Detection of internal N7-methylguanosine (m7G) RNA modifications by mutational profiling sequencing

All the sites we cannot see: Sources and mitigation of false negatives in RNA modification studies

RNA modifications are essential for human health - too much or too little of them leads to serious illnesses ranging from neurodevelopmental disorders to cancer. Technical advances in RNA modification sequencing are beginning to uncover the RNA targets of diverse RNA-modifying enzymes that are dysregulated in disease. However, the emerging transcriptome-wide maps of modified nucleosides installed by these enzymes should be considered as first drafts. In particular, a range of technical artefacts lead to false negatives - modified sites that are overlooked owing to technique-dependent, and often sequence-context-specific, 'blind spots'. In this Review, we discuss potential sources of false negatives in sequencing-based RNA modification maps, propose mitigation strategies and suggest guidelines for transparent reporting of sensitivity to detect modified sites in profiling studies. Important considerations for recognition and avoidance of false negatives include assessment and reporting of position-specific sequencing depth, identification of protocol-dependent RNA capture biases and applying controls for false negatives as well as for false positives. Despite their limitations, emerging maps of RNA modifications reveal exciting and largely uncharted potential for post-transcriptional control of all aspects of RNA function.

Metabolic rewiring during bone development underlies tRNA m7G-associated primordial dwarfism

Translation of mRNA to protein is tightly regulated by transfer RNAs (tRNAs), which are subject to various chemical modifications that maintain structure, stability, and function. Deficiency of tRNA N7-methylguanosine (m7G) modification in patients causes a type of primordial dwarfism, but the underlying mechanism remains unknown. Here we report that the loss of m7G rewires cellular metabolism, leading to the pathogenesis of primordial dwarfism. Conditional deletion of the catalytic enzyme Mettl1 or missense mutation of the scaffold protein Wdr4 severely impaired endochondral bone formation and bone mass accrual. Mechanistically, Mettl1 knockout decreased abundance of m7G-modified tRNAs and inhibited translation of mRNAs relating to cytoskeleton and Rho GTPase signaling. Meanwhile, Mettl1 knockout enhanced cellular energy metabolism despite incompetent proliferation and osteogenic commitment. Further exploration revealed that impairment of Rho GTPase signaling upregulated the level of branched-chain amino acid transaminase 1 (BCAT1) that rewired cell metabolism and restricted intracellular α-ketoglutarate (αKG). Supplementation of αKG ameliorated the skeletal defect of Mettl1-deficient mice. In addition to the selective translation of metabolism-related mRNAs, we further revealed that Mettl1 knockout globally regulated translation via integrated stress response (ISR) and mammalian target of rapamycin complex 1 (mTORC1) signaling. Restoring translation by targeting either ISR or mTORC1 aggravated bone defects of Mettl1-deficient mice. Overall, our study unveils a critical role of m7G tRNA modification in bone development by regulation of cellular metabolism and indicates suspension of translation initiation as a quality control mechanism in response to tRNA dysregulation.

RNA modifications identification based on chemical reactions

RNA modification identification is an emerging field in epigenetics due to its indispensable regulatory role in the cell life cycle. With advancements in identification methods, an increasing number of RNA modifications has been discovered, thereby driving the development of more efficient and accurate techniques for localizing modified RNAs and elucidating their functions. High-throughput sequencing approaches for modified RNA detection can be categorized into antibody-based, enzymatic-based, and chemical-labeling-based methods. Given the intrinsic chemical reactions involved in all biochemical processes, we provide a comprehensive review of recent advancements in artificial chemical labeling and transformations of ten distinct RNA modifications and their applications in sequencing. Our aim is to contribute to a deeper understanding of the mechanisms underlying these modifications. We focus on the chemical reactions associated with RNA modifications and briefly compare the advantages and disadvantages of detection methods based on these reactions. Additionally, we introduce several approaches that identify multiple modifications through chemical labeling. As the field of RNA modification research continues to expand, we anticipate that the techniques and insights presented in this review will serve as a valuable resource for future studies aimed at further elucidating the functional roles of RNA modifications in biological processes.

Exploring the role of m7G modification in Cancer: Mechanisms, regulatory proteins, and biomarker potential

The dysregulation of N(7)-methylguanosine (m7G) modification is increasingly recognized as a key factor in the pathogenesis of cancers. Aberrant expression of these regulatory proteins in various cancers, including lung, liver, and bladder cancers, suggests a universal role in tumorigenesis. Studies have established a strong correlation between the expression levels of m7G regulatory proteins, such as Methyltransferase like 1 (METTL1) and WD repeat domain 4 (WDR4), and clinical parameters including tumor stage, grade, and patient prognosis. For example, in hepatocellular carcinoma, high METTL1 expression is associated with advanced tumor stage and poor prognosis. Similarly, WDR4 overexpression in colorectal cancer correlates with increased tumor invasiveness and reduced patient survival. This correlation underscores the potential of these proteins as valuable biomarkers for cancer diagnosis and prognosis. Additionally, m7G modification regulatory proteins influence cancer progression by modulating the expression of target genes involved in critical biological processes, including cell proliferation, apoptosis, migration, and invasion. Their ability to regulate these processes highlights their significance in the intricate network of molecular interactions driving tumor development and metastasis. Given their pivotal role in cancer biology, m7G modification regulatory proteins are emerging as promising therapeutic targets. Targeting these proteins could offer a novel approach to disrupt the malignant behavior of cancer cells and enhance treatment outcomes. Furthermore, their diagnostic and prognostic value could aid in the early detection of cancer and the selection of appropriate therapeutic strategies, ultimately enhancing patient management and survival rates. This review aims to explore the mechanisms of action of RNA m7G modification regulatory proteins in tumors and their potential applications in cancer progression and treatment. By delving into the roles of these regulatory proteins, we intend to provide a theoretical foundation for the development of novel cancer treatment strategies.

Writers, readers, and erasers RNA modifications and drug resistance in cancer

Drug resistance in cancer cells significantly diminishes treatment efficacy, leading to recurrence and metastasis. A critical factor contributing to this resistance is the epigenetic alteration of gene expression via RNA modifications, such as N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), 7-methylguanosine (m7G), pseudouridine (Ψ), and adenosine-to-inosine (A-to-I) editing. These modifications are pivotal in regulating RNA splicing, translation, transport, degradation, and stability. Governed by "writers," "readers," and "erasers," RNA modifications impact numerous biological processes and cancer progression, including cell proliferation, stemness, autophagy, invasion, and apoptosis. Aberrant RNA modifications can lead to drug resistance and adverse outcomes in various cancers. Thus, targeting RNA modification regulators offers a promising strategy for overcoming drug resistance and enhancing treatment efficacy. This review consolidates recent research on the role of prevalent RNA modifications in cancer drug resistance, with a focus on m6A, m1A, m5C, m7G, Ψ, and A-to-I editing. Additionally, it examines the regulatory mechanisms of RNA modifications linked to drug resistance in cancer and underscores the existing limitations in this field.

IGF2BP3 promotes mRNA degradation through internal m7G modification

Recent studies have suggested that mRNA internal m7G and its writer protein METTL1 are closely related to cell metabolism and cancer regulation. Here, we identify that IGF2BP family proteins IGF2BP1-3 can preferentially bind internal mRNA m7G. Such interactions, especially IGF2BP3 with m7G, could promote the degradation of m7G target transcripts in cancer cells. IGF2BP3 is more responsive to changes of m7G modification, while IGF2BP1 prefers m6A to stabilize the bound transcripts. We also demonstrate that p53 transcript, TP53, is m7G-modified at its 3'UTR in cancer cells. In glioblastoma, the methylation level and the half lifetime of the modified transcript could be modulated by tuning IGF2BP3, or by site-specific targeting of m7G through a dCas13b-guided system, resulting in modulation of cancer progression and chemosensitivity.

RNA tertiary structure and conformational dynamics revealed by BASH MaP

The functional effects of an RNA can arise from complex three-dimensional folds known as tertiary structures. However, predicting the tertiary structure of an RNA and whether an RNA adopts distinct tertiary conformations remains challenging. To address this, we developed BASH MaP, a single-molecule dimethyl sulfate (DMS) footprinting method and DAGGER, a computational pipeline, to identify alternative tertiary structures adopted by different molecules of RNA. BASH MaP utilizes potassium borohydride to reveal the chemical accessibility of the N7 position of guanosine, a key mediator of tertiary structures. We used BASH MaP to identify diverse conformational states and dynamics of RNA G-quadruplexes, an important RNA tertiary motif, in vitro and in cells. BASH MaP and DAGGER analysis of the fluorogenic aptamer Spinach reveals that it adopts alternative tertiary conformations which determine its fluorescence states. BASH MaP thus provides an approach for structural analysis of RNA by revealing previously undetectable tertiary structures.

A user guide to RT-based mapping of RNA modifications

Chemical modifications to RNA nucleotides are both a naturally occurring layer of biological regulation and an increasingly prevalent approach to synthetically alter RNA function in therapeutic applications. Detection of their presence, prevalence, and stoichiometry across different RNAs is critical to understanding their underlying functions. However, this remains challenging due to the technical barriers involved in differentiating chemically similar modification species, and in detecting rare or low stoichiometry modifications. Reverse transcription-based techniques rely on the introduction of a predictable mutation, truncation, or deletion signature when a reverse transcriptase encounters a modified nucleotide of interest. Previous studies have shown promise in detecting modifications to single nucleotide resolution, but the low efficiency and processivity of many commercially available reverse transcriptases has resulted in discordant conclusions in some cases. Here, we present guidelines and best practices for applying the highly processive MarathonRT enzyme to reverse transcription-based modification sequencing. These guidelines include recommendations for controls and example protocols to help users plan robust experiments for mapping modification(s) of choice, as well as discussion of the limitations for the methods described.

Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site Prediction

N-7methylguanosine (m7G) modification plays a crucial role in various biological processes and is closely associated with the development and progression of many cancers. Accurate identification of m7G modification sites is essential for understanding their regulatory mechanisms and advancing cancer therapy. Previous studies often suffered from insufficient research data, underutilization of motif information, and lack of interpretability. In this work, we designed a novel motif-based interpretable method for m7G modification site prediction, called Moss-m7G. This approach enables the analysis of RNA sequences from a motif-centric perspective. Our proposed word-detection module and motif-embedding module within Moss-m7G extract motif information from sequences, transforming the raw sequences from base-level into motif-level and generating embeddings for these motif sequences. Compared with base sequences, motif sequences contain richer contextual information, which is further analyzed and integrated through the Transformer model. We constructed a comprehensive m7G data set to implement the training and testing process to address the data insufficiency noted in prior research. Our experimental results affirm the effectiveness and superiority of Moss-m7G in predicting m7G modification sites. Moreover, the introduction of the word-detection module enhances the interpretability of the model, providing insights into the predictive mechanisms.

The m7G Methyltransferase Mettl1 Drives Cardiac Hypertrophy by Regulating SRSF9-Mediated Splicing of NFATc4

Cardiac hypertrophy is a key factor driving heart failure (HF), yet its pathogenesis remains incompletely elucidated. Mettl1-catalyzed RNA N7-methylguanosine (m7G) modification has been implicated in ischemic cardiac injury and fibrosis. This study aims to elucidate the role of Mettl1 and the mechanism underlying non-ischemic cardiac hypertrophy and HF. It is found that Mettl1 is upregulated in human failing hearts and hypertrophic murine hearts following transverse aortic constriction (TAC) and Angiotensin II (Ang II) infusion. YY1 acts as a transcriptional factor for Mettl1 during cardiac hypertrophy. Mettl1 knockout alleviates cardiac hypertrophy and dysfunction upon pressure overload from TAC or Ang II stimulation. Conversely, cardiac-specific overexpression of Mettl1 results in cardiac remodeling. Mechanically, Mettl1 increases SRSF9 expression by inducing m7G modification of SRSF9 mRNA, facilitating alternative splicing and stabilization of NFATc4, thereby promoting cardiac hypertrophy. Moreover, the knockdown of SRSF9 protects against TAC- or Mettl1-induced cardiac hypertrophic phenotypes in vivo and in vitro. The study identifies Mettl1 as a crucial regulator of cardiac hypertrophy, providing a novel therapeutic target for HF.

Perturbation of METTL1-mediated tRNA N7- methylguanosine modification induces senescence and aging

Cellular senescence is characterized by a decrease in protein synthesis, although the underlying processes are mostly unclear. Chemical modifications to transfer RNAs (tRNAs) frequently influence tRNA activity, which is crucial for translation. We describe how tRNA N7-methylguanosine (m7G46) methylation, catalyzed by METTL1-WDR4, regulates translation and influences senescence phenotypes. Mettl1/Wdr4 and m7G gradually diminish with senescence and aging. A decrease in METTL1 causes a reduction in tRNAs, especially those with the m7G modification, via the rapid tRNA degradation (RTD) pathway. The decreases cause ribosomes to stall at certain codons, impeding the translation of mRNA that is essential in pathways such as Wnt signaling and ribosome biogenesis. Furthermore, chronic ribosome stalling stimulates the ribotoxic and integrative stress responses, which induce senescence-associated secretory phenotype. Moreover, restoring eEF1A protein mitigates senescence phenotypes caused by METTL1 deficiency by reducing RTD. Our findings demonstrate that tRNA m7G modification is essential for preventing premature senescence and aging by enabling efficient mRNA translation.

[Advances in mapping analysis of ribonucleic acid modifications through sequencing]

Over 170 chemical modifications have been discovered in various types of ribonucleic acids (RNAs), including messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and small nuclear RNA (snRNA). These RNA modifications play crucial roles in a wide range of biological processes such as gene expression regulation, RNA stability maintenance, and protein translation. RNA modifications represent a new dimension of gene expression regulation known as the "epitranscriptome". The discovery of RNA modifications and the relevant writers, erasers, and readers provides an important basis for studies on the dynamic regulation and physiological functions of RNA modifications. Owing to the development of detection technologies for RNA modifications, studies on RNA epitranscriptomes have progressed to the single-base resolution, multilayer, and full-coverage stage. Transcriptome-wide methods help discover new RNA modification sites and are of great importance for elucidating the molecular regulatory mechanisms of epitranscriptomics, exploring the disease associations of RNA modifications, and understanding their clinical applications. The existing RNA modification sequencing technologies can be categorized according to the pretreatment approach and sequencing principle as direct high-throughput sequencing, antibody-enrichment sequencing, enzyme-assisted sequencing, chemical labeling-assisted sequencing, metabolic labeling sequencing, and nanopore sequencing technologies. These methods, as well as studies on the functions of RNA modifications, have greatly expanded our understanding of epitranscriptomics. In this review, we summarize the recent progress in RNA modification detection technologies, focusing on the basic principles, advantages, and limitations of different methods. Direct high-throughput sequencing methods do not require complex RNA pretreatment and allow for the mapping of RNA modifications using conventional RNA sequencing methods. However, only a few RNA modifications can be analyzed by high-throughput sequencing. Antibody enrichment followed by high-throughput sequencing has emerged as a crucial approach for mapping RNA modifications, significantly advancing the understanding of RNA modifications and their regulatory functions in different species. However, the resolution of antibody-enrichment sequencing is limited to approximately 100-200 bp. Although chemical crosslinking techniques can achieve single-base resolution, these methods are often complex, and the specificity of the antibodies used in these methods has raised concerns. In particular, the issue of off-target binding by the antibodies requires urgent attention. Enzyme-assisted sequencing has improved the accuracy of the localization analysis of RNA modifications and enables stoichiometric detection with single-base resolution. However, the enzymes used in this technique show poor reactivity, specificity, and sequence preference. Chemical labeling sequencing has become a widely used approach for profiling RNA modifications, particularly by altering reverse transcription (RT) signatures such as RT stops, misincorporations, and deletions. Chemical-assisted sequencing provides a sequence-independent RNA modification detection strategy that enables the localization of multiple RNA modifications. Additionally, when combined with the biotin-streptavidin affinity method, low-abundance RNA modifications can be enriched and detected. Nevertheless, the specificity of many chemical reactions remains problematic, and the development of specific reaction probes for particular modifications should continue in the future to achieve the precise localization of RNA modifications. As an indirect localization method, metabolic labeling sequencing specifically localizes the sites at which modifying enzymes act, which is of great significance in the study of RNA modification functions. However, this method is limited by the intracellular labeling of RNA and cannot be applied to biological samples such as clinical tissues and blood samples. Nanopore sequencing is a direct RNA-sequencing method that does not require RT or the polymerase chain reaction (PCR). However, challenges in analyzing the data obtained from nanopore sequencing, such as the high rate of false positives, must be resolved. Discussing sequencing analysis methods for various types of RNA modifications is instructive for the future development of novel RNA modification mapping technologies, and will aid studies on the functions of RNA modifications across the entire transcriptome.

The role of RNA methylation in tumor immunity and its potential in immunotherapy

RNA methylation, a prevalent post-transcriptional modification, has garnered considerable attention in research circles. It exerts regulatory control over diverse biological functions by modulating RNA splicing, translation, transport, and stability. Notably, studies have illuminated the substantial impact of RNA methylation on tumor immunity. The primary types of RNA methylation encompass N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G), and 3-methylcytidine (m3C). Compelling evidence underscores the involvement of RNA methylation in regulating the tumor microenvironment (TME). By affecting RNA translation and stability through the "writers", "erasers" and "readers", RNA methylation exerts influence over the dysregulation of immune cells and immune factors. Consequently, RNA methylation plays a pivotal role in modulating tumor immunity and mediating various biological behaviors, encompassing proliferation, invasion, metastasis, etc. In this review, we discussed the mechanisms and functions of several RNA methylations, providing a comprehensive overview of their biological roles and underlying mechanisms within the tumor microenvironment and among immunocytes. By exploring how these RNA modifications mediate tumor immune evasion, we also examine their potential applications in immunotherapy. This review aims to provide novel insights and strategies for identifying novel targets in RNA methylation and advancing cancer immunotherapy efficacy.

Enhanced ac4C detection in RNA via chemical reduction and cDNA synthesis with modified dNTPs

The functional analysis of epitranscriptomic modifications in RNA is constrained by a lack of methods that accurately capture their locations and levels. We previously demonstrated that the RNA modification N4-acetylcytidine (ac4C) can be mapped at base resolution through sodium borohydride reduction to tetrahydroacetylcytidine (tetrahydro-ac4C), followed by cDNA synthesis to misincorporate adenosine opposite reduced ac4C sites, culminating in C:T mismatches at acetylated cytidines (RedaC:T). However, this process is relatively inefficient, resulting in <20% C:T mismatches at a fully modified ac4C site in 18S rRNA. Considering that ac4C locations in other substrates including mRNA are unlikely to reach full penetrance, this method is not ideal for comprehensive mapping. Here, we introduce "RetraC:T" (reduction to tetrahydro-ac4C and reverse transcription with amino-dATP to induce C:T mismatches) as a method with enhanced ability to detect ac4C in cellular RNA. In brief, RNA is reduced through NaBH4 or the closely related reagent sodium cyanoborohydride (NaCNBH3) followed by cDNA synthesis in the presence of a modified DNA nucleotide, 2-amino-dATP, that preferentially binds to tetrahydro-ac4C. Incorporation of the modified dNTP substantially improved C:T mismatch rates, reaching stoichiometric detection of ac4C in 18S rRNA. Importantly, 2-amino-dATP did not result in truncated cDNA products nor increase mismatches at other locations. Thus, modified dNTPs are introduced as a new addition to the toolbox for detecting ac4C at base resolution.

Prognostic signature and immune efficacy of m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

Emerging role of RNA modification and long noncoding RNA interaction in cancer

RNA modification, especially N6-methyladenosine, 5-methylcytosine, and N7-methylguanosine methylation, participates in the occurrence and progression of cancer through multiple pathways. The function and expression of these epigenetic regulators have gradually become a hot topic in cancer research. Mutation and regulation of noncoding RNA, especially lncRNA, play a major role in cancer. Generally, lncRNAs exert tumor-suppressive or oncogenic functions and its dysregulation can promote tumor occurrence and metastasis. In this review, we summarize N6-methyladenosine, 5-methylcytosine, and N7-methylguanosine modifications in lncRNAs. Furthermore, we discuss the relationship between epigenetic RNA modification and lncRNA interaction and cancer progression in various cancers. Therefore, this review gives a comprehensive understanding of the mechanisms by which RNA modification affects the progression of various cancers by regulating lncRNAs, which may shed new light on cancer research and provide new insights into cancer therapy.

Comprehensive review on lipid metabolism and RNA methylation: Biological mechanisms, perspectives and challenges

Adipose tissue plays a crucial role in maintaining energy balance, regulating hormones, and promoting metabolic health. To address disorders related to obesity and develop effective therapies, it is essential to have a deep understanding of adipose tissue biology. In recent years, RNA methylation has emerged as a significant epigenetic modification involved in various cellular functions and metabolic pathways. Particularly in the realm of adipogenesis and lipid metabolism, extensive research is ongoing to uncover the mechanisms and functional importance of RNA methylation. Increasing evidence suggests that RNA methylation plays a regulatory role in adipocyte development, metabolism, and lipid utilization across different organs. This comprehensive review aims to provide an overview of common RNA methylation modifications, their occurrences, and regulatory mechanisms, focusing specifically on their intricate connections to fat metabolism. Additionally, we discuss the research methodologies used in studying RNA methylation and highlight relevant databases that can aid researchers in this rapidly advancing field.

Prognostic model and ceRNA network of m7G- and radiosensitivity-related genes in hepatocellular carcinoma

Background

Radiotherapy is an effective treatment for hepatocellular carcinoma (HCC). Recent studies indicated that N7-methylguanosine (m7G)-associated genes are involved in radioresistance and prognosis of HCC. However, the prognostic value and underlying mechanism of m7G-and radiosensitivity-associated genes are still lacking.

Methods

The related statistics of HCC were downloaded from The Cancer Genome Atlas (TCGA). M7G- and radiosensitivity-associated genes were screened and evaluated using correlation, differential, univariate, and multivariate analysis. The least absolute shrinkage and selection operator (LASSO) algorithm was used to establish a prognostic model. Prognostic efficacy, functional analysis, immune cell infiltration,and drug sensitivity of the prognostic model were assessed. The ceRNA network was predicted and evaluated through the StarBase database, correlation analysis, expression analysis, and survival analysis.

Result

METTL1, EIF3D, NCBP2, and WDR4 participated in prognosis model construction. The favorable prediction efficiency has been verified in both the training and verification sets. Different risk groups have differences in prognosis outcome, function analysis, immune cell infiltration, and drug sensitivity. NCBP2 can be used to predict the prognosis and has excellent potential in immunotherapy. A prognostic ceRNA network based on the NCBP2/miR-122-5p axis was established.

Conclusion

The prognosis model of m7G- and radiosensitivity-related genes is constructed, and widely used in clinical prognosis, immunotherapy, and drug therapy. NCBP2, as a hub gene, may be a prognostic biomarker for HCC and is related to immunotherapy. Establishing the NCBP2/miR-122-5p axis helps study the mechanism of ceRNA and provides new ideas for finding a new candidate biomarker.

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

Detection of ac4C in human mRNA is preserved upon data reassessment

We recently reported the distribution of N4-acetylcytidine (ac4C) in HeLa mRNA at base resolution through chemical reduction and the induction of C:T mismatches in sequencing (RedaC:T-seq). Our results contradicted an earlier report from Schwartz and colleagues utilizing a similar method termed ac4C-seq. Here, we revisit both datasets and reaffirm our findings. Through RedaC:T-seq reanalysis, we establish a low basal error rate at unmodified nucleotides that is not skewed to any specific mismatch type and a prominent increase in C:T substitutions as the dominant mismatch type in both treated wild-type replicates, with a high degree of reproducibility across replicates. In contrast, through ac4C-seq reanalysis, we uncover significant data quality issues including insufficient depth, with one wild-type replicate yielding 2.7 million reads, inconsistencies in reduction efficiencies between replicates, and an overall increase in mismatches involving thymine that could obscure ac4C detection. These analyses bolster the detection of ac4C in HeLa mRNA through RedaC:T-seq.

RNA modifications in cellular metabolism: implications for metabolism-targeted therapy and immunotherapy

Cellular metabolism is an intricate network satisfying bioenergetic and biosynthesis requirements of cells. Relevant studies have been constantly making inroads in our understanding of pathophysiology, and inspiring development of therapeutics. As a crucial component of epigenetics at post-transcription level, RNA modification significantly determines RNA fates, further affecting various biological processes and cellular phenotypes. To be noted, immunometabolism defines the metabolic alterations occur on immune cells in different stages and immunological contexts. In this review, we characterize the distribution features, modifying mechanisms and biological functions of 8 RNA modifications, including N6-methyladenosine (m6A), N6,2'-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N4-acetylcytosine (ac4C), N7-methylguanosine (m7G), Pseudouridine (Ψ), adenosine-to-inosine (A-to-I) editing, which are relatively the most studied types. Then regulatory roles of these RNA modification on metabolism in diverse health and disease contexts are comprehensively described, categorized as glucose, lipid, amino acid, and mitochondrial metabolism. And we highlight the regulation of RNA modifications on immunometabolism, further influencing immune responses. Above all, we provide a thorough discussion about clinical implications of RNA modification in metabolism-targeted therapy and immunotherapy, progression of RNA modification-targeted agents, and its potential in RNA-targeted therapeutics. Eventually, we give legitimate perspectives for future researches in this field from methodological requirements, mechanistic insights, to therapeutic applications.

General Principles and Limitations for Detection of RNA Modifications by Sequencing

Among the many analytical methods applied to RNA modifications, a particularly pronounced surge has occurred in the past decade in the field of modification mapping. The occurrence of modifications such as m6A in mRNA, albeit known since the 1980s, became amenable to transcriptome-wide analyses through the advent of next-generation sequencing techniques in a rather sudden manner. The term "mapping" here refers to detection of RNA modifications in a sequence context, which has a dramatic impact on the interpretation of biological functions. As a consequence, an impressive number of mapping techniques were published, most in the perspective of what now has become known as "epitranscriptomics". While more and more different modifications were reported to occur in mRNA, conflicting reports and controversial results pointed to a number of technical and theoretical problems rooted in analytics, statistics, and reagents. Rather than finding the proverbial needle in a haystack, the tasks were to determine how many needles of what color in what size of a haystack one was looking at.As the authors of this Account, we think it important to outline the limitations of different mapping methods since many life scientists freshly entering the field confuse the accuracy and precision of modification mapping with that of normal sequencing, which already features numerous caveats by itself. Indeed, we propose here to qualify a specific mapping method by the size of the transcriptome that can be meaningfully analyzed with it.We here focus on high throughput sequencing by Illumina technology, referred to as RNA-Seq. We noted with interest the development of methods for modification detection by other high throughput sequencing platforms that act directly on RNA, e.g., PacBio SMRT and nanopore sequencing, but those are not considered here.In contrast to approaches relying on direct RNA sequencing, current Illumina RNA-Seq protocols require prior conversion of RNA into DNA. This conversion relies on reverse transcription (RT) to create cDNA; thereafter, the cDNA undergoes a sequencing-by-synthesis type of analysis. Thus, a particular behavior of RNA modified nucleotides during the RT-step is a prerequisite for their detection (and quantification) by deep sequencing, and RT properties have great influence on the detection efficiency and reliability. Moreover, the RT-step requires annealing of a synthetic primer, a prerequisite with a crucial impact on library preparation. Thus, all RNA-Seq protocols must feature steps for the introduction of primers, primer landing sites, or adapters on both the RNA 3'- and 5'-ends.

Role of RNA Modifications, Especially m6A, in Aflatoxin Biosynthesis of Aspergillus flavus

RNA modifications play key roles in eukaryotes, but the functions in Aspergillus flavus are still unknown. Temperature has been reported previously to be a critical environmental factor that regulates the aflatoxin production of A. flavus, but much remains to be learned about the molecular networks. Here, we demonstrated that 12 kinds of RNA modifications in A. flavus were significantly changed under 29 °C compared to 37 °C incubation; among them, m6A was further verified by a colorimetric method. Then, the transcriptome-wide m6A methylome and m6A-altered genes were comprehensively illuminated through methylated RNA immunoprecipitation sequencing and RNA sequencing, from which 22 differentially methylated and expressed transcripts under 29 °C were screened out. It is especially notable that AFCA_009549, an aflatoxin biosynthetic pathway gene (aflQ), and the m6A methylation of its 332nd adenine in the mRNA significantly affect aflatoxin biosynthesis in A. flavus both on media and crop kernels. The content of sterigmatocystin in both ΔaflQ and aflQA332C strains was significantly higher than that in the WT strain. Together, these findings reveal that RNA modifications are associated with secondary metabolite biosynthesis of A. flavus.

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 and single-nucleotide resolution detection of 7-methylguanosine in RNA

RNA modifications, including N-7-methylguanosine (m7G), are pivotal in governing RNA stability and gene expression regulation. The accurate detection of internal m7G modifications is of paramount significance, given recent associations between altered m7G deposition and elevated expression of the methyltransferase METTL1 in various human cancers. The development of robust m7G detection techniques has posed a significant challenge in the field of epitranscriptomics. In this study, we introduce two methodologies for the global and accurate identification of m7G modifications in human RNA. We introduce borohydride reduction sequencing (Bo-Seq), which provides base resolution mapping of m7G modifications. Bo-Seq achieves exceptional performance through the optimization of RNA depurination and scission, involving the strategic use of high concentrations of NaBH4, neutral pH and the addition of 7-methylguanosine monophosphate (m7GMP) during the reducing reaction. Notably, compared to NaBH4-based methods, Bo-Seq enhances the m7G detection performance, and simplifies the detection process, eliminating the necessity for intricate chemical steps and reducing the protocol duration. In addition, we present an antibody-based approach, which enables the assessment of m7G relative levels across RNA molecules and biological samples, however it should be used with caution due to limitations associated with variations in antibody quality between batches. In summary, our novel approaches address the pressing need for reliable and accessible methods to detect RNA m7G methylation in human cells. These advancements hold the potential to catalyse future investigations in the critical field of epitranscriptomics, shedding light on the complex regulatory roles of m7G in gene expression and its implications in cancer biology.

A review on the role of RNA methylation in aging-related diseases

Senescence is the underlying mechanism of organism aging and is robustly regulated at the post-transcriptional level. This regulation involves the chemical modifications, of which the RNA methylation is the most common. Recently, a rapidly growing number of studies have demonstrated that methylation is relevant to aging and aging-associated diseases. Owing to the rapid development of detection methods, the understanding on RNA methylation has gone deeper. In this review, we summarize the current understanding on the influence of RNA modification on cellular senescence, with a focus on mRNA methylation in aging-related diseases, and discuss the emerging potential of RNA modification in diagnosis and therapy.

The complex nature of lncRNA-mediated chromatin dynamics in multiple myeloma

Extensive genome-wide sequencing efforts have unveiled the intricate regulatory potential of long non-protein coding RNAs (lncRNAs) within the domain of haematological malignancies. Notably, lncRNAs have been found to directly modulate chromatin architecture, thereby impacting gene expression and disease progression by interacting with DNA, RNA, and proteins in a tissue- or condition-specific manner. Furthermore, recent studies have highlighted the intricate epigenetic control of lncRNAs in cancer. Consequently, this provides a rationale to explore the possibility of therapeutically targeting lncRNAs themselves or the epigenetic mechanisms that govern their activity. Within the scope of this review, we will assess the current state of knowledge regarding the epigenetic regulation of lncRNAs and how, in turn, lncRNAs contribute to chromatin remodelling in the context of multiple myeloma.

MRT-ModSeq - Rapid Detection of RNA Modifications with MarathonRT

Chemical modifications are essential regulatory elements that modulate the behavior and function of cellular RNAs. Despite recent advances in sequencing-based RNA modification mapping, methods combining accuracy and speed are still lacking. Here, we introduce MRT-ModSeq for rapid, simultaneous detection of multiple RNA modifications using MarathonRT. MRT-ModSeq employs distinct divalent cofactors to generate 2-D mutational profiles that are highly dependent on nucleotide identity and modification type. As a proof of concept, we use the MRT fingerprints of well-studied rRNAs to implement a general workflow for detecting RNA modifications. MRT-ModSeq rapidly detects positions of diverse modifications across a RNA transcript, enabling assignment of m1acp3Y, m1A, m3U, m7G and 2'-OMe locations through mutation-rate filtering and machine learning. m1A sites in sparsely modified targets, such as MALAT1 and PRUNE1 could also be detected. MRT-ModSeq can be trained on natural and synthetic transcripts to expedite detection of diverse RNA modification subtypes across targets of interest.

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

Mettl1-mediated internal m7G methylation of Sptbn2 mRNA elicits neurogenesis and anti-alzheimer's disease

BACKGROUND

N7-methylguanosine (m7G) is one of the most conserved modifications in nucleosides impacting mRNA export, splicing, and translation. However, the precise function and molecular mechanism of internal mRNA m7G methylation in adult hippocampal neurogenesis and neurogenesis-related Alzheimer's disease (AD) remain unknown.

RESULTS

We profiled the dynamic Mettl1/Wdr4 expressions and m7G modification during neuronal differentiation of neural stem cells (NSCs) in vitro and in vivo. Adult hippocampal neurogenesis and its molecular mechanisms were examined by morphology, biochemical methods and biological sequencing. The translation efficiency of mRNA was detected by polysome profiling. The stability of Sptbn2 mRNA was constructed by RNA stability assay. APPswe/PS1ΔE9 (APP/PS1) double transgenic mice were used as model of AD. Morris water maze was used to detect the cognitive function.

METHODS

We found that m7G methyltransferase complex Mettl1/Wdr4 as well as m7G was significantly elevated in neurons. Functionally, silencing Mettl1 in neural stem cells (NSCs) markedly decreased m7G modification, neuronal genesis and proliferation in addition to increasing gliogenesis, while forced expression of Mettl1 facilitated neuronal differentiation and proliferation. Mechanistically, the m7G modification of Sptbn2 mRNA by Mettl1 enhanced its stability and translation, which promoted neurogenesis. Importantly, genetic defciency of Mettl1 reduced hippocampal neurogenesis and spatial memory in the adult mice. Furthermore, Mettl1 overexpression in the hippocampus of APP/PS1 mice rescued neurogenesis and behavioral defects.

CONCLUSION

Our findings unravel the pivotal role of internal mRNA m7G modification in Sptbn2-mediated neurogenesis, and highlight Mettl3 regulation of neurogenesis as a novel therapeutic target in AD treatment.

Biological roles of RNA m7G modification and its implications in cancer

M7G modification, known as one of the common post-transcriptional modifications of RNA, is present in many different types of RNAs. With the accurate identification of m7G modifications within RNAs, their functional roles in the regulation of gene expression and different physiological functions have been revealed. In addition, there is growing evidence that m7G modifications are crucial in the emergence of cancer. Here, we review the most recent findings regarding the detection techniques, distribution, biological functions and Regulators of m7G. We also summarize the connections between m7G modifications and cancer development, drug resistance, and tumor microenvironment as well as we discuss the research's future directions and trends.

Predicting Disease-Associated N7-Methylguanosine (m7G) Sites via Random Walk on Heterogeneous Network

Recent studies revealed that the modification of N7-methylguanosine (m7G) has associations with many human diseases. Effectively identifying disease-associated m7G methylation sites would provide crucial clues for disease diagnosis and treatment. Previous studies have developed computational methods to predict disease-associated m7G sites based on similarities among m7G sites and diseases. However, few have focused on the influence of the known m7G-disease association information on calculating similarity measures of m7G site and disease, which potentially promotes the identification of the disease-associated m7G sites. In this work, we propose а computational method called m7GDP-RW to predict m7G-disease associations by random walk algorithm. m7GDP-RW first incorporates the feature information of m7G site and disease with the known m7G-disease associations to compute m7G site similarity and disease similarity. Then m7GDP-RW combines the known m7G-disease associations with the computed similarity of m7G site and disease to construct a m7G-disease heterogeneous network. Finally, m7GDP-RW utilizes a two-pass random walk with restart algorithm to find novel m7G-disease associations on the heterogeneous network. The experimental results show that our method achieves higher prediction accuracy compared to the existing methods. The study case also demonstrates the effectiveness of m7GDP-RW in discovering potential m7G-disease associations.

Mapping epigenetic modifications by sequencing technologies

The "epigenetics" concept was first described in 1942. Thus far, chemical modifications on histones, DNA, and RNA have emerged as three important building blocks of epigenetic modifications. Many epigenetic modifications have been intensively studied and found to be involved in most essential biological processes as well as human diseases, including cancer. Precisely and quantitatively mapping over 100 [1], 17 [2], and 160 [3] different known types of epigenetic modifications in histone, DNA, and RNA is the key to understanding the role of epigenetic modifications in gene regulation in diverse biological processes. With the rapid development of sequencing technologies, scientists are able to detect specific epigenetic modifications with various quantitative, high-resolution, whole-genome/transcriptome approaches. Here, we summarize recent advances in epigenetic modification sequencing technologies, focusing on major histone, DNA, and RNA modifications in mammalian cells.

Regulation of the epigenome through RNA modifications

Chemical modifications of nucleotides expand the complexity and functional properties of genomes and transcriptomes. A handful of modifications in DNA bases are part of the epigenome, wherein DNA methylation regulates chromatin structure, transcription, and co-transcriptional RNA processing. In contrast, more than 150 chemical modifications of RNA constitute the epitranscriptome. Ribonucleoside modifications comprise a diverse repertoire of chemical groups, including methylation, acetylation, deamination, isomerization, and oxidation. Such RNA modifications regulate all steps of RNA metabolism, including folding, processing, stability, transport, translation, and RNA's intermolecular interactions. Initially thought to influence all aspects of the post-transcriptional regulation of gene expression exclusively, recent findings uncovered a crosstalk between the epitranscriptome and the epigenome. In other words, RNA modifications feedback to the epigenome to transcriptionally regulate gene expression. The epitranscriptome achieves this feat by directly or indirectly affecting chromatin structure and nuclear organization. This review highlights how chemical modifications in chromatin-associated RNAs (caRNAs) and messenger RNAs (mRNAs) encoding factors involved in transcription, chromatin structure, histone modifications, and nuclear organization affect gene expression transcriptionally.

RNA epigenetic modifications in ovarian cancer: The changes, chances, and challenges

Ovarian cancer (OC) is the most common female cancer worldwide. Patients with OC have high mortality because of its complex and poorly understood pathogenesis. RNA epigenetic modifications, such as m6 A, m1 A, and m5 C, are closely associated with the occurrence and development of OC. RNA modifications can affect the stability of mRNA transcripts, nuclear export of RNAs, translation efficiency, and decoding accuracy. However, there are few overviews that summarize the link between m6 A RNA modification and OC. Here, we discuss the molecular and cellular functions of different RNA modifications and how their regulation contributes to the pathogenesis of OC. By improving our understanding of the role of RNA modifications in the etiology of OC, we provide new perspectives for their use in OC diagnosis and treatment. This article is categorized under: RNA Processing > RNA Editing and Modification RNA in Disease and Development > RNA in Disease.

Epigenetic inhibitors and their role in cancer therapy

Epigenetic modifications to DNA are crucial for normal cellular and biological functioning. DNA methylation, histone modifications, and chromatin remodeling are the most common epigenetic mechanisms. These changes are heritable but still reversible. The aberrant epigenetic alterations, such as DNA methylation, histone modification, and non-coding RNA (ncRNA)-mediated gene regulation, play an essential role in developing various human diseases, including cancer. Recent studies show that synthetic and dietary epigenetic inhibitors attenuate the abnormal epigenetic modifications in cancer cells and therefore have strong potential for cancer treatment. In this chapter, we have highlighted various types of epigenetic modifications, their mechanism, and as drug targets for epigenetic therapy.

Identification and validation of a novel prognostic model for gastric cancer based on m7G-related genes

Background

The role of N7-methyladenosine (m7G)-related genes in the progression and prognosis of gastric cancer (GC) remains unclear. This study aimed to explore prognostic biomarkers for GC based on m7G methylation regulators and to construct a prognostic risk model.

Methods

RNA sequencing profiles with corresponding clinicopathological information associated with GC of which the histological type was stomach adenocarcinoma (STAD) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. A total of 29 m7G regulators were extracted from previous studies. According to the expression similarity of m7G regulators, the GC samples obtained from TCGA were further classified into 2 clusters demonstrating different overall survival (OS) rates and genetic heterogeneity, and the differentially expressed genes (DEGs) between these 2 clusters were defined as m7G-related genes. Univariate regression analysis and regression analysis were then used to obtain the prognostic m7G-related genes. The samples in TCGA and Genotype-Tissue Expression (GTEx) were used to verify the differential expression and prognostic value of these m7G-related genes contained in the prognostic model. Subsequently, the risk score was combined with other prognostic factors to develop a nomogram. The predictive ability of the nomogram was evaluated by the standard receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA) was used to identify activation pathways in both groups. Finally, the association between the prognostic model and the immune characteristics of GC were appraised.

Results

A prognostic model consisting of 11 m7G-related genes was constructed. GC patients in the high-risk group were shown to have a poor prognosis and this result was further demonstrated in each group. The risk model can be applied for patients with different clinical features. The results of GSEA showed that cell adhesion, cell junction, and focal adhesion were highly enriched in the high-risk group. In addition, we found that the expression of programmed cell death ligand 1 (PD-L1) was significantly elevated in the low-risk group, whereas programmed cell death ligand 2 (PD-L2) and tumor necrosis factor receptor superfamily member 4 (TNFRSF4) were overexpressed in the high-risk group.

Conclusions

We successfully built and verified a m7G relevant prognostic model for predicting prognosis and providing a new train of thought for improving the treatment of GC.

QKI shuttles internal m7G-modified transcripts into stress granules and modulates mRNA metabolism

N7-methylguanosine (m7G) modification, routinely occurring at mRNA 5' cap or within tRNAs/rRNAs, also exists internally in messenger RNAs (mRNAs). Although m7G-cap is essential for pre-mRNA processing and protein synthesis, the exact role of mRNA internal m7G modification remains elusive. Here, we report that mRNA internal m7G is selectively recognized by Quaking proteins (QKIs). By transcriptome-wide profiling/mapping of internal m7G methylome and QKI-binding sites, we identified more than 1,000 high-confidence m7G-modified and QKI-bound mRNA targets with a conserved "GANGAN (N = A/C/U/G)" motif. Strikingly, QKI7 interacts (via C terminus) with the stress granule (SG) core protein G3BP1 and shuttles internal m7G-modified transcripts into SGs to regulate mRNA stability and translation under stress conditions. Specifically, QKI7 attenuates the translation efficiency of essential genes in Hippo signaling pathways to sensitize cancer cells to chemotherapy. Collectively, we characterized QKIs as mRNA internal m7G-binding proteins that modulate target mRNA metabolism and cellular drug resistance.

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.

Small RNA modifications: regulatory molecules and potential applications

Small RNAs (also referred to as small noncoding RNAs, sncRNA) are defined as polymeric ribonucleic acid molecules that are less than 200 nucleotides in length and serve a variety of essential functions within cells. Small RNA species include microRNA (miRNA), PIWI-interacting RNA (piRNA), small interfering RNA (siRNA), tRNA-derived small RNA (tsRNA), etc. Current evidence suggest that small RNAs can also have diverse modifications to their nucleotide composition that affect their stability as well as their capacity for nuclear export, and these modifications are relevant to their capacity to drive molecular signaling processes relevant to biogenesis, cell proliferation and differentiation. In this review, we highlight the molecular characteristics and cellular functions of small RNA and their modifications, as well as current techniques for their reliable detection. We also discuss how small RNA modifications may be relevant to the clinical applications for the diagnosis and treatment of human health conditions such as cancer.

mRNA Regulation by RNA Modifications

Chemical modifications on mRNA represent a critical layer of gene expression regulation. Research in this area has continued to accelerate over the last decade, as more modifications are being characterized with increasing depth and breadth. mRNA modifications have been demonstrated to influence nearly every step from the early phases of transcript synthesis in the nucleus through to their decay in the cytoplasm, but in many cases, the molecular mechanisms involved in these processes remain mysterious. Here, we highlight recent work that has elucidated the roles of mRNA modifications throughout the mRNA life cycle, describe gaps in our understanding and remaining open questions, and offer some forward-looking perspective on future directions in the field.

Fast and Efficient Design of Deep Neural Networks for Predicting N7-Methylguanosine Sites Using autoBioSeqpy

N⁷-Methylguanosine (m⁷G) is a crucial post-transcriptional RNA modification that plays a pivotal role in regulating gene expression. Accurately identifying m⁷G sites is a fundamental step in understanding the biological functions and regulatory mechanisms associated with this modification. While whole-genome sequencing is the gold standard for RNA modification site detection, it is a time-consuming, expensive, and intricate process. Recently, computational approaches, especially deep learning (DL) techniques, have gained popularity in achieving this objective. Convolutional neural networks and recurrent neural networks are examples of DL algorithms that have emerged as versatile tools for modeling biological sequence data. However, developing an efficient network architecture with superior performance remains a challenging task, requiring significant expertise, time, and effort. To address this, we previously introduced a tool called autoBioSeqpy, which streamlines the design and implementation of DL networks for biological sequence classification. In this study, we utilized autoBioSeqpy to develop, train, evaluate, and fine-tune sequence-level DL models for predicting m⁷G sites. We provided detailed descriptions of these models, along with a step-by-step guide on their execution. The same methodology can be applied to other systems dealing with similar biological questions. The benchmark data and code utilized in this study can be accessed for free at http://github.com/jingry/autoBioSeeqpy/tree/2.0/examples/m7G.

The covalent nucleotide modifications within plant mRNAs: What we know, how we find them, and what should be done in the future

Although covalent nucleotide modifications were first identified on the bases of transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs), a number of these epitranscriptome marks have also been found to occur on the bases of messenger RNAs (mRNAs). These covalent mRNA features have been demonstrated to have various and significant effects on the processing (e.g. splicing, polyadenylation, etc.) and functionality (e.g. translation, transport, etc.) of these protein-encoding molecules. Here, we focus our attention on the current understanding of the collection of covalent nucleotide modifications known to occur on mRNAs in plants, how they are detected and studied, and the most outstanding future questions of each of these important epitranscriptomic regulatory signals.

MRT-ModSeq - Rapid detection of RNA modifications with MarathonRT

Chemical modifications are essential regulatory elements that modulate the behavior and function of cellular RNAs. Despite recent advances in sequencing-based RNA modification mapping, methods combining accuracy and speed are still lacking. Here, we introduce MRT- ModSeq for rapid, simultaneous detection of multiple RNA modifications using MarathonRT. MRT-ModSeq employs distinct divalent cofactors to generate 2-D mutational profiles that are highly dependent on nucleotide identity and modification type. As a proof of concept, we use the MRT fingerprints of well-studied rRNAs to implement a general workflow for detecting RNA modifications. MRT-ModSeq rapidly detects positions of diverse modifications across a RNA transcript, enabling assignment of m1acp3Y, m1A, m3U, m7G and 2'-OMe locations through mutation-rate filtering and machine learning. m1A sites in sparsely modified targets, such as MALAT1 and PRUNE1 could also be detected. MRT-ModSeq can be trained on natural and synthetic transcripts to expedite detection of diverse RNA modification subtypes across targets of interest.

Emerging roles of tRNA in cancer

Transfer RNAs (tRNAs) play pivotal roles in the transmission of genetic information, and abnormality of tRNAs directly leads to translation disorders and causes diseases, including cancer. The complex modifications enable tRNA to execute its delicate biological function. Alteration of appropriate modifications may affect the stability of tRNA, impair its ability to carry amino acids, and disrupt the pairing between anticodons and codons. Studies confirmed that dysregulation of tRNA modifications plays an important role in carcinogenesis. Furthermore, when the stability of tRNA is impaired, tRNAs are cleaved into small tRNA fragments (tRFs) by specific RNases. Though tRFs have been found to play vital regulatory roles in tumorigenesis, its formation process is far from clear. Understanding improper tRNA modifications and abnormal formation of tRFs in cancer is conducive to uncovering the role of metabolic process of tRNA under pathological conditions, which may open up new avenues for cancer prevention and treatment.

An Update of Epigenetic Drugs for the Treatment of Cancers and Brain Diseases: A Comprehensive Review

Epigenetics has long been recognized as a significant field in biology and is defined as the investigation of any alteration in gene expression patterns that is not attributed to changes in the DNA sequences. Epigenetic marks, including histone modifications, non-coding RNAs, and DNA methylation, play crucial roles in gene regulation. Numerous studies in humans have been carried out on single-nucleotide resolution of DNA methylation, the CpG island, new histone modifications, and genome-wide nucleosome positioning. These studies indicate that epigenetic mutations and aberrant placement of these epigenetic marks play a critical role in causing the disease. Consequently, significant development has occurred in biomedical research in identifying epigenetic mechanisms, their interactions, and changes in health and disease conditions. The purpose of this review article is to provide comprehensive information about the different types of diseases caused by alterations in epigenetic factors such as DNA methylation and histone acetylation or methylation. Recent studies reported that epigenetics could influence the evolution of human cancer via aberrant methylation of gene promoter regions, which is associated with reduced gene function. Furthermore, DNA methyltransferases (DNMTs) in the DNA methylation process as well as histone acetyltransferases (HATs)/histone deacetylases (HDACs) and histone methyltransferases (HMTs)/demethylases (HDMs) in histone modifications play important roles both in the catalysis and inhibition of target gene transcription and in many other DNA processes such as repair, replication, and recombination. Dysfunction in these enzymes leads to epigenetic disorders and, as a result, various diseases such as cancers and brain diseases. Consequently, the knowledge of how to modify aberrant DNA methylation as well as aberrant histone acetylation or methylation via inhibitors by using epigenetic drugs can be a suitable therapeutic approach for a number of diseases. Using the synergistic effects of DNA methylation and histone modification inhibitors, it is hoped that many epigenetic defects will be treated in the future. Numerous studies have demonstrated a link between epigenetic marks and their effects on brain and cancer diseases. Designing appropriate drugs could provide novel strategies for the management of these diseases in the near future.

When N7-methyladenosine modification meets cancer: Emerging frontiers and promising therapeutic opportunities

N⁷-methylguanosine (m⁷G) methylation, one of the most common RNA modifications in eukaryotes, has recently gained considerable attention. The biological functions of m⁷G modification in RNAs, including tRNA, rRNA, mRNA, and miRNA, remain largely unknown in human diseases. Owing to rapid advances in high-throughput technologies, increasing evidence suggests that m⁷G modification plays a critical role in cancer initiation and progression. As m⁷G modification and hallmarks of cancer are inextricably linked together, targeting m⁷G regulators may provide new possibilities for future cancer diagnoses and potential intervention targets. This review summarizes various detection methods for m⁷G modification, recent advances in m⁷G modification and tumor biology regarding their interplay and regulatory mechanisms. We conclude with an outlook on the future of diagnosing and treating m⁷G-related diseases.

RNA modifications in hematological malignancies

RNA modifications play an important role in various cancers including blood cancers by controlling gene expression programs critical for survival, proliferation and differentiation of cancer cells. While hundreds of RNA modifications have been identified, many have not been functionally characterized. With development of enabling technologies to identify and map RNA modifications, tremendous advancement has been made in our understanding of the biological functions of these molecular markers in diverse cellular contexts. In the last 5 years, N⁶-methyladenosine (m⁶A), the most prevalent internal mRNA modification, has been extensively implicated in many facets of leukemogenesis. Other types of RNA modifications are also involved in the regulation of cell fate decisions and tumorigenesis. Here, we summarize existing knowledge and recent discoveries regarding the role of RNA modifications in leukemia. We choose to highlight cutting-edge techniques to characterize and profile RNA modifications while discussing critical functions of key modifiers and regulatory mechanisms in the pathogenesis of hematological malignancies and touch on therapeutic strategies targeting RNA modifications. These important advancements in the field will continue to foster a strong foundation for the development of innovative treatments for hematological malignancies.

Single cell sequencing analysis constructed the N7-methylguanosine (m7G)-related prognostic signature in uveal melanoma

BACKGROUND

Uveal melanoma is a highly malignant tumor in the eye. Its recurrence and metastasis are common, and the prognosis is poor.

METHODS

The transcriptome data of UVM were downloaded from TCGA database, and the single cell sequencing dataset GSE139829 was downloaded from GEO database. Weighted co-expression network analysis was used to explore the modules associated with m7G. Lasso regression was used to construct M⁷G-related prognostic signature. Immune infiltration analysis was used to explore the significance of the model in the tumor immune microenvironment. Finally, cell assays were used to explore the function of key genes in the MUM-2B and OCM-1 cell lines of UVM.

RESULTS

The prognostic signature was constructed by Cox regression and Lasso regression. Patients could be divided into high-risk group and low-risk group by this signature, and the high-risk group had worse prognosis (P<0.05). Cell experiments showed that the proliferation, invasion and migration ability of UVM cell lines were significantly decreased after the knockdown of PAG1, a key gene in signature, which proved that PAG1 might be a potential target of UVM.

CONCLUSIONS

Our study explored the significance of m⁷G in UVM, provided biomarkers for its diagnosis and treatment.

Expression pattern and prognostic value of key regulators for N7-methylguanosine RNA modification in prostate cancer

Alterations in the regulators of RNA methylation modifications, such as N7-methylguanosine (m7G), have been implicated in a variety of diseases. Therefore, the analysis and identification of disease-related m7G modification regulators will accelerate advances in understanding disease pathogenesis. However, the implications of alterations in the regulators of m7G modifications remain poorly understood in prostate adenocarcinoma. In the present study, we analyze the expression patterns of 29 m7G RNA modification regulators in prostate adenocarcinoma using The Cancer Genome Atlas (TCGA) and perform consistent clustering analysis of differentially expressed genes (DEGs). We find that 18 m7G-related genes are differentially expressed in tumor and normal tissues. In different cluster subgroups, DEGs are mainly enriched in tumorigenesis and tumor development. Furthermore, immune analyses demonstrate that patients in cluster 1 have significantly higher scores for stromal and immune cells, such as B cells, T cells, and macrophages. Then, a TCGA-related risk model is developed and successfully validated using a Gene Expression Omnibus external dataset. Two genes ( EIF4A1 and NCBP2) are determined to be prognostically significant. Most importantly, we construct tissue microarrays from 26 tumor specimens and 20 normal specimens, and further confirm that EIF4A1 and NCBP2 are associated with tumor progression and Gleason score. Therefore, we conclude that the m7G RNA methylation regulators may be involved in the poor prognosis of patients with prostate adenocarcinoma. The results of this study may provide support for exploring the underlying molecular mechanisms of m7G regulators, especially EIF4A1 and NCBP2.