-glycyl protein side chains using molecular dynamics simulations and umbrella sampling in both water and methanol, the latter mimicking the low dielectric environment at the dehydrated nucleic-acid/protein interfaces. We verify the derived affinities by comparing against a comprehensive set of high-resolution structures of nucleic-protein complexes involving 5mC. Our analysis identifies protein side chains that are highly tuned for detecting cytosine methylation as a function of the environment and can thus serve as microscopic readers of epigenetic marks. Conversely, we show that the relative ordering of sidechain affinities for 5hmC and m⁶A does not differ significantly from those for their precursor bases, cytosine and adenine, respectively, especially in the low dielectric environment. For those two modified bases, the effect is more nuanced and manifests itself primarily at the level of absolute changes in the binding free energy. Our results contribute towards establishing a quantitative foundation for understanding, predicting and modulating the interactions between modified nucleic acids and proteins at the atomistic level.

RNA m6 A methylation in cancer

N⁶ -methyladenosine (m⁶ A) is one of the most abundant internal modifications in eukaryotic messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs). It is a reversible and dynamic RNA modification that has been observed in both internal coding segments and untranslated regions. Studies indicate that m⁶ A modifications play important roles in translation, RNA splicing, export, degradation and ncRNA processing control. In this review, we focus on the profiles and biological functions of RNA m⁶ A methylation on both mRNAs and ncRNAs. The dynamic modification of m⁶ A and its potential roles in cancer development are discussed. Moreover, we discuss the possibility of m⁶ A modifications serving as potential biomarkers for cancer diagnosis and targets for therapy.

Advances in detecting N6-methyladenosine modification in circRNAs

Circular RNAs (circRNAs) are a class of noncoding RNAs with covalently single-stranded closed loop structures derived from back-splicing event of linear precursor mRNAs (pre-mRNAs). N6-methyladenosine (m⁶A), the most abundant epigenetic modification in eukaryotic RNAs, has been shown to play a crucial role in regulating the fate and biological function of circRNAs, and thus affecting various physiological and pathological processes. Accurate identification of m⁶A modification in circRNAs is an essential step to fully elucidate the crosstalk between m⁶A and circRNAs. In recent years, the rapid development of high-throughput sequencing technology and bioinformatic methodology has propelled the establishment of a multitude of approaches to detect circRNAs and m⁶A modification, including in vitro-based and in silico methods. Based on this, the research community has started on a new journey to develop methods for identification of m⁶A modification in circRNAs. In this review, we provide a comprehensive review and evaluation of the existing methods responsible for detecting circRNAs, m⁶A modification, and especially, m⁶A modification in circRNAs, which mainly focused on those developed based on high-throughput technologies and methodology of bioinformatics. This handy reference can help researchers figure out towards which direction this field will go.

The Epitranscriptome in miRNAs: Crosstalk, Detection, and Function in Cancer

The epitranscriptome encompasses all post-transcriptional modifications that occur on RNAs. These modifications can alter the function and regulation of their RNA targets, which, if dysregulated, result in various diseases and cancers. As with other RNAs, miRNAs are highly modified by epitranscriptomic modifications such as m6A methylation, 2'-O-methylation, m5C methylation, m7G methylation, polyuridine, and A-to-I editing. miRNAs are a class of small non-coding RNAs that regulates gene expression at the post-transcriptional level. miRNAs have gathered high clinical interest due to their role in disease, development, and cancer progression. Epitranscriptomic modifications alter the targeting, regulation, and biogenesis of miRNAs, increasing the complexity of miRNA regulation. In addition, emerging studies have revealed crosstalk between these modifications. In this review, we will summarize the epitranscriptomic modifications-focusing on those relevant to miRNAs-examine the recent crosstalk between these modifications, and give a perspective on how this crosstalk expands the complexity of miRNA biology.

Role of m6A Methylation in the Occurrence and Development of Heart Failure

N6-methyladenosine (m6A) RNA methylation is one of the most common epigenetic modifications in RNA nucleotides. It is known that m6A methylation is involved in regulation, including gene expression, homeostasis, mRNA stability and other biological processes, affecting metabolism and a variety of biochemical regulation processes, and affecting the occurrence and development of a variety of diseases. Cardiovascular disease has high morbidity, disability rate and mortality in the world, of which heart failure is the final stage. Deeper understanding of the potential molecular mechanism of heart failure and exploring more effective treatment strategies will bring good news to the sick population. At present, m6A methylation is the latest research direction, which reveals some potential links between epigenetics and pathogenesis of heart failure. And m6A methylation will bring new directions and ideas for the prevention, diagnosis and treatment of heart failure. The purpose of this paper is to review the physiological and pathological mechanisms of m6A methylation that may be involved in cardiac remodeling in heart failure, so as to explain the possible role of m6A methylation in the occurrence and development of heart failure. And we hope to help m6A methylation obtain more in-depth research in the occurrence and development of heart failure.

The m6A reader YTHDC2 is essential for escape from KSHV SOX-induced RNA decay

The role of N6-methyladenosine (m6A) modifications has increasingly been associated with a diverse set of roles in modulating viruses and influencing the outcomes of viral infection. Here, we report that the landscape of m6A deposition is drastically shifted during Kaposi's sarcoma-associated herpesvirus (KSHV) lytic infection for both viral and host transcripts. In line with previous reports, we also saw an overall decrease in host methylation in favor of viral messenger RNA (mRNA), along with 5' hypomethylation and 3' hypermethylation. During KSHV lytic infection, a major shift in overall mRNA abundance is driven by the viral endoribonuclease SOX, which induces the decay of greater than 70% of transcripts. Here, we reveal that interlukin-6 (IL-6) mRNA, a well-characterized, SOX-resistant transcript, is m6A modified during lytic infection. Furthermore, we show that this modification falls within the IL-6 SOX resistance element, an RNA element in the IL-6 3' untranslated region (UTR) that was previously shown to be sufficient for protection from SOX cleavage. We show that the presence of this m6A modification is essential to confer SOX resistance to the IL-6 mRNA. We next show that this modification recruits the m6A reader YTHDC2 and found that YTHDC2 is necessary for the escape of the IL-6 transcript. These results shed light on how the host cell has evolved to use RNA modifications to circumvent viral manipulation of RNA fate during KSHV infection.

m6A-Maize: Weakly supervised prediction of m6A-carrying transcripts and m6A-affecting mutations in maize (Zea mays)

With the rapid development of high-throughput sequencing techniques nowadays, extensive attention has been paid to epitranscriptomics, which covers more than 150 distinct chemical modifications to date. Among that, N6-methyladenosine (m⁶A) modification has the most abundant existence, and it is also significantly related to varieties of biological processes. Meanwhile, maize is the most important food crop and cultivated throughout the world. Therefore, the study of m⁶A modification in maize has both economic and academic value. In this research, we proposed a weakly supervised learning model to predict the situation of m⁶A modification in maize. The proposed model learns from low-resolution epitranscriptome datasets (e.g., MeRIP-seq), which predicts the m⁶A methylation status of given fragments or regions. By taking advantage of our prediction model, we further identified traits-associated SNPs that may affect (add or remove) m⁶A modifications in maize, which may provide potential regulatory mechanisms at epitranscriptome layer. Additionally, a centralized online-platform was developed for m⁶A study in maize, which contains 58,838 experimentally validated maize m⁶A-containing regions including training and testing datasets, and a database for 2,578 predicted traits-associated m⁶A-affecting maize mutations. Furthermore, the online web server based on proposed weakly supervised model is available for predicting putative m⁶A sites from user-uploaded maize sequences, as well as accessing the epitranscriptome impact of user-interested maize SNPs on m⁶A modification. In all, our work provided a useful resource for the study of m⁶A RNA methylation in maize species. It is freely accessible at www.xjtlu.edu.cn/biologicalsciences/maize.

Machine learning applications in RNA modification sites prediction

Ribonucleic acid (RNA) modifications are post-transcriptional chemical composition changes that have a fundamental role in regulating the main aspect of RNA function. Recently, large datasets have become available thanks to the recent development in deep sequencing and large-scale profiling. This availability of transcriptomic datasets has led to increased use of machine learning based approaches in epitranscriptomics, particularly in identifying RNA modifications. In this review, we comprehensively explore machine learning based approaches used for the prediction of 11 RNA modification types, namely,m 1 A ,m 6 A ,m 5 C , 5 hmC , ψ , 2 ' - O - Me , ac 4 C ,m 7 G , A - to - I ,m 2 G , and D . This review covers the life cycle of machine learning methods to predict RNA modification sites including available benchmark datasets, feature extraction, and classification algorithms. We compare available methods in terms of datasets, target species, approach, and accuracy for each RNA modification type. Finally, we discuss the advantages and limitations of the reviewed approaches and suggest future perspectives.

RNA m6A methyltransferase METTL3 promotes colorectal cancer cell proliferation and invasion by regulating Snail expression

Nitrogen 6-methyladenosine (m⁶A) is the result of methylation of nitrogen-6 on adenosine, and is the most abundant chemical modification of eukaryotic mRNA. Dysregulation of m⁶A methylation has been implicated in cancer development and progression through various mechanisms. This type of methylation is primarily regulated by methyltransferase-like 3 (METTL3). However, the molecular mechanisms underlying the role of METTL3 in colorectal cancer (CRC) have not been extensively elucidated. The present study explored m⁶A modification and the underlying mechanism of m⁶A, which serve regulatory roles in the development of CRC. It was found that METTL3 is upregulated in CRC cell lines and tissues, and its expression positively correlated with poor overall survival (OS). Mechanistically, the present study demonstrated that METTL3 methylates Snail mRNA, thus stabilizing it to promote CRC malignancy. The present findings indicate that m⁶A modification is involved in CRC tumorigenesis, and highlight its potential as a therapeutic target against CRC.

m6A Regulator-Associated Modification Patterns and Immune Infiltration of the Tumor Microenvironment in Hepatocarcinoma

Background: Immunotherapy elicits durable responses in many tumors. Nevertheless, the positive response to immunotherapy always depends on the dynamic interactions between the tumor cells and infiltrating lymphocytes in the tumor microenvironment (TME). Currently, the application of immunotherapy in hepatocellular carcinoma (HCC) has achieved limited success. The ectopic modification of N6-methyladenosine (m6A) is a common feature in multiple tumors. However, the relationship between m6A modification with HCC clinical features, prognosis, immune cell infiltration, and immunotherapy efficacy remains unclear.

Materials and Methods: Here, we comprehensively evaluated m6A modification clusters based on 22 m6A regulators and systematically explored the relationship between m6A modification with tumor progression, prognosis, and immune cell infiltration characteristics. The m6Ascore was calculated by principal component analysis to quantify the m6A modifications of individual patients. Key regulators involved in immunoregulation in HCC were identified using immunohistochemistry and immunofluorescence.

Results: Three distinct m6A modification clusters were identified. The m6A clusters were significantly associated with clinical features, prognosis, and immune cell infiltration. The three clusters were highly consistent with the three tumor immune phenotypes, i.e., immune-excluded, immune-inflamed, and immune-desert. Comprehensive bioinformatics analysis revealed that high m6Ascore was closely associated with tumor progression, poor prognosis, and immunotherapy non-response. m6A regulators were dysregulated in HCC tissues. Hence, they play a role as predictors of poor prognosis. Tissue microarray demonstrated that overexpressed YTHDF1 was associated with low CD3⁺ and CD8⁺ T cell infiltration in HCC.

Conclusion: Our findings demonstrate that m6A modification patterns play a crucial role in the tumor immune microenvironment and the prognosis of HCC. High YTHDF1 expression is closely associated with low CD3⁺ and CD8⁺ T cell infiltration in HCC.

N6 -methyladenosine (m6 A) RNA modification of G protein-coupled receptor 133 increases proliferation of lung adenocarcinoma

Lung adenocarcinoma (LUAD) accounts for almost 40% of lung cancers, leading to significant associated morbidity and mortality rates. However, the mechanism of LUAD tumorigenesis remains far from clear. Here, we scanned down‐regulated genes involved in LUAD sourced from The Cancer Genome Atlas and Gene Expression Omnibus data and focused on G protein‐coupled receptor 133 (GPR133). We offer compelling evidence that GPR133 was expressed at low levels in the setting of LUAD, and higher expression was positively related to a better prognosis among patients with LUAD. Functionally, GPR133 inhibited cell proliferation and tumor growth in vitro and in vivo. Regarding the mechanism, flow cytometry assays and western blot assays showed that GPR133 enhanced p21 and decreased cyclin B1 expression, thus triggering LUAD cells at G2/M‐phase arrest. Consistent with this, we evaluated the expression levels of cell‐cycle biomarkers and found that bioinformatics analysis combined with N⁶‐methyladenosine (methylation at the N6 position in adenosine) RNA immunoprecipitation‐qPCR assay indicated that GPR133 expression was down‐regulated by this modification. Moreover, we observed that methyltransferase‐like 3 was impaired in LUAD, and that it is able to significantly increase levels of GPR133 by enhancing its RNA stability. In conclusion, we found that GPR133 expression was down‐regulated in LUAD via N⁶‐methyladenosine modification. Increasing GPR133 levels could suppress LUAD cell proliferation and tumor growth.

Identification of m6A-Associated RNA Binding Proteins Using an Integrative Computational Framework

N6-methyladenosine (m⁶A) is an abundant modification on mRNA that plays an important role in regulating essential RNA activities. Several wet lab studies have identified some RNA binding proteins (RBPs) that are related to m⁶A's regulation. The objective of this study was to identify potential m⁶A-associated RBPs using an integrative computational framework. The framework was composed of an enrichment analysis and a classification model. Utilizing RBPs' binding data, we analyzed reproducible m⁶A regions from independent studies using this framework. The enrichment analysis identified known m⁶A-associated RBPs including YTH domain-containing proteins; it also identified RBM3 as a potential m⁶A-associated RBP for mouse. Furthermore, a significant correlation for the identified m⁶A-associated RBPs is observed at the protein expression level rather than the gene expression level. On the other hand, a Random Forest classification model was built for the reproducible m⁶A regions using RBPs' binding data. The RBP-based predictor demonstrated not only competitive performance when compared with sequence-based predictions but also reflected m⁶A's action of repelling against RBPs, which suggested that our framework can infer interaction between m⁶A and m⁶A-associated RBPs beyond sequence level when utilizing RBPs' binding data. In conclusion, we designed an integrative computational framework for the identification of known and potential m⁶A-associated RBPs. We hope the analysis will provide more insights on the studies of m⁶A and RNA modifications.