The RNA modification landscape in human disease

Current and potential roles of RNA modification-mediated autophagy dysregulation in cancer

Autophagy, a cellular lysosomal degradation and survival pathway, supports nutrient recycling and adaptation to metabolic stress and participates in various stages of tumor development, including tumorigenesis, metastasis, and malignant state maintenance. Among the various factors contributing to the dysregulation of autophagy in cancer, RNA modification can regulate autophagy by directly affecting the expression of core autophagy proteins. We propose that autophagy disorder mediated by RNA modification is an important mechanism for cancer development. Therefore, this review mainly discusses the role of RNA modification-mediated autophagy regulation in tumorigenesis. We summarize the molecular basis of autophagy and the core proteins and complexes at different stages of autophagy, especially those involved in cancer development. Moreover, we describe the crosstalk of RNA modification and autophagy and review the recent advances and potential role of the RNA modification/autophagy axis in the development of multiple cancers. Furthermore, the dual role of the RNA modification/autophagy axis in cancer drug resistance is discussed. A comprehensive understanding and extensive exploration of the molecular crosstalk of RNA modifications with autophagy will provide important insights into tumor pathophysiology and provide more options for cancer therapeutic strategies.

RNA out of the mist

RNA has long been regarded primarily as the intermediate between genes and proteins. It was a surprise then to discover that eukaryotic genes are mosaics of mRNA sequences interrupted by large tracts of transcribed but untranslated sequences, and that multicellular organisms also express many long 'intergenic' and antisense noncoding RNAs (lncRNAs). The identification of small RNAs that regulate mRNA translation and half-life did not disturb the prevailing view that animals and plant genomes are full of evolutionary debris and that their development is mainly supervised by transcription factors. Gathering evidence to the contrary involved addressing the low conservation, expression, and genetic visibility of lncRNAs, demonstrating their cell-specific roles in cell and developmental biology, and their association with chromatin-modifying complexes and phase-separated domains. The emerging picture is that most lncRNAs are the products of genetic loci termed 'enhancers', which marshal generic effector proteins to their sites of action to control cell fate decisions during development.

The emergent role of mitochondrial RNA modifications in metabolic alterations

Mitochondrial epitranscriptomics refers to the modifications occurring in all the different RNA types of mitochondria. Although the number of mitochondrial RNA modifications is less than those in cytoplasm, substantial evidence indicates that they play a critical role in accurate protein synthesis. Recent evidence supported those modifications in mitochondrial RNAs also have crucial implications in mitochondrial-related diseases. In the light of current knowledge about the involvement, the association between mitochondrial RNA modifications and diseases arises from studies focusing on mutations in both mitochondrial and nuclear DNA genes encoding enzymes involved in such modifications. Here, we review the current evidence available for mitochondrial RNA modifications and their role in metabolic disorders, and we also explore the possibility of using them as promising targets for prevention and early detection. Finally, we discuss future directions of mitochondrial epitranscriptomics in these metabolic alterations, and how these RNA modifications may offer a new diagnostic and theragnostic avenue for preventive purposes. This article is categorized under: RNA Processing > RNA Editing and Modification.

The chemical landscape of the human ribosome at 1.67 Å resolution

The ability of ribosomes to translate the genetic code into protein requires a finely tuned ion and solvent ecosystem. However, the lack of high-resolution structures has precluded accurate positioning of all the functional elements of the ribosome and limited our understanding of the specific role of ribosomal RNA chemical modifications in modulating ribosome function in health and disease. Here, using a new sample preparation methodology based on functionalised pristine graphene-coated grids, we solve the cryo-EM structure of the human large ribosomal subunit to a resolution of 1.67 Å. The accurate assignment of water molecules, magnesium and potassium ions in our model highlights the fundamental biological role of ribosomal RNA methylation in harnessing unconventional carbon-oxygen hydrogen bonds to establish chemical interactions with the environment and fine-tune the functional interplay with tRNA. In addition, the structures of three translational inhibitors bound to the human large ribosomal subunit at better than 2 Å resolution provide mechanistic insights into how three key druggable pockets of the ribosome are targeted and illustrate the potential of this methodology to accelerate high-throughput structure-based design of anti-cancer therapeutics.

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.

Hierarchical DNA branch assembly-encoded fluorescent nanoladders for single-cell transcripts imaging

Spatial visualization of single-cell transcripts is limited by signal specificity and multiplexing. Here, we report hierarchical DNA branch assembly-encoded fluorescent nanoladders, which achieve denoised and highly multiplexed signal amplification for single-molecule transcript imaging. This method first offers independent RNA-primed rolling circle amplification without nonspecific amplification based on circular DNAzyme. It then executes programmable DNA branch assembly on these amplicons to encode virtual signals for visualizing numbers of targets by FISH. In theory, more virtual signals can be encoded via the increase of detection spectral channels and repeats of the same sequences on barcode. Our method almost eliminates nonspecific amplification in fixed cells (reducing nonspecific spots of single cells from 16 to nearly zero), and achieves simultaneous quantitation of nine transcripts by using only two detection spectral channels. We demonstrate accurate RNA profiling in different cancer cells, and reveal diverse localization patterns for spatial regulation of transcripts.

m5C-dependent cross-regulation between nuclear reader ALYREF and writer NSUN2 promotes urothelial bladder cancer malignancy through facilitating RABL6/TK1 mRNAs splicing and stabilization

The significance of 5-methylcytosine (m⁵C) methylation in human malignancies has become an increasing focus of investigation. Here, we show that m⁵C regulators including writers, readers and erasers, are predominantly upregulated in urothelial carcinoma of the bladder (UCB) derived from Sun Yat-sen University Cancer Center and The Cancer Genome Atlas cohort. In addition, NOP2/Sun RNA methyltransferase family member 2 (NSUN2) as a methyltransferase and Aly/REF export factor (ALYREF) as a nuclear m⁵C reader, are frequently coexpressed in UCB. By applying patient-derived organoids model and orthotopic xenograft mice model, we demonstrate that ALYREF enhances proliferation and invasion of UCB cells in an m⁵C-dependent manner. Integration of tanscriptome-wide RNA bisulphite sequencing (BisSeq), RNA-sequencing (RNA-seq) and RNA Immunoprecipitation (RIP)-seq analysis revealed that ALYREF specifically binds to hypermethylated m⁵C site in RAB, member RAS oncogene family like 6 (RABL6) and thymidine kinase 1 (TK1) mRNA via its K171 domain. ALYREF controls UCB malignancies through promoting hypermethylated RABL6 and TK1 mRNA for splicing and stabilization. Moreover, ALYREF recognizes hypermethylated m⁵C site of NSUN2, resulting in NSUN2 upregulation in UCB. Clinically, the patients with high coexpression of ALYREF/RABL6/TK1 axis had the poorest overall survival. Our study unveils an m⁵C dependent cross-regulation between nuclear reader ALYREF and m⁵C writer NSUN2 in activation of hypermethylated m⁵C oncogenic RNA through promoting splicing and maintaining stabilization, consequently leading to tumor progression, which provides profound insights into therapeutic strategy for UCB.

m6A Modification-Association with Oxidative Stress and Implications on Eye Diseases

Oxidative stress (OS) refers to a state of imbalance between oxidation and antioxidation. OS is considered to be an important factor leading to aging and a range of diseases. The eyes are highly oxygen-consuming organs. Due to its continuous exposure to ultraviolet light, the eye is particularly vulnerable to the impact of OS, leading to eye diseases such as corneal disease, cataracts, glaucoma, etc. The N6-methyladenosine (m6A) modification is the most investigated RNA post-transcriptional modification and participates in a variety of cellular biological processes. In this study, we review the role of m6A modification in oxidative stress-induced eye diseases and some therapeutic methods to provide a relatively overall understanding of m6A modification in oxidative stress-related eye diseases.

RNA Modification Detection Using Nanopore Direct RNA Sequencing and nanoDoc2

RNA modifications regulate multiple aspects of cellular function including RNA splicing, translation, export, decay, stability, and phase separation. One of the comprehensive ways to detect such modifications is by the recent advancement of direct RNA sequencing from Oxford Nanopore Technologies (ONT). However, this method obtains a large amount of data with high complexity in the form of raw current signal that poses a new informatics challenge to accurately detect those modifications. Here, we provide nanoDoc2, a software to detect multiple types of RNA modification from nanopore direct RNA sequencing data. The nanoDoc2 includes a novel signal segmentation algorithm based on the trace value-a base probability feature that is added by the Guppy basecalling program from ONT during processing of the raw signal. The core of nanoDoc2 includes a machine learning algorithm in which a 6-mer segmented raw current signal is analyzed by deep one-class classification using a WaveNet-based neural network. As an output, an RNA modification is detected by a statistical score in each candidate position. Herein, we describe the detailed instructions on how to use nanoDoc2 for signal segmentation, train/test the neural network, and finally predict RNA modifications present in nanopore direct RNA sequencing data.

Comprehensive analysis of transcriptomic profiling of 5-methylcytosin modification in placentas from preeclampsia and normotensive pregnancies

Increasing evidence suggests that RNA m5C modification and its regulators have been confirmed to be associated with the pathogenesis of many diseases. However, the distribution and biological functions of m5C in mRNAs of placental tissues remain unknown. we collected placentae from normotensive pregnancies (CTR) and preeclampsia patients (PE) to analyze the transcriptomic profiling of m5C RNA methylation through m5C RNA immunoprecipitation (UMI-MeRIP-Seq). we discovered that overall m5C methylation peaks were decreased in placental tissues from PE patients. And, 2844 aberrant m5C peaks were identified, of which respectively 1304 m5C peaks were upregulated and 1540 peaks were downregulated. The distribution of m5C peaks were mainly located in CDS (coding sequences) regions in placental tissues of both groups, but compared with the CTR group, the m5C peak in PE group before the stop code of CDS was significantly increased and even higher than the peak value after start code in CDS. Differentially methylated genes were mainly enriched in MAPK/cAMP signaling pathway. Moreover, the up-regulated genes with hypermethylated modification were enriched in the processes of hypoxia, inflammation/immune response. Finally, through analyzing the mRNA expression levels of m5C RNA methylation regulators, we found only DNMT3B and TET3 were significantly upregulated in PE samples than in control group. And they are not only negatively correlated with each other, but also closely related to those differentially expressed genes modified by differential methylation.Our findings provide new insights regarding alterations of m5C RNA modification into the pathogenic mechanisms of PE.

Self-attention enabled deep learning of dihydrouridine (D) modification on mRNAs unveiled a distinct sequence signature from tRNAs

Dihydrouridine (D) is a modified pyrimidine nucleotide universally found in viral, prokaryotic, and eukaryotic species. It serves as a metabolic modulator for various pathological conditions, and its elevated levels in tumors are associated with a series of cancers. Precise identification of D sites on RNA is vital for understanding its biological function. A number of computational approaches have been developed for predicting D sites on tRNAs; however, none have considered mRNAs. We present here DPred, the first computational tool for predicting D on mRNAs in yeast from the primary RNA sequences. Built on a local self-attention layer and a convolutional neural network (CNN) layer, the proposed deep learning model outperformed classic machine learning approaches (random forest, support vector machines, etc.) and achieved reasonable accuracy and reliability with areas under the curve of 0.9166 and 0.9027 in jackknife cross-validation and on an independent testing dataset, respectively. Importantly, we showed that distinct sequence signatures are associated with the D sites on mRNAs and tRNAs, implying potentially different formation mechanisms and putative divergent functionality of this modification on the two types of RNA. DPred is available as a user-friendly Web server.

The Repertoire of RNA Modifications Orchestrates a Plethora of Cellular Responses

Although a plethora of DNA modifications have been extensively investigated in the last decade, recent breakthroughs in molecular biology, including high throughput sequencing techniques, have enabled the identification of post-transcriptional marks that decorate RNAs; hence, epitranscriptomics has arisen. This recent scientific field aims to decode the regulatory layer of the transcriptome and set the ground for the detection of modifications in ribose nucleotides. Until now, more than 170 RNA modifications have been reported in diverse types of RNA that contribute to various biological processes, such as RNA biogenesis, stability, and transcriptional and translational accuracy. However, dysfunctions in the RNA-modifying enzymes that regulate their dynamic level can lead to human diseases and cancer. The present review aims to highlight the epitranscriptomic landscape in human RNAs and match the catalytic proteins with the deposition or deletion of a specific mark. In the current review, the most abundant RNA modifications, such as N6-methyladenosine (m⁶A), N5-methylcytosine (m⁵C), pseudouridine (Ψ) and inosine (I), are thoroughly described, their functional and regulatory roles are discussed and their contributions to cellular homeostasis are stated. Ultimately, the involvement of the RNA modifications and their writers, erasers, and readers in human diseases and cancer is also discussed.

Selective Chemical Labeling Strategy for Oligonucleotides Determination: A First Application to Full-Range Profiling of Transfer RNA Modifications

To date, the extremely high polarity and poor signal intensity of macromolecular nucleic acids are greatly impeding the progress of mass spectrometry technology in the quality control of nucleic acid drugs and the characterization of DNA oxidation and RNA modifications. We recently described a general N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (MTBSTFA) labeling method for oligonucleotide determination and applied it to the full-range profiling of tRNA in vitro and in vivo studies for the first time. The primary advantages of this method include strong retention, no observable byproducts, predictable and easily interpreted MS² data, and the circumvention of instrument harmful reagents that were necessary in previous methods. Selective labeling of N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide to the terminal phosphate groups of oligonucleotides endows it broadly applicable for DNA/RNA profiling. Moreover, the improvement of sequence coverage was achieved in yeast tRNA^phe(GAA) analysis owing to this method's good detection capability of 1-12 nucleotides in length. We also extended this strategy to determine the abundance of modified bases and discover new modifications via digesting RNA into single-nucleotide products, promoting the comprehensive mapping of RNA. The easy availability of derivatization reagent and the simple, rapid one-step reaction render it easy to operate for researchers. When applied in characterizing tRNAs in HepG2 cells and rats with nonalcoholic fatty liver disease, a fragment of U[m¹G][m²G], specific for tRNA^Asn(QUU) in cells, was significantly upregulated, indicating a possible clue to nonalcoholic fatty liver disease pathogenesis.

Nucleos'ID: A New Search Engine Enabling the Untargeted Identification of RNA Post-transcriptional Modifications from Tandem Mass Spectrometry Analyses of Nucleosides

As RNA post-transcriptional modifications are of growing interest, several methods were developed for their characterization. One of them established for their identification, at the nucleosidic level, is the hyphenation of separation methods, such as liquid chromatography or capillary electrophoresis, to tandem mass spectrometry. However, to our knowledge, no software is yet available for the untargeted identification of RNA post-transcriptional modifications from MS/MS data-dependent acquisitions. Thus, very long and tedious manual data interpretations are required. To meet the need of easier and faster data interpretation, a new user-friendly search engine, called Nucleos'ID, was developed for CE-MS/MS and LC-MS/MS users. Performances of this new software were evaluated on CE-MS/MS data from nucleoside analyses of already well-described Saccharomyces cerevisiae transfer RNA and Bos taurus total tRNA extract. All samples showed great true positive, true negative, and false discovery rates considering the database size containing all modified and unmodified nucleosides referenced in the literature. The true positive and true negative rates obtained were above 0.94, while the false discovery rates were between 0.09 and 0.17. To increase the level of sample complexity, untargeted identification of several RNA modifications from Pseudomonas aeruginosa 70S ribosome was achieved by the Nucleos'ID search following CE-MS/MS analysis.

A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction

Background: Prostate cancer (PCa) is one of the most common cancers in males around the globe, and about one-third of patients with localized PCa will experience biochemical recurrence (BCR) after radical prostatectomy or radiation therapy. Reportedly, a proportion of patients with BCR had a poor prognosis. Cumulative studies have shown that RNA modifications participate in the cancer-related transcriptome, but the role of pseudouridylation occurring in lncRNAs in PCa remains opaque. Methods: Spearman correlation analysis and univariate Cox regression were utilized to determine pseudouridylation-related lncRNAs with prognostic value in PCa. Prognostic pseudouridylation-related lncRNAs were included in the LASSO (least absolute shrinkage and selection operator) regression algorithm to develop a predictive model. KM (Kaplan-Meier) survival analysis and ROC (receiver operating characteristic) curves were applied to validate the constructed model. A battery of biological cell assays was conducted to confirm the cancer-promoting effects of RP11-468E2.5 in the model. Results: A classifier containing five pseudouridine-related lncRNAs was developed to stratify PCa patients on BCR and named the "ψ-lnc score." KM survival analysis showed patients in the high ψ-lnc score group experienced BCR more than those in the low ψ-lnc score group. ROC curves demonstrated that ψ-lnc score outperformed other clinical indicators in BCR prediction. An external dataset, GSE54460, was utilized to validate the predictive model's efficacy and authenticity. A ceRNA (competitive endogenous RNA) network was constructed to explore the model's potential molecular functions and was annotated through GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. RP11-468E2.5 was picked for further investigation, including pan-cancer analysis and experimental validation. Preliminarily, RP11-468E2.5 was confirmed as a tumor promoter. Conclusion: We provide some evidence that pseudouridylation in lncRNA played a role in the development of PCa and propose a novel prognostic classifier for clinical practice.

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

With advanced technologies to map RNA modifications, our understanding of them has been revolutionized, and they are seen to be far more widespread and important than previously thought. Current next-generation sequencing (NGS)-based modification profiling methods are blind to RNA modifications and thus require selective chemical treatment or antibody immunoprecipitation methods for particular modification types. They also face the problem of short read length, isoform ambiguities, biases and artifacts. Direct RNA sequencing (DRS) technologies, commercialized by Oxford Nanopore Technologies (ONT), enable the direct interrogation of any given modification present in individual transcripts and promise to address the limitations of previous NGS-based methods. Here, we present the first ONT-based database of quantitative RNA modification profiles, DirectRMDB, which includes 16 types of modification and a total of 904,712 modification sites in 25 species identified from 39 independent studies. In addition to standard functions adopted by existing databases, such as gene annotations and post-transcriptional association analysis, we provide a fresh view of RNA modifications, which enables exploration of the epitranscriptome in an isoform-specific manner. The DirectRMDB database is freely available at: http://www.rnamd.org/directRMDB/.

Structures and mechanisms of tRNA methylation by METTL1-WDR4

Specific, regulated modification of RNAs is important for proper gene expression^1,2. tRNAs are rich with various chemical modifications that affect their stability and function^3,4. 7-Methylguanosine (m⁷G) at tRNA position 46 is a conserved modification that modulates steady-state tRNA levels to affect cell growth^5,6. The METTL1-WDR4 complex generates m⁷G46 in humans, and dysregulation of METTL1-WDR4 has been linked to brain malformation and multiple cancers^7-22. Here we show how METTL1 and WDR4 cooperate to recognize RNA substrates and catalyse methylation. A crystal structure of METTL1-WDR4 and cryo-electron microscopy structures of METTL1-WDR4-tRNA show that the composite protein surface recognizes the tRNA elbow through shape complementarity. The cryo-electron microscopy structures of METTL1-WDR4-tRNA with S-adenosylmethionine or S-adenosylhomocysteine along with METTL1 crystal structures provide additional insights into the catalytic mechanism by revealing the active site in multiple states. The METTL1 N terminus couples cofactor binding with conformational changes in the tRNA, the catalytic loop and the WDR4 C terminus, acting as the switch to activate m⁷G methylation. Thus, our structural models explain how post-translational modifications of the METTL1 N terminus can regulate methylation. Together, our work elucidates the core and regulatory mechanisms underlying m⁷G modification by METTL1, providing the framework to understand its contribution to biology and disease.

A novel RNA modification prognostic signature for predicting the characteristics of the tumor microenvironment in gastric cancer

Gastric cancer (GC) is one of the most common neoplastic malignancies, which permutes a fourth of cancer-related mortality globally. RNA modification plays a significant role in tumorigenesis, the underlying molecular mechanism of how different RNA modifications directly affect the tumor microenvironment (TME) in GC is unclear. Here, we profiled the genetic and transcriptional alterations of RNA modification genes (RMGs) in GC samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts. Through the unsupervised clustering algorithm, we identified three distinct RNA modification clusters and found that they participate in different biological pathways and starkly correlate with the clinicopathological characteristics, immune cell infiltration, and prognosis of GC patients. Subsequently, univariate Cox regression analysis unveiled 298 of 684 subtype-related differentially expressed genes (DEGs) are tightly interwoven to prognosis. In addition, we conducted the principal component analysis to develop the RM_Score system, which was used to quantify and predict the prognostic value of RNA modification in GC. Our analysis indicated that patients with high RM_Score were characterized by higher tumor mutational burden, mutation frequency, and microsatellite instability which were more susceptible to immunotherapy and had a favorable prognosis. Altogether, our study uncovered RNA modification signatures that may have a potential role in the TME and prediction of clinicopathological characteristics. Identification of these RNA modifications may provide a new understanding of immunotherapy strategies for gastric cancer.

Pathological and Therapeutic Advances in Parkinson's Disease: Mitochondria in the Interplay

Parkinson's disease (PD) is the second most common neurodegenerative illness majorly affecting the population between the ages of 55 to 65 years. Progressive dopaminergic neuronal loss and the collective assemblage of misfolded alpha-synuclein in the substantia nigra, remain notable neuro-pathological hallmarks of the disease. Multitudes of mechanistic pathways have been proposed in attempts to unravel the pathogenesis of PD but still, it remains elusive. The convergence of PD pathology is found in organelle dysfunction where mitochondria remain a major contributor. Mitochondrial processes like bioenergetics, mitochondrial dynamics, and mitophagy are under strict regulation by the mitochondrial genome and nuclear genome. These processes aggravate neurodegenerative activities upon alteration through neuroinflammation, oxidative damage, apoptosis, and proteostatic stress. Therefore, the mitochondria have grabbed a central position in the patho-mechanistic exploration of neurodegenerative diseases like PD. The management of PD remains a challenge to physicians to date, due to the variable therapeutic response of patients and the limitation of conventional chemical agents which only offer symptomatic relief with minimal to no disease-modifying effect. This review describes the patho-mechanistic pathways involved in PD not only limited to protein dyshomeostasis and oxidative stress, but explicit attention has been drawn to exploring mechanisms like organelle dysfunction, primarily mitochondria and mitochondrial genome influence, while delineating the newer exploratory targets such as GBA1, GLP, LRRK2, and miRNAs and therapeutic agents targeting them.

ALKBH5 ALLEVIATES HYPOXIA POSTCONDITIONING INJURY IN d -GALACTOSE-INDUCED SENESCENT CARDIOMYOCYTES BY REGULATING STAT3

ABSTRACT

Ischemic postconditioning (I/Post) reduces I/R injury by activating endogenous cardioprotection mechanisms, such as the JAK/signal transducer and activator of transcription 3 (STAT3) and PI3K/Akt pathways, which offer a traditional approach to myocardial protection. According to a previous study, cardioprotection by I/Post may be lost in aged mice, and in our previous research, hypoxic postconditioning (H/Post) lacked a protective effect in senescent cardiomyocytes, which was associated with low expression of long noncoding RNA H19. The N6-methyladenosine (m 6 A) modification is a dynamic and reversible process that has been confirmed to play a role in cardiovascular diseases. However, the mechanisms of m 6 A modification in myocardial I/Post remain to be explored. Neonatal cardiomyocytes were isolated from 2-day-old Sprague-Dawley rats, and senescence was induced by d -galactose, followed by stimulation of hypoxia-reoxygenation and H/Post. Hypoxic injury was evaluated by cell viability and the Bcl-2/Bax protein ratio. Total m 6 A levels were measured using a colorimetric m 6 A RNA Methylation Quantification Kit, and the m 6 A modified and differentially expressed mRNA was determined by MeRIP (methylated RNA immunoprecipitation). We found that H/Post increased m 6 A methylation and decreased RNA mA demethylase alkB homolog 5 (ALKBH5) expression in aged cardiomyocytes. Furthermore, ALKBH5 knockdown exacerbated injury following H/Post in senescent cardiomyocytes. In addition, ALKBH5 regulated STAT3 expression by mediating its m 6 A modification and long noncoding RNA H19/miR-124-3p. ALKBH5 also alleviated the H/Post injury induced by the low expression of STAT3 in senescent cardiomyocytes.

Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores

This chapter describes MasterOfPores v.2 (MoP2), an open-source suite of pipelines for processing and analyzing direct RNA Oxford Nanopore sequencing data. The MoP2 relies on the Nextflow DSL2 framework and Linux containers, thus enabling reproducible data analysis in transcriptomic and epitranscriptomic studies. We introduce the key concepts of MoP2 and provide a step-by-step fully reproducible and complete example of how to use the workflow for the analysis of S. cerevisiae total RNA samples sequenced using MinION flowcells. The workflow starts with the pre-processing of raw FAST5 files, which includes basecalling, read quality control, demultiplexing, filtering, mapping, estimation of per-gene/transcript abundances, and transcriptome assembly, with support of the GPU computing for the basecalling and read demultiplexing steps. The secondary analyses of the workflow focus on the estimation of RNA poly(A) tail lengths and the identification of RNA modifications. The MoP2 code is available at https://github.com/biocorecrg/MOP2 and is distributed under the MIT license.

Parent tRNA Modification Status Determines the Induction of Functional tRNA-Derived RNA by Respiratory Syncytial Virus Infection

tRNA-derived RNA fragments (tRFs) are a recently discovered family of small noncoding RNAs (sncRNAs). We previously reported that respiratory syncytial virus (RSV) infection induces functional tRFs, which are derived from a limited subset of parent tRNAs, in airway epithelial cells. Such induction is also observed in nasopharyngeal wash samples from RSV patients and correlates to RSV genome copies, suggesting a clinical significance of tRFs in RSV infection. This work also investigates whether the modification of parent tRNAs is changed by RSV to induce tRFs, using one of the most inducible tRFs as a model. We discovered that RSV infection changed the methylation modification of adenine at position 57 in tRNA glutamic acid, with a codon of CTC (tRNA-GluCTC), and the change is essential for its cleavage. AlkB homolog 1, a previously reported tRNA demethylase, appears to remove methyladenine from tRNA-GluCTC, prompting the subsequent production of tRFs from the 5'-end of tRNA-GluCTC, a regulator of RSV replication. This study demonstrates for the first time the importance of post-transcriptional modification of tRNAs in tRF biogenesis following RSV infection, providing critical insights for antiviral strategy development.

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.

Interplay of four types of RNA modification writers revealed distinct tumor microenvironment and biological characteristics in pancreatic cancer

Background

Pancreatic cancer (PC) is one of the most lethal malignancies and carries a dismal mortality and morbidity. Four types of RNA modification (namely m6A, m1A, APA and A-to-I) could be catalyzed by distinct enzymatic compounds ("writers"), mediating numerous epigenetic events in carcinogenesis and immunomodulation. We aim to investigate the interplay mechanism of these writers in immunogenomic features and molecular biological characteristics in PC.

Methods

We first accessed the specific expression pattern and transcriptional variation of 26 RNA modification writers in The Cancer Genome Atlas (TCGA) dataset. Unsupervised consensus clustering was performed to divide patients into two RNA modification clusters. Then, based on the differentially expressed genes (DEGs) among two clusters, RNA modification score (WM_Score) model was established to determine RNA modification-based subtypes and was validated in International Cancer Genome Consortium (ICGC) dataset. What's more, we manifested the unique status of WM_Score in transcriptional and post-transcriptional regulation, molecular biological characteristics, targeted therapies and immunogenomic patterns.

Results

We documented the tight-knit correlations between transcriptional expression and variation of RNA modification writers. We classified patients into two distinct RNA modification patterns (WM_Score_high and _low), The WM_Score_high subgroup was correlated with worse prognosis, Th2/Th17 cell polarization and oncogenic pathways (e.g. EMT, TGF-β, and mTORC1 signaling pathways), whereas the WM_Score_low subgroup associated with favorable survival rate and Th1 cell trend. WM_Score model also proved robust predictive power in interpreting transcriptional and post-transcriptional events. Additionally, the potential targeted compounds with related pathways for the WM_Score model were further identified.

Conclusions

Our research unfolds a novel horizon on the interplay network of four RNA modifications in PC. This WM_Score model demonstrated powerful predictive capacity in epigenetic, immunological and biological landscape, providing a theoretical basis for future clinical judgments of PC.

The emerging role of epigenetic regulation in the progression of silicosis

Silicosis is one of the most severe occupational diseases worldwide and is characterized by silicon nodules and diffuse pulmonary fibrosis. However, specific treatments for silicosis are still lacking at present. Therefore, elucidating the pathogenesis of silicosis plays a significant guiding role for its treatment and prevention. The occurrence and development of silicosis are accompanied by many regulatory mechanisms, including epigenetic regulation. The main epigenetic regulatory mechanisms of silicosis include DNA methylation, non-coding RNA (ncRNA), and histone modifications. In recent years, the expression and regulation of genes related to silicosis have been explored at epigenetic level to reveal its pathogenesis further, and the identification of aberrant epigenetic markers provides new biomarkers for prediction and diagnosis of silicosis. Here, we summarize the studies on the role of epigenetic changes in the pathogenesis of silicosis to give some clues for finding specific therapeutic targets for silicosis.

m1A-pred: Prediction of Modified 1-methyladenosine Sites in RNA Sequences through Artificial Intelligence

BACKGROUND

The process of nucleotides modification or methyl groups addition to nucleotides is known as post-transcriptional modification (PTM). 1-methyladenosine (m1A) is a type of PTM formed by adding a methyl group to the nitrogen at the 1st position of the adenosine base. Many human disorders are associated with m1A, which is widely found in ribosomal RNA and transfer RNA.

OBJECTIVE

The conventional methods such as mass spectrometry and site-directed mutagenesis proved to be laborious and burdensome. Systematic identification of modified sites from RNA sequences is gaining much attention nowadays. Consequently, an extreme gradient boost predictor, m1A-Pred, is developed in this study for the prediction of modified m1A sites.

METHODS

The current study involves the extraction of position and composition-based properties within nucleotide sequences. The extraction of features helps in the development of the features vector. Statistical moments were endorsed for dimensionality reduction in the obtained features.

RESULTS

Through a series of experiments using different computational models and evaluation methods, it was revealed that the proposed predictor, m1A-pred, proved to be the most robust and accurate model for the identification of modified sites.

AVAILABILITY AND IMPLEMENTATION

To enhance the research on m¹A sites, a friendly server was also developed, which was the final phase of this research.

Constructing and validating of m7G-related genes prognostic signature for hepatocellular carcinoma and immune infiltration: potential biomarkers for predicting the overall survival

Background

To investigate the prognostic significance of N7-methylguanosine (m7G) regulators and immune infiltration in liver hepatocellular carcinoma (LIHC).

Methods

The research measured predictive m7G genes in LIHC samples from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Data on the stemness index based on mRNA expression (mRNAsi), gene mutations, and corresponding clinical characteristics were obtained from TCGA and ICGC. Lasso regression was used to construct the prediction model to assess the m7G prognostic signals in LIHC. Based on these genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify key biological functions and pathways. The correlation between m7G RNA methylation regulators and the prognosis and immune infiltration of LIHC was evaluated.

Results

There were 21 m7G-related differentially expressed genes (DEGs) in LIHC and healthy tissues, and LIHC patients could be divided into two categories by consensus clustering of these DEGs. A five-gene predictive approach was employed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Patients in the low-risk group showed a significantly higher survival rate compared with those in the high-risk group (P=0.001). Validations using the ICGC database. Also, univariate and multivariate Cox regression analyses suggested that the risk score produced by the predictive model is an independent predictor for LIHC [hazard ratio (HR): 1.848, 95% confidence interval (CI): 1.286-2.656; HR: 2.597, 95% CI: 1.358-4.965]. The ROC curves of the ICGC cohort revealed that the five-gene prediction model performed well [area under the curve (AUC) =0.642 at 1 year, AUC =0.686 at 2 years, and AUC =0.667 at 3 years]. Immuno-oncology scoring revealed that in the high-risk group, among 16 immune cells, the expressions of neutrophils and natural killer (NK) cells were low and that of regulatory T-cells (Tregs) was high.

Conclusions

LIHC occurrence and progression are linked to m7G-related genes. Corresponding prognostic models help forecast the prognosis of LIHC patients. m7G-related genes and associated immune cell infiltration in the TME may serve as potential therapeutic targets in LIHC, which requires further trials. In addition, the m7G-related gene signature offers a viable alternative to predict LIHC, and these m7G-related genes show a prospective research area for LIHC targeted treatment in the future.

Metabolic Analysis of Nucleosides/Bases in the Urine and Serum of Patients with Alcohol-Associated Liver Disease

Accumulating evidence supports the important role of RNA modifications in liver disease pathogenesis. However, RNA modifications in alcohol-associated liver disease (ALD) have not yet been reported. Modified ribonucleosides/bases are products of RNA degradation; therefore, we investigated whether modified ribonucleosides/bases in human urine and serum are changed and whether these changes are associated with the severity of ALD. Human urine and serum samples from patients with ALD and appropriate controls were collected. Free nucleosides/bases were extracted from these samples and quantified using untargeted and targeted metabolomic approaches. Thirty-nine and forty free nucleosides/bases were respectively detected in human urine and serum samples. Twelve and eleven modified nucleosides are significantly changed in patients’ urine and serum (q < 0.05 and fold-change > 20%). The abundance of modified nucleobase and ribonucleoside, 7,9-dimethylguanine in urine and 2-methylthio-N6-threonylcarbamoyladenosine (ms2t6A) in serum are strongly associated with the severity of ALD. Spearman’s rank correlation coefficient of these two metabolites with the Model for End-stage Liver Disease (MELD) score are 0.66 and 0.74, respectively. Notably, the abundance changes in these two metabolites are sufficiently large to distinguish severe alcohol-associate hepatitis (AH) from non-severe ALD and non-severe ALD from healthy controls.

Integrative multiomics evaluation reveals the importance of pseudouridine synthases in hepatocellular carcinoma

Background: The pseudouridine synthases (PUSs) have been reported to be associated with cancers. However, their involvement in hepatocellular carcinoma (HCC) has not been well documented. Here, we assess the roles of PUSs in HCC. Methods: RNA sequencing data of TCGA-LIHC and LIRI-JP were downloaded from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), respectively. GSE36376 gene expression microarray was downloaded from the Gene Expression Omnibus (GEO). Proteomics data for an HBV-related HCC cohort was obtained from the CPTAC Data Portal. The RT-qPCR assay was performed to measure the relative mRNA expression of genes in clinical tissues and cell lines. Diagnostic efficiency was evaluated by the ROC curve. Prognostic value was assessed using the Kaplan-Meier curve, Cox regression model, and time-dependent ROC curve. Copy number variation (CNV) was analyzed using the GSCA database. Functional analysis was carried out with GSEA, GSVA, and clusterProfiler package. The tumor microenvironment (TME) related analysis was performed using ssGSEA and the ESTIMATE algorithm. Results: We identified 7 PUSs that were significantly upregulated in HCC, and 5 of them (DKC1, PUS1, PUS7, PUSL1, and RPUSD3) were independent risk factors for patients' OS. Meanwhile, the protein expression of DKC1, PUS1, and PUS7 was also upregulated and related to poor survival. Both mRNA and protein of these PUSs were highly diagnostic of HCC. Moreover, the CNV of PUS1, PUS7, PUS7L, and RPUSD2 was also associated with prognosis. Further functional analysis revealed that PUSs were mainly involved in pathways such as genetic information processing, substance metabolism, cell cycle, and immune regulation. Conclusion: PUSs may play crucial roles in HCC and could be used as potential biomarkers for the diagnosis and prognosis of patients.

Epitranscriptome: Review of Top 25 Most-Studied RNA Modifications

The alphabet of building blocks for RNA molecules is much larger than the standard four nucleotides. The diversity is achieved by the post-transcriptional biochemical modification of these nucleotides into distinct chemical entities that are structurally and functionally different from their unmodified counterparts. Some of these modifications are constituent and critical for RNA functions, while others serve as dynamic markings to regulate the fate of specific RNA molecules. Together, these modifications form the epitranscriptome, an essential layer of cellular biochemistry. As of the time of writing this review, more than 300 distinct RNA modifications from all three life domains have been identified. However, only a few of the most well-established modifications are included in most reviews on this topic. To provide a complete overview of the current state of research on the epitranscriptome, we analyzed the extent of the available information for all known RNA modifications. We selected 25 modifications to describe in detail. Summarizing our findings, we describe the current status of research on most RNA modifications and identify further developments in this field.

Structural basis for sequence-independent substrate selection by eukaryotic wobble base tRNA deaminase ADAT2/3

The essential deamination of adenosine A34 to inosine at the wobble base is the individual tRNA modification with the greatest effects on mRNA decoding, empowering a single tRNA to translate three different codons. To date, many aspects of how eukaryotic deaminases specifically select their multiple substrates remain unclear. Here, using cryo-EM, we present the structure of a eukaryotic ADAT2/3 deaminase bound to a full-length tRNA, revealing that the enzyme distorts the anticodon loop, but in contrast to the bacterial enzymes, selects its substrate via sequence-independent contacts of eukaryote-acquired flexible or intrinsically unfolded motifs distal from the conserved catalytic core. A gating mechanism for substrate entry to the active site is identified. Our multi-step tRNA recognition model yields insights into how RNA editing by A34 deamination evolved, shaped the genetic code, and directly impacts the eukaryotic proteome.

ALKBH5-mediated m6A modification of lincRNA LINC02551 enhances the stability of DDX24 to promote hepatocellular carcinoma growth and metastasis

As the most important RNA epigenetic regulation in eukaryotic cells, N6-metheyladenosine (m⁶A) modification has been demonstrated to play significant roles in cancer progression. However, this modification in long intergenic non-coding RNAs (lincRNAs) and the corresponding functions remain elusive. Here, we showed a lincRNA LINC02551 was downregulated by AlkB Homolog 5 (ALKBH5) overexpression in a m⁶A-dependent manner in hepatocellular carcinoma (HCC). Functionally, LINC02551 was required for the growth and metastasis of HCC. Mechanistically, LINC02551, a bona fide m⁶A target of ALKBH5, acted as a molecular adaptor that blocked the combination between DDX24 and a E3 ligase TRIM27 to decrease the ubiquitination and subsequent degradation of DDX24, ultimately facilitating HCC growth and metastasis. Thus, ALKBH5-mediated LINC02551 m⁶A methylation was required for HCC growth and metastasis.

RNA modifications: an overview of select web-based tools

The field of epitranscriptomics has expanded dramatically in recent years, both in the number of identified RNA modifications and the number of researchers studying them. As knowledge of post-transcriptional modifications continues to expand, numerous new methods have been developed to detect these modifications. Additionally, modifications are being extended to therapeutic settings, such as with recent mRNA vaccines. With this increase in knowledge and use, the community is recognizing the necessity for user-friendly databases to (i) store information from both high- and low-throughput studies and (ii) provide prediction software on how RNA modifications contribute to RNA function and disease. This mini-review highlights select RNA modification databases and their key attributes with the aim of providing a resource to researchers in the field of epitranscriptomics.

Dysfunctional tRNA reprogramming and codon-biased translation in cancer

Many cancers hijack translation to increase the synthesis of tumor-driving proteins, the messenger mRNAs of which have specific codon usage patterns. Termed 'codon-biased translation' and originally identified in stress response regulation, this mechanism is supported by diverse studies demonstrating how the 50 RNA modifications of the epitranscriptome, specific tRNAs, and codon-biased mRNAs are used by oncogenic programs to promote proliferation and chemoresistance. The epitranscriptome writers METTL1-WDR4, Elongator complex protein (ELP)1-6, CTU1-2, and ALKBH8-TRM112 illustrate the principal mechanism of codon-biased translation, with gene amplifications, increased RNA modifications, and enhanced tRNA stability promoting cancer proliferation. Furthermore, systems-level analyses of 34 tRNA writers and 493 tRNA genes highlight the theme of tRNA epitranscriptome dysregulation in many cancers and identify candidate tRNA writers, tRNA modifications, and tRNA molecules as drivers of pathological codon-biased translation.

Exploring the epitranscriptome by native RNA sequencing

Chemical RNA modifications, collectively referred to as the "epitranscriptome," are essential players in fine-tuning gene expression. Our ability to analyze RNA modifications has improved rapidly in recent years, largely due to the advent of high-throughput sequencing methodologies, which typically consist of coupling modification-specific reagents, such as antibodies or enzymes, to next-generation sequencing. Recently, it also became possible to map RNA modifications directly by sequencing native RNAs using nanopore technologies, which has been applied for the detection of a number of RNA modifications, such as N6-methyladenosine (m⁶A), pseudouridine (Ψ), and inosine (I). However, the signal modulations caused by most RNA modifications are yet to be determined. A global effort is needed to determine the signatures of the full range of RNA modifications to avoid the technical biases that have so far limited our understanding of the epitranscriptome.

RNA-binding proteins in regulating mRNA stability and translation: roles and mechanisms in cancer

RNA-binding proteins (RBPs) are key players in cellular physiology through posttranscriptional regulation of the expression of target RNA transcripts. By modulating the processing, stability and translation of cancer-related messenger RNA (mRNA) transcripts, a large set of RBPs play essential roles in various types of cancers. Perturbations in RBP activity have been causally associated with cancer development, tumor metabolism, drug resistance, cancer stem cell self-renewal, and tumor immune evasion. Here, we summarize the recent advances in cancer pathological roles and mechanisms of RBPs in regulating mRNA stability and translation with an emphasis on the emerging category of RNA modification-associated RBPs. The functional diversity of RBPs in different types of cancers and the therapeutic potential of targeting dysregulated RBPs for cancer treatment are also discussed.

The N6-methyladenosine methyltransferase METTL16 enables erythropoiesis through safeguarding genome integrity

During erythroid differentiation, the maintenance of genome integrity is key for the success of multiple rounds of cell division. However, molecular mechanisms coordinating the expression of DNA repair machinery in erythroid progenitors are poorly understood. Here, we discover that an RNA N⁶-methyladenosine (m⁶A) methyltransferase, METTL16, plays an essential role in proper erythropoiesis by safeguarding genome integrity via the control of DNA-repair-related genes. METTL16-deficient erythroblasts exhibit defective differentiation capacity, DNA damage and activation of the apoptotic program. Mechanistically, METTL16 controls m⁶A deposition at the structured motifs in DNA-repair-related transcripts including Brca2 and Fancm mRNAs, thereby upregulating their expression. Furthermore, a pairwise CRISPRi screen revealed that the MTR4-nuclear RNA exosome complex is involved in the regulation of METTL16 substrate mRNAs in erythroblasts. Collectively, our study uncovers that METTL16 and the MTR4-nuclear RNA exosome act as essential regulatory machinery to maintain genome integrity and erythropoiesis.

RM2Target: a comprehensive database for targets of writers, erasers and readers of RNA modifications

RNA modification is a dynamic and reversible process regulated by a series of writers, erasers and readers (WERs). Abnormal changes of WERs will disrupt the RNA modification homeostasis of their target genes, leading to the dysregulation of RNA metabolisms such as RNA stability and translation, and consequently to diseases such as cancer. A public repository hosting the regulatory relationships between WERs and their target genes will help in understanding the roles of RNA modifications in various physiological and pathological conditions. Previously, we developed a database named 'm6A2Target' to host targets of WERs in m6A, one of the most prevalent RNA modifications in eukaryotic cells. To host all RNA modification (RM)-related WER-target associations, we hereby present an updated database, named 'RM2Target' (http://rm2target.canceromics.org/). In this update, RM2Target encompasses 1 619 653 WER-target associations for nine RNA modifications in human and mouse, including m6A, m6Am, m5C, m5U, m1A, m7G, pseudouridine, 2'-O-Me and A-to-I. Extensive annotations of target genes are available in RM2Target, including but not limited to basic gene information, RNA modifications, RNA-RNA/RNA-protein interactions and related diseases. Altogether, we expect that RM2Target will facilitate further downstream functional and mechanistic studies in the field of RNA modification research.

Covalent Catalytic Strategies for Enzymes That Modify RNA Molecules on their Tripartite Building Blocks

The tripartite structures of the four 5'-nucleotide monophosphate (NMP) building blocks in all RNAs enable enzyme-catalyzed chemical modifications to three types of sites: the heterocyclic bases via N- and C-methylations and other alkylations, conversion of the N-glycoside linkages of the uridine moiety to the C-C glycoside link in pseudouridines, and the phosphodiester-mediated processes of 5'-capping, splicing, and 3'-tailing of premRNAs. We examine known cases for enzymatic covalent catalytic strategies that entail transient formation and breakdown of covalent enzyme-RNA adducts in each catalytic cycle. One case involves generation of the required carbon nucleophile during C₅ methylation of cytosine residues in RNAs. A second examines the mechanism proposed for pseudouridine synthases and for replacement of a guanine residue in tRNAs by queuosine. The third category involves phosphoric anhydride and phosphodiester chemistry by which viral RNAs encode enzymes for making their own mRNA 5'-caps. This strategy includes the recent finding that the SARS-CoV2 proteins assemble a canonical 5',5'-GTP cap on their 28 900 nucleotide genomic RNA to enable its translation as an mRNA by host translational machinery by way of a covalent RNA-viral enzyme intermediate.

A novel prognostic signature based on N7-methylguanosine-related long non-coding RNAs in breast cancer

Long non-coding RNA (lncRNA) are closely associated with the occurrence and progression of tumors. However, research on N7-methylguanosine (m7G)-related lncRNA in breast cancer is lacking. Therefore, the present study explored the prognostic value, gene expression characteristics, and effects of m7G-related lncRNA on tumor immune cell infiltration and tumor mutational burden (TMB) in breast cancer. lncRNA expression matrices and clinical follow-up data of patients with breast cancer were obtained from The Cancer Genome Atlas, revealing eight significantly differentially expressed and prognostically relevant m7G-related lncRNAs in breast cancer tissues: BAIAP2-DT, COL4A2-AS1, FARP1-AS1, RERE-AS1, NDUFA6-DT, TFAP2A-AS1, LINC00115, and MIR302CHG. A breast cancer prognostic signature was created based on these m7G-related lncRNAs according to least absolute shrinkage and selection operator Cox regression. The prognostic signature combined with potential prognostic factors showed independent prognostic value, reliability, and specificity. Meanwhile, we constructed a risk score-based nomogram to assist clinical decision-making. Gene set enrichment analysis revealed that low- and high-risk group were associated with metabolism-related pathways. Our study demonstrated the association between tumor immune cell infiltration based on analyses with the CIBERSORT algorithm and prognostic signature. We also assessed the correlation between prognostic signature and TMB. Lastly, quantitative real-time polymerase chain reaction analysis was performed to validate differentially expressed lncRNAs. The effective prognostic signature based on m7G-related lncRNAs has the potential to predict the survival prognosis of patients with breast cancer. The eight m7G-related lncRNAs identified in this study might represent potential biomarkers and therapeutic targets of breast cancer.

Comprehensive analysis of key m5C modification-related genes in type 2 diabetes

Background: 5-methylcytosine (m5C) RNA methylation plays a significant role in several human diseases. However, the functional role of m5C in type 2 diabetes (T2D) remains unclear.

Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. After LASSO regression, we constructed a diagnostic model and validated its accuracy. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to confirm the biological functions of DEGs. Gene Set Enrichment Analysis (GSEA) was used to determine the functional enrichment of molecular subtypes. Weighted gene co-expression network analysis (WGCNA) was used to select the module that correlated with the most pyroptosis-related genes. Protein-protein interaction (PPI) network was established using the STRING database, and hub genes were identified using Cytoscape software. The competitive endogenous RNA (ceRNA) interaction network of the hub genes was obtained. The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.

Results: m5C-related genes were significantly differentially expressed in T2D and correlated with most T2D-related DEGs. LASSO regression showed that ZBTB4 could be a predictive gene for T2D. GO, KEGG, and GSEA indicated that the enriched modules and pathways were closely related to metabolism-related biological processes and cell death. The top five genes were identified as hub genes in the PPI network. In addition, a ceRNA interaction network of hub genes was obtained. Moreover, the expression levels of the hub genes were significantly correlated with the abundance of various immune cells.

Conclusion: Our findings may provide insights into the molecular mechanisms underlying T2D based on its pathophysiology and suggest potential biomarkers and therapeutic targets for T2D.

Analysis of N6-Methyladenosine RNA Methylation Regulators in Diagnosis and Distinct Molecular Subtypes of Ankylosing Spondylitis

The most frequent internal modification in eukaryotic mRNA is N6-methyladenosine (m6A). However, what we know about the m6A regulators in Ankylosing spondylitis (AS) is still limited. In our study, eight distinct m6A regulators were selected utilizing Differentially Expressed Gene (DEG) analysis of the Gene Expression Omnibus GSE73754 dataset for making comparisons between AS (Ankylosing spondylitis) and non-AS patients. The random forest model and the nomogram model were used to screen the eight candidate m6A regulators and evaluate their prediction accuracy for the occurrence of AS. Furthermore, based on the selected m6A regulators, the AS patients were divided into two subgroups, and we applied principal component analysis algorithms to calculate their m6A score and evaluate the m6A patterns. Our findings revealed that patients in cluster A were linked to activated CD4 T cell immunity and activated CD8 T cell immunity. With its major contributions in the area of immunology, our research in m6A patterns may benefit the future diagnosis and treatment strategies of AS.

Biological functions of RNA modification patterns that define tumor microenvironment and survival outcomes in testicular germ cell tumors

BACKGROUND

Accumulating evidence has indicated that aberrant RNA modifications are associated with malignant progression and the immune microenvironment in various tumors. However, the function of RNA modification regulators in testicular germ cell tumors (TGCTs) remains to be discovered. This study aimed to investigate the biological functions of RNA modification regulators in testicular germ cell tumors and identify their potential clinical predictive value.

METHODS

Expression level of 75 RNA modification regulators was acquired to generate differential expression patterns. RNA modification regulatory genes were applied to construct a progression-free survival (PFS) risk model. Meanwhile, three RNA modification clusters were identified using consensus clustering. Subsequently, the infiltration characteristics of cells in the microenvironment as well as the antitumor drug candidates have been further analyzed. Finally, to further validate our results, we examined the expression and biological behavior of seven selected RNA modification regulators both in TGCT cell lines and clinical tissues.

RESULTS

We collected the differentially expressed regulators of RNA modification. RNA modification risk signature was developed to stratify the prognosis of TGCT patients. Furthermore, we found significant differences in immune microenvironment between subgroups. Ultimately, seven selected RNA modification regulators were further verified.

CONCLUSIONS

We generated and validated a risk signature related to RNA modification which could accurately predict the relapse risk in TGCT patients. This risk signature was correlated with immune cells infiltration among tumor microenvironments. Furthermore, we screened antitumor drug candidates and evaluated the sensitivity and efficacy of class chemotherapeutic drugs, which could provide reference for clinical drug use.

Identification of RNA Modification-Associated Alternative Splicing Signature as an Independent Factor in Head and Neck Squamous Cell Carcinoma

Objective

Head and neck squamous cell carcinoma (HNSCC) is a highly heterotopic malignant tumor. Alternative splicing (AS) and RNA modification have been reported to be involved in tumorigenesis. Therefore, we constructed RNA modification-associated AS (RMA-AS) signature model to predict the prognosis of HNSCC.

Methods

AS events and RNA-modified gene expression information were downloaded from TCGA-HNSCC database. Univariate Cox regression analysis was employed for analyzing prognosis-related AS events. RMA-AS events were obtained by constructing a coexpression network between RNA modification-associated genes and AS events using WGCNA package. The prognostic signatures were analyzed by LASSO, univariate Cox, and multivariate Cox regression. Kaplan-Meier survival analysis, proportional hazard model, and ROC curve were performed to verify the prognostic value. “ESTIMATE” R package, ssGSEA algorithm, and CIBERSORT method were used to detect immune microenvironment in HNSCC. Cytoscape was utilized to build a regulatory network of splicing factor-regulated RMA-AS.

Results

There were 16,574 prognostic AS events and 4 differentially expressed RNA modification-associated genes in HNSCC. Based on RMA-AS events, we obtained a risk model consisting of 14 AS events, named RMA-AS_Score. The samples were divided into RMA-AS_Score high- and RMA-AS_Score low-risk groups, according to the risk score. The RMA-AS_Score high group was related to poor prognosis. Moreover, the RMA-AS_Score signature was an independent prognostic predictor and was related to tumor grade. Meanwhile, the AUC value of RMA-AS_Score was 0.652, which is better than other clinical characteristics. Besides, a nomogram prediction model of quantitative prognosis has also been developed, which has robust effectiveness in predicting prognosis. In addition, the prognostic signature was observably related to immune microenvironment and immune checkpoint. Finally, 14 splicing factors were identified and constructed into a network of splicing factor-regulated RMA-AS.

Conclusion

We identified the RMA-AS signature of HNSCC. This signature could be treated as an independent prognostic predictor.

Domain specific mutations in dyskerin disrupt 3' end processing of scaRNA13

Mutations in DKC1 (encoding dyskerin) cause telomere diseases including dyskeratosis congenita (DC) by decreasing steady-state levels of TERC, the non-coding RNA component of telomerase. How DKC1 mutations variably impact numerous other snoRNAs remains unclear, which is a barrier to understanding disease mechanisms in DC beyond impaired telomere maintenance. Here, using DC patient iPSCs, we show that mutations in the dyskerin N-terminal extension domain (NTE) dysregulate scaRNA13. In iPSCs carrying the del37L NTE mutation or engineered to carry NTE mutations via CRISPR/Cas9, but not in those with C-terminal mutations, we found scaRNA13 transcripts with aberrant 3' extensions, as seen when the exoribonuclease PARN is mutated in DC. Biogenesis of scaRNA13 was rescued by repair of the del37L DKC1 mutation by genome-editing, or genetic or pharmacological inactivation of the polymerase PAPD5, which counteracts PARN. Inspection of the human telomerase cryo-EM structure revealed that in addition to mediating intermolecular dyskerin interactions, the NTE interacts with terminal residues of the associated snoRNA, indicating a role for this domain in 3' end definition. Our results provide mechanistic insights into the interplay of dyskerin and the PARN/PAPD5 axis in the biogenesis and accumulation of snoRNAs beyond TERC, broadening our understanding of ncRNA dysregulation in human diseases.

Significance of m6A regulatory factor in gene expression and immune function of osteoarthritis

One of the most prevalent posttranscriptional modifications of eukaryotic mRNA is the RNA N6-methyladenosine (m⁶A) regulator, which plays a significant role in various illnesses. The involvement of m⁶A regulators in osteoarthritis (OA) is not fully known. By comparing nonosteoarthritic and osteoarthritic patients, 26 important m⁶A regulators were identified from the gene expression omnibus GSE48556 dataset. Seven candidate m⁶A regulators (IGFBP3, WTAP, IGFBP1, HNRNPC, RBM15B, YTHDC1, and METTL3) were screened using a random forest model to assess the likelihood of OA. A column line graph model founded on seven m⁶A modulator candidates was created. According to decision curve analysis, patients might profit from the column line graph model. Based on chosen relevant m⁶A modifiers, a consensus clustering approach was utilized to categorize OA into two m⁶A categories (group A and group B). To measure the m⁶A pattern, a principal component analysis technique was created to generate the m⁶A score for every sample. Cluster A patients exhibited more excellent m⁶A scores than cluster B patients. Furthermore, we discovered that patients with lower and higher m⁶A scores had varied immunological responses using the m⁶A type. At last, m⁶A regulators contribute significantly to the progression of OA. Our research on m⁶A patterns might help to guide further OA immunotherapeutic techniques.

Exploring RNA modifications, editing, and splicing changes in hyperuricemia and gout

Hyperuricemia and gout are two of the most common metabolic disorders worldwide; their incidence is increasing with changes in lifestyle, and they are correlated with many diseases, including renal and cardiovascular diseases. The majority of studies on hyperuricemia and gout have focused on the discovery of the associated genes and their functions and on the roles of monocytes and neutrophils in the development of gout. Virtually no studies investigating the epigenomics of gout disease or exploring the clinical significance of such research have been conducted. In this study, we observed that the expression of enzymes involved in RNA modifications or RNA editing was affected in uric acid (UA)- or monosodium urate (MSU)-treated cell lines. RNA alternative splicing and splicing factors were also affected by UA or MSU treatment. We used transcriptome sequencing to analyze genome-wide RNA splicing and RNA editing and found significant changes in RNA splicing and RNA editing in MSU- or UA-treated THP-1 and HEK293 cells. We further found significant changes of RNA modifications, editing, and splicing in patients with gout. The data indicate that RNA modifications, editing, and splicing play roles in gout. The findings of this study may help to understand the mechanism of RNA splicing and modifications in gout, facilitating the development of new diagnostic and therapeutic strategies.

The pattern of expression and prognostic value of key regulators for m7G RNA methylation in hepatocellular carcinoma

N7-methylguanosine (m7G) modification on internal RNA positions plays a vital role in several biological processes. Recent research shows m7G modification is associated with multiple cancers. However, in hepatocellular carcinoma (HCC), its implications remain to be determined. In this place, we need to interrogate the mRNA patterns for 29 key regulators of m7G RNA modification and assess their prognostic value in HCC. Initial, the details from The Cancer Genome Atlas (TCGA) database concerning transcribed gene data and clinical information of HCC patients were inspected systematically. Second, according to the mRNA profiles of 29 m7G RNA methylation regulators, two clusters (named 1 and 2, respectively) were identified by consensus clustering. Furthermore, robust risk signature for seven m7G RNA modification regulators was constructed. Last, we used the Gene Expression Omnibus (GEO) dataset to validate the prognostic associations of the seven-gene risk signature. We figured out that 24/29 key regulators of m7G RNA modification varied remarkably in their grades of expression between the HCC and the adjacent tumor control tissues. Cluster one compared with cluster two had a substandard prognosis and was also positively correlated with T classification (T), pathological stage, and vital status (fustat) significantly. Consensus clustering results suggested the expression pattern of m7G RNA modification regulators was correlated with the malignancy of HCC strongly. In addition, cluster one was extensively enriched in metabolic-related pathways. Seven optimal genes (METTL1, WDR4, NSUN2, EIF4E, EIF4E2, NCBP1, and NCBP2) were selected to establish the risk model for HCC. Indicating by further analyses and validation, the prognostic model has fine anticipating command and this probability signature might be a self supporting presage factor for HCC. Finally, a new prognostic nomogram based on age, gender, pathological stage, histological grade, and prospects were established to forecast the prognosis of HCC patients accurately. In essence, we detected association of HCC severity and expression levels of m7G RNA modification regulators, and developed a risk score model for predicting prognosis of HCC patients’ progression.