An expanding universe of mRNA modifications

m6A-SPP: Identification of RNA N6-methyladenosine modification sites through multi-source biological features and a hybrid deep learning architecture

The N6-methyladenosine(m6A) modification plays crucial regulatory roles in various biological processes including gene expression regulation, RNA stability, splicing, and translation. Accurate prediction of m6A modification sites is essential for understanding their biological functions and implications in diseases. To address this, we introduce m6A-SPP, a novel deep learning framework for predicting m6A modification sites effectively. The model integrates both sequence features and physicochemical properties of RNA through two specialized modules. The sequence feature module leverages a pretrained bidirectional encoder representation of transformers (BERT) module (DNABERT), combined with convolutional neural networks (CNN), to provide refined processing of RNA sequence representations. The physicochemical feature module, on the other hand, computes feature embeddings by incorporating three crucial physicochemical properties. The feature matrices from both modules are then concatenated effectively and passed through fully connected layers to produce precise predictions of m6A modification sites. Comprehensive evaluations were performed on a dataset with single-nucleotide resolution for m6A, encompassing eight cell lines (such as HEK293T and HeLa) and three tissue types (including Brain, Liver, and Kidney). The experimental results demonstrate that m6A-SPP surpasses existing methods, highlighting its better performance in predicting m6A modification sites.

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.

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.

miRNA dosage control in development and human disease

In mammals, miRNAs recognize target mRNAs via base pairing, which leads to a complex 'multiple-to-multiple' regulatory network. Previous studies have focused on the regulatory mechanisms and functions of individual miRNAs, but alterations of many individual miRNAs do not strongly disturb the miRNA regulatory network. Recent studies revealed the important roles of global miRNA dosage control events in physiological processes and pathogenesis, suggesting that miRNAs can be considered as a 'cellular buffer' that controls cell fate. Here, we review the current state of research on how global miRNA dosage is tightly controlled to regulate development, tumorigenesis, neurophysiology, and immunity. We propose that methods of controlling global miRNA dosage may serve as effective therapeutic tools to cure human diseases.

Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues

MOTIVATION

RNA N6-methyladenosine (m6A) in Homo sapiens plays vital roles in a variety of biological functions. Precise identification of m6A modifications is thus essential to elucidation of their biological functions and underlying molecular-level mechanisms. Currently available high-throughput single-nucleotide-resolution m6A modification data considerably accelerated the identification of RNA modification sites through the development of data-driven computational methods. Nevertheless, existing methods have limitations in terms of the coverage of single-nucleotide-resolution cell lines and have poor capability in model interpretations, thereby having limited applicability.

RESULTS

In this study, we present CLSM6A, comprising a set of deep learning-based models designed for predicting single-nucleotide-resolution m6A RNA modification sites across eight different cell lines and three tissues. Extensive benchmarking experiments are conducted on well-curated datasets and accordingly, CLSM6A achieves superior performance than current state-of-the-art methods. Furthermore, CLSM6A is capable of interpreting the prediction decision-making process by excavating critical motifs activated by filters and pinpointing highly concerned positions in both forward and backward propagations. CLSM6A exhibits better portability on similar cross-cell line/tissue datasets, reveals a strong association between highly activated motifs and high-impact motifs, and demonstrates complementary attributes of different interpretation strategies.

AVAILABILITY AND IMPLEMENTATION

The webserver is available at http://csbio.njust.edu.cn/bioinf/clsm6a. The datasets and code are available at https://github.com/zhangying-njust/CLSM6A/.

Root Exposure of Graphitic Carbon Nitride (g-C3N4) Modulates Metabolite Profile and Endophytic Bacterial Community to Alleviate Cadmium- and Arsenate-Induced Phytotoxicity to Rice (Oryza sativa L.)

To investigate the mechanisms by which g-C3N4 alleviates metal(loid)-induced phytotoxicity, rice seedlings were exposed to 100 and 250 mg/kg graphitic carbon nitride (g-C3N4) with or without coexposure to 10 mg/kg Cd and 50 mg/kg As for 30 days. Treatment with 250 mg/kg g-C3N4 significantly increased shoot and root fresh weight by 22.4-29.9%, reduced Cd and As accumulations in rice tissues by 20.6-26.6%, and elevated the content of essential nutrients (e.g., K, S, Mg, Cu, and Zn) compared to untreated controls. High-throughput sequencing showed that g-C3N4 treatment increased the proportion of plant-growth-promoting endophytic bacteria, including Streptomyces, Saccharimonadales, and Thermosporothrix, by 0.5-3.30-fold; these groups are known to be important to plant nutrient assimilation, as well as metal(loid) resistance and bioremediation. In addition, the population of Deinococcus was decreased by 72.3%; this genus is known to induce biotransformation As(V) to As(III). Metabolomics analyses highlighted differentially expressed metabolites (DEMs) involved in the metabolism of tyrosine metabolism, pyrimidines, and purines, as well as phenylpropanoid biosynthesis related to Cd/As-induced phytotoxicity. In the phenylpropanoid biosynthesis pathway, the increased expression of 4-coumarate (1.13-fold) and sinapyl alcohol (1.26-fold) triggered by g-C3N4 coexposure with Cd or As played a critical role in promoting plant growth and enhancing rice resistance against metal(loid) stresses. Our findings demonstrate the potential of g-C3N4 to enhance plant growth and minimize the Cd/As-induced toxicity in rice and provide a promising nanoenabled strategy for remediating heavy metal(loid)-contaminated soil.

New insights into transcriptome variation during cattle adipocyte adipogenesis by direct RNA sequencing

We performed direct RNA sequencing (DRS) together with PCR-amplified cDNA long and short read sequencing for cattle adipocyte at different stages. We proved that the DRS was with advantages to avoid artificial transcripts and questionable exitrons. Totally, we obtained 68,124 transcripts with information of alternative splicing, poly (A) length and mRNA modification. The number of transcripts for adipogenesis was expanded by alternative splicing, which lead regulation mechanisms far more complex than ever known. We detected 891 differentially expressed genes (DEGs). However, 62.78% transcripts of DEGs were not significantly differentially expressed, and 248 transcripts showed opposite changing directions with their genes. The poly (A) tail became globally shorter in differentiated adipocyte than in primary adipocyte, and had a weak negative correlation with gene/transcript expression. Moreover, the study of different mRNA modifications implied their potential roles in gene expression and alternative splicing. Overall, our study promoted better understanding of adipogenesis mechanisms in cattle adipocytes.

Prediction of Multiple Types of RNA Modifications via Biological Language Model

It has been demonstrated that RNA modifications play essential roles in multiple biological processes. Accurate identification of RNA modifications in the transcriptome is critical for providing insights into the biological functions and mechanisms. Many tools have been developed for predicting RNA modifications at single-base resolution, which employ conventional feature engineering methods that focus on feature design and feature selection processes that require extensive biological expertise and may introduce redundant information. With the rapid development of artificial intelligence technologies, end-to-end methods are favorably received by researchers. Nevertheless, each well-trained model is only suitable for a specific RNA methylation modification type for nearly all of these approaches. In this study, we present MRM-BERT by feeding task-specific sequences into the powerful BERT (Bidirectional Encoder Representations from Transformers) model and implementing fine-tuning, which exhibits competitive performance to the state-of-the-art methods. MRM-BERT avoids repeated de novo training of the model and can predict multiple RNA modifications such as pseudouridine, m6A, m5C, and m1A in Mus musculus, Arabidopsis thaliana, and Saccharomyces cerevisiae. In addition, we analyse the attention heads to provide high attention regions for the prediction, and conduct saturated in silico mutagenesis of the input sequences to discover potential changes of RNA modifications, which can better assist researchers in their follow-up research.

Advances in mRNA therapeutics for cancer immunotherapy: From modification to delivery

RNA vaccines have demonstrated their ability to solve the issues posed by the COVID-19 pandemic. This success has led to the renaissance of research into mRNA and their nanoformulations as potential therapeutic modalities for various diseases. The potential of mRNA as a template for synthesizing proteins and protein fragments for cancer immunotherapy is now being explored. Despite the promise, the use of mRNA in cancer immunotherapy is limited by challenges, such as low stability against extracellular RNases, poor delivery efficiency to the target organs and cells, short circulatory half-life, variable expression levels and duration. This review highlights recent advances in chemical modification and advanced delivery systems that are helping to address these challenges and unlock the biological and pharmacological potential of mRNA therapeutics in cancer immunotherapy. The review concludes by discussing future perspectives for mRNA-based cancer immunotherapy, which holds great promise as a next-generation therapeutic modality.

A Novel 7-Methylguanosine (m7G)-Related Gene Signature for Overall Survival Prediction in Patient with Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type of renal cancer that has an abysmal prognosis. Although a crucial role for 7-methylguanosine modification in cancer cell development has been reported, its role in ccRCC remains uncertain. This study was conducted to determine the efficacy of predictive biomarkers based on m7G-related genes in ccRCC. Firstly, we extracted clinical data and gene expression profiles of ccRCC patients from publicly accessible databases. It identified that 22 of the m7G-related 34 genes were related to overall survival, and 5 of the 22 genes were significantly expressed differently in tumor tissues. Based on Lasso regression analysis, five optimal genes (CYFIP2, EIF4A1, NUDT1, NUDT10, and NUDT4) were chosen to build a new predictive risk model in the TCGA cohort. Validation was carried out with the E-MTAB-1980 cohort. Then, a prognostic nomogram was erected, including the m7G-related gene risk score, age, histological grade, and stage status. Further studies and analysis showed that immune cell infiltration might be associated with the m7G-related risk genes. In addition, the relationship between gene expression and drug response was evaluated by the Pearson correlation test. Therefore, the risk signature with five selected m7G-related genes may be a promising prognostic biomarker and contribute to standardized prognostic assessment for ccRCC.

M7G-related LncRNAs: A comprehensive analysis of the prognosis and immunity in glioma

Today, numerous international researchers have demonstrated that N7-methylguanosine (m7G) related long non-coding RNAs (m7G-related lncRNAs) are closely linked to the happenings and developments of various human beings’ cancers. However, the connection between m7G-related lncRNAs and glioma prognosis has not been investigated. We did this study to look for new potential biomarkers and construct an m7G-related lncRNA prognostic signature for glioma. We identified those lncRNAs associated with DEGs from glioma tissue sequences as m7G-related lncRNAs. First, we used Pearson’s correlation analysis to identify 28 DEGs by glioma and normal brain tissue gene sequences and predicated 657 m7G-related lncRNAs. Then, eight lncRNAs associated with prognosis were obtained and used to construct the m7G risk score model by lasso and Cox regression analysis methods. Furthermore, we used Kaplan-Meier analysis, time-dependent ROC, principal component analysis, clinical variables, independent prognostic analysis, nomograms, calibration curves, and expression levels of lncRNAs to determine the model’s accuracy. Importantly, we validated the model with external and internal validation methods and found it has strong predictive power. Finally, we performed functional enrichment analysis (GSEA, aaGSEA enrichment analyses) and analyzed immune checkpoints, associated pathways, and drug sensitivity based on predictors. In conclusion, we successfully constructed the formula of m7G-related lncRNAs with powerful predictive functions. Our study provides instructional value for analyzing glioma pathogenesis and offers potential research targets for glioma treatment and scientific research.

Single-base resolution mapping of 2′-O-methylation sites by an exoribonuclease-enriched chemical method

2'-O-methylation (Nm) is one of the most abundant RNA epigenetic modifications and plays a vital role in the post-transcriptional regulation of gene expression. Current Nm mapping approaches are normally limited to highly abundant RNAs and have significant technical hurdles in mRNAs or relatively rare non-coding RNAs (ncRNAs). Here, we developed a new method for enriching Nm sites by using RNA exoribonuclease and periodate oxidation reactivity to eliminate 2'-hydroxylated (2'-OH) nucleosides, coupled with sequencing (Nm-REP-seq). We revealed several novel classes of Nm-containing ncRNAs as well as mRNAs in humans, mice, and drosophila. We found that some novel Nm sites are present at fixed positions in different tRNAs and are potential substrates of fibrillarin (FBL) methyltransferase mediated by snoRNAs. Importantly, we discovered, for the first time, that Nm located at the 3'-end of various types of ncRNAs and fragments derived from them. Our approach precisely redefines the genome-wide distribution of Nm and provides new technologies for functional studies of Nm-mediated gene regulation.

Collateral Damage Occurs When Using Photosensitizer Probes to Detect or Modulate Nucleic Acid Modifications

Nucleic acids are chemically modified to fine-tune their properties for biological function. Chemical tools for selective tagging of base modifications enables new approaches; the photosensitizers riboflavin and anthraquinone were previously proposed to oxidize N⁶ -methyladenine (m⁶ A) or 5-methylcytosine (5mdC) selectively. Herein, riboflavin, anthraquinone, or Rose Bengal were allowed to react with the canonical nucleosides dA, dC, dG, and dT, and the modified bases 5mdC, m⁶ A, 8-oxoguanine (dOG), and 8-oxoadenine (dOA) to rank their reactivities. The nucleoside studies reveal that dOG is the most reactive and that the native nucleoside dG is higher or similar in reactivity to 5mdC or m⁶ A; competition in both single- and double-stranded DNA of dG vs. 5mdC or 6mdA for oxidant confirmed that dG is favorably oxidized. Thus, photosensitizers are promiscuous nucleic acid oxidants with poor chemoselectivity that will negatively impact attempts at targeted oxidation of modified nucleotides in cells.

m7GDisAI: N7-methylguanosine (m7G) sites and diseases associations inference based on heterogeneous network

Background

Recent studies have confirmed that N7-methylguanosine (m⁷G) modification plays an important role in regulating various biological processes and has associations with multiple diseases. Wet-lab experiments are cost and time ineffective for the identification of disease-associated m⁷G sites. To date, tens of thousands of m⁷G sites have been identified by high-throughput sequencing approaches and the information is publicly available in bioinformatics databases, which can be leveraged to predict potential disease-associated m⁷G sites using a computational perspective. Thus, computational methods for m⁷G-disease association prediction are urgently needed, but none are currently available at present.

Results

To fill this gap, we collected association information between m⁷G sites and diseases, genomic information of m⁷G sites, and phenotypic information of diseases from different databases to build an m⁷G-disease association dataset. To infer potential disease-associated m⁷G sites, we then proposed a heterogeneous network-based model, m⁷G Sites and Diseases Associations Inference (m⁷GDisAI) model. m⁷GDisAI predicts the potential disease-associated m⁷G sites by applying a matrix decomposition method on heterogeneous networks which integrate comprehensive similarity information of m⁷G sites and diseases. To evaluate the prediction performance, 10 runs of tenfold cross validation were first conducted, and m⁷GDisAI got the highest AUC of 0.740(± 0.0024). Then global and local leave-one-out cross validation (LOOCV) experiments were implemented to evaluate the model’s accuracy in global and local situations respectively. AUC of 0.769 was achieved in global LOOCV, while 0.635 in local LOOCV. A case study was finally conducted to identify the most promising ovarian cancer-related m⁷G sites for further functional analysis. Gene Ontology (GO) enrichment analysis was performed to explore the complex associations between host gene of m⁷G sites and GO terms. The results showed that m⁷GDisAI identified disease-associated m⁷G sites and their host genes are consistently related to the pathogenesis of ovarian cancer, which may provide some clues for pathogenesis of diseases.

Conclusion

The m⁷GDisAI web server can be accessed at http://180.208.58.66/m7GDisAI/, which provides a user-friendly interface to query disease associated m⁷G. The list of top 20 m⁷G sites predicted to be associted with 177 diseases can be achieved. Furthermore, detailed information about specific m⁷G sites and diseases are also shown.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04007-9.

A brief review of RNA modification related database resources

To date, over 150 different RNA modifications have been identified, playing crucial roles in biological processes and disease pathogenesis. Thanks to the advancement of high-throughput sequencing technologies employed for transcriptome-wide mapping, a bunch of RNA modification databases have emerged as an exciting area, which promotes further investigation of the mechanisms and functions of these modified ribonucleotides. This article introduces the high-throughput sequencing technique developed for transcriptome-wide mapping of RNA modifications, as well as the procedures and main techniques of building these databases from the developers' perspective. It also reviews existing RNA modification databases in terms of their main functions, species, the number of sites they collected, the annotations, and the tools they provided. From the view of users, we further analyze and compare these databases in terms of their functions. For instance, these databases can be applied to record chemical structures and biosynthetic pathways, or unravel the epi-transcriptome comprehensively, or only investigate specific features of RNA modifications. Additionally, the limitations of the existing approaches are discussed, and some future suggestions are offered.

Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics

Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.

m7GHub: deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human

MOTIVATION

Recent progress in N7-methylguanosine (m7G) RNA methylation studies has focused on its internal (rather than capped) presence within mRNAs. Tens of thousands of internal mRNA m7G sites have been identified within mammalian transcriptomes, and a single resource to best share, annotate and analyze the massive m7G data generated recently are sorely needed.

RESULTS

We report here m7GHub, a comprehensive online platform for deciphering the location, regulation and pathogenesis of internal mRNA m7G. The m7GHub consists of four main components, including: the first internal mRNA m7G database containing 44 058 experimentally validated internal mRNA m7G sites, a sequence-based high-accuracy predictor, the first web server for assessing the impact of mutations on m7G status, and the first database recording 1218 disease-associated genetic mutations that may function through regulation of m7G methylation. Together, m7GHub will serve as a useful resource for research on internal mRNA m7G modification.

AVAILABILITY AND IMPLEMENTATION

m7GHub is freely accessible online at www.xjtlu.edu.cn/biologicalsciences/m7ghub.

CONTACT

kunqi.chen@liverpool.ac.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ontogenic mRNA expression of RNA modification writers, erasers, and readers in mouse liver

RNA modifications are recently emerged epigenetic modifications. These diverse RNA modifications have been shown to regulate multiple biological processes, including development. RNA modifications are dynamically controlled by the “writers, erasers, and readers”, where RNA modifying proteins are able to add, remove, and recognize specific chemical modification groups on RNAs. However, little is known about the ontogenic expression of these RNA modifying proteins in various organs, such as liver. In the present study, the hepatic mRNA expression of selected RNA modifying proteins involve in m⁶A, m¹A, m⁵C, hm⁵C, m⁷G, and Ψ modifications was analyzed using the RNA-seq technique. Liver samples were collected from male C57BL/6 mice at several ages from prenatal through neonatal, infant, child to young adult. Results showed that most of the RNA modifying proteins were highly expressed in prenatal mouse liver with a dramatic drop at birth. After birth, most of the RNA modifying proteins showed a downregulation trend during liver maturation. Moreover, the RNA modifying proteins that belong to the same enzyme family were expressed at different abundances at the same ages in mouse liver. In conclusion, this study unveils that the mRNA expression of RNA modifying proteins follows specific ontogenic expression patterns in mice liver during maturation. These data indicated that the changes in expression of RNA modifying proteins might have a potential role to regulate gene expression in liver through alteration of RNA modification status.

Synthesis of an acp3U phosphoramidite and incorporation of the hypermodified base into RNA

acp3U is a hypermodified base that is found in the tRNAs of prokaryotes and eukaryotes and also in the ribosomal RNA of mammals. Its function has so far been unknown but it is speculated that acp3U complexes Mg ions, which may contribute to the stabilization of the RNA structure. As a hypermodified base in which a nucleoside is covalently connected to an amino acid, acp3U is a natural nucleoside between genotype and phenotype and hence is also of particular importance for theories about the origin of life. Herein, we report the development of a phosphoramidite building block and of a solid phase protocol that allows synthesis of RNA containing acp3U.

Structural Elucidation of Bisulfite Adducts to Pseudouridine That Result in Deletion Signatures during Reverse Transcription of RNA

The recent report of RBS-Seq to map simultaneously the epitranscriptomic modifications N¹-methyladenosine, 5-methylcytosine, and pseudouridine (Ψ) via bisulfite treatment of RNA provides a key advance to locate these important modifications. The locations of Ψ were found by a deletion signature generated during cDNA synthesis after bisulfite treatment for which the chemical details of the reaction are poorly understood. In the present work, the bisulfite reaction with Ψ was explored to identify six isomers of bisulfite adducted to Ψ. We found four of these adducts involved the heterocyclic ring, similar to the reaction with other pyrimidines. The remaining two adducts were bonded to the 1' carbon, which resulted in opening of the ribose ring. The utilization of complementary 1D- and 2D-NMR, Raman, and electronic circular dichroism spectroscopies led to the assignment of the two ribose adducts being the constitutional isomers of an S- and an O-adduct of bisulfite to the ribose, and these are the final products after heating. A mechanistic proposal is provided to rationalize chemically the formation and stereochemistries of all six isomeric bisulfite adducts to Ψ; conversion of intermediate adducts to the two final products is proposed to involve E2, S_N2', and [2,3]-sigmatropic shift reactions. Lastly, a synthetic RNA template with Ψ at a known location was treated with bisulfite, leading to a deletion signature after reverse transcription, supporting the RBS-Seq report. This classical bisulfite reaction used for epigenomic and epitranscriptomic sequencing diverges from the C nucleoside Ψ to form stable bisulfite end products that yield signatures for next-generation sequencing.

RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data

More than 100 distinct chemical modifications to RNA have been characterized so far. However, the prevalence, mechanisms and functions of various RNA modifications remain largely unknown. To provide transcriptome-wide landscapes of RNA modifications, we developed the RMBase v2.0 (http://rna.sysu.edu.cn/rmbase/), which is a comprehensive database that integrates epitranscriptome sequencing data for the exploration of post-transcriptional modifications of RNAs and their relationships with miRNA binding events, disease-related single-nucleotide polymorphisms (SNPs) and RNA-binding proteins (RBPs). RMBase v2.0 was expanded with ∼600 datasets and ∼1 397 000 modification sites from 47 studies among 13 species, which represents an approximately 10-fold expansion when compared with the previous release. It contains ∼1 373 000 N6-methyladenosines (m⁶A), ∼5400 N1-methyladenosines (m¹A), ∼9600 pseudouridine (Ψ) modifications, ∼1000 5-methylcytosine (m⁵C) modifications, ∼5100 2′-O-methylations (2′-O-Me), and ∼2800 modifications of other modification types. Moreover, we built a new module called ‘Motif’ that provides the visualized logos and position weight matrices (PWMs) of the modification motifs. We also constructed a novel module termed ‘modRBP’ to study the relationships between RNA modifications and RBPs. Additionally, we developed a novel web-based tool named ‘modMetagene’ to plot the metagenes of RNA modification along a transcript model. This database will help researchers investigate the potential functions and mechanisms of RNA modifications.

Eukaryotic Translation Elongation is Modulated by Single Natural Nucleotide Derivatives in the Coding Sequences of mRNAs

RNA modifications are crucial factors for efficient protein synthesis. All classes of RNAs that are involved in translation are modified to different extents. Recently, mRNA modifications and their impact on gene regulation became a focus of interest because they can exert a variety of effects on the fate of mRNAs. mRNA modifications within coding sequences can either directly or indirectly interfere with protein synthesis. In order to investigate the roles of various natural occurring modified nucleotides, we site-specifically introduced them into the coding sequence of reporter mRNAs and subsequently translated them in HEK293T cells. The analysis of the respective protein products revealed a strong position-dependent impact of RNA modifications on translation efficiency and accuracy. Whereas a single 5-methylcytosine (m⁵C) or pseudouridine (Ψ) did not reduce product yields, N¹-methyladenosine (m¹A) generally impeded the translation of the respective modified mRNA. An inhibitory effect of 2′O-methlyated nucleotides (Nm) and N⁶-methyladenosine (m⁶A) was strongly dependent on their position within the codon. Finally, we could not attribute any miscoding potential to the set of mRNA modifications tested in HEK293T cells.

Decoding the Atlas of RNA Modifications from Epitranscriptome Sequencing Data

Over 100 types of chemical modifications have been identified in protein-coding and noncoding RNAs (ncRNAs). However, the prevalence, regulation, and function of diverse RNA modifications remain largely unknown. In this chapter, we describe how to annotate, visualize, and analyze the RNA modification sites from the high-throughput epitranscriptome sequencing data using RMBase platform and software. We developed two stand-alone computational software, modAnnotator and metaProfile, to annotate and visualize RNA modification sites and their prevalence in the gene body. In addition, we constructed interactive web implementations to decode the atlas of various RNA modifications, including the N6-methyladenosine (m⁶A) modification, pseudouridine (Ψ) modification, 5-methylcytosine (m⁵C) modification, and 2'-O-methylation (2'-O-Me) modification, as well as other types of modifications. We also developed web-based interfaces to analyze the associations between RNA modification sites with miRNA target sites and disease-related single-nucleotide polymorphisms (SNPs). Moreover, RMBase provides a genome browser and a web-based modTool to query, annotate, and visualize various RNA modifications. RMBase is expected to provide comprehensive interfaces and tools to facilitate the analysis and functional study of the massive RNA modification sites. The software and platform are available at http://rna.sysu.edu.cn/rmbase/modSoftware.php .

Uridine Depletion and Chemical Modification Increase Cas9 mRNA Activity and Reduce Immunogenicity without HPLC Purification

The Cas9/guide RNA (Cas9/gRNA) system is commonly used for genome editing. mRNA expressing Cas9 can induce innate immune responses, reducing Cas9 expression. First-generation Cas9 mRNAs were modified with pseudouridine and 5-methylcytosine to reduce innate immune responses. We combined four approaches to produce more active, less immunogenic second-generation Cas9 mRNAs. First, we developed a novel co-transcriptional capping method yielding natural Cap 1. Second, we screened modified nucleotides in Cas9 mRNA to identify novel modifications that increase Cas9 activity. Third, we depleted the mRNA of uridines to improve mRNA activity. Lastly, we tested high-performance liquid chromatography (HPLC) purification to remove double-stranded RNAs. The activity of these mRNAs was tested in cell lines and primary human CD34+ cells. Cytokines were measured in whole blood and mice. These approaches yielded more active and less immunogenic mRNA. Uridine depletion (UD) most impacted insertion or deletion (indel) activity. Specifically, 5-methoxyuridine UD induced indel frequencies as high as 88% (average ± SD = 79% ± 11%) and elicited minimal immune responses without needing HPLC purification. Our work suggests that uridine-depleted Cas9 mRNA modified with 5-methoxyuridine (without HPLC purification) or pseudouridine may be optimal for the broad use of Cas9 both in vitro and in vivo.

Above the Epitranscriptome: RNA Modifications and Stem Cell Identity

Sequence databases and transcriptome-wide mapping have revealed different reversible and dynamic chemical modifications of the nitrogen bases of RNA molecules. Modifications occur in coding RNAs and noncoding-RNAs post-transcriptionally and they can influence the RNA structure, metabolism, and function. The result is the expansion of the variety of the transcriptome. In fact, depending on the type of modification, RNA molecules enter into a specific program exerting the role of the player or/and the target in biological and pathological processes. Many research groups are exploring the role of RNA modifications (alias epitranscriptome) in cell proliferation, survival, and in more specialized activities. More recently, the role of RNA modifications has been also explored in stem cell biology. Our understanding in this context is still in its infancy. Available evidence addresses the role of RNA modifications in self-renewal, commitment, and differentiation processes of stem cells. In this review, we will focus on five epitranscriptomic marks: N6-methyladenosine, N1-methyladenosine, 5-methylcytosine, Pseudouridine (Ψ) and Adenosine-to-Inosine editing. We will provide insights into the function and the distribution of these chemical modifications in coding RNAs and noncoding-RNAs. Mainly, we will emphasize the role of epitranscriptomic mechanisms in the biology of naïve, primed, embryonic, adult, and cancer stem cells.

Probing the mechanisms underlying human diseases in making ribosomes

Ribosomes are essential, highly complex machines responsible for protein synthesis in all growing cells. Because of their importance, the process of building these machines is intricately regulated. Although the proteins involved in regulating ribosome biogenesis are just beginning to be understood, especially in human cells, the consequences for dysregulating this process have been even less studied. Such interruptions in ribosome synthesis result in a collection of human disorders known as ribosomopathies. Ribosomopathies, which occur due to mutations in proteins involved in the global process of ribosome biogenesis, result in tissue-specific defects. The questions posed by this dichotomy and the steps taken to address these questions are therefore the focus of this review: How can tissue-specific disorders result from alterations in global processes? Could ribosome specialization account for this difference?

Advances in analyzing RNA diversity in eukaryotic transcriptomes: peering through the Omics lens

Alternative splicing, polyadenylation, and chemical modifications of RNA generate astonishing complexity within eukaryotic transcriptomes. The last decade has brought numerous advances in sequencing technologies that allow biologists to investigate these phenomena with greater depth and accuracy while reducing time and cost. A commensurate development in biochemical techniques for the enrichment and analysis of different RNA variants has accompanied the advancement of global sequencing analysis platforms. Here, we present a detailed overview of the latest biochemical methods, along with bioinformatics pipelines that have aided in identifying different RNA variants. We also highlight the ongoing developments and challenges associated with RNA variant detection and quantification, including sample heterogeneity and isolation, as well as 'Omics' big data handling.

RNAs Containing Modified Nucleotides Fail To Trigger RIG-I Conformational Changes for Innate Immune Signaling

Invading pathogen nucleic acids are recognized and bound by cytoplasmic (retinoic acid-inducible gene I [RIG-I]-like) and membrane-bound (Toll-like) pattern recognition receptors to activate innate immune signaling. Modified nucleotides, when present in RNA molecules, diminish the magnitude of these signaling responses. However, mechanisms explaining the blunted signaling have not been elucidated. In this study, we used several independent biological assays, including inhibition of virus replication, RIG-I:RNA binding assays, and limited trypsin digestion of RIG-I:RNA complexes, to begin to understand how RNAs containing modified nucleotides avoid or suppress innate immune signaling. The experiments were based on a model innate immune activating RNA molecule, the polyU/UC RNA domain of hepatitis C virus, which was transcribed in vitro with canonical nucleotides or with one of eight modified nucleotides. The approach revealed signature assay responses associated with individual modified nucleotides or classes of modified nucleotides. For example, while both N-6-methyladenosine (m6A) and pseudouridine nucleotides correlate with diminished signaling, RNA containing m6A modifications bound RIG-I poorly, while RNA containing pseudouridine bound RIG-I with high affinity but failed to trigger the canonical RIG-I conformational changes associated with robust signaling. These data advance understanding of RNA-mediated innate immune signaling, with additional relevance for applying nucleotide modifications to RNA therapeutics.

The innate immune system provides the first response to virus infections and must distinguish between host and pathogen nucleic acids to mount a protective immune response without activating autoimmune responses. While the presence of nucleotide modifications in RNA is known to correlate with diminished innate immune signaling, the underlying mechanisms have not been explored. The data reported here are important for defining mechanistic details to explain signaling suppression by RNAs containing modified nucleotides. The results suggest that RNAs containing modified nucleotides interrupt signaling at early steps of the RIG-I-like innate immune activation pathway and also that nucleotide modifications with similar chemical structures can be organized into classes that suppress or evade innate immune signaling steps. These data contribute to defining the molecular basis for innate immune signaling suppression by RNAs containing modified nucleotides. The results have important implications for designing therapeutic RNAs that evade innate immune detection.

The Cardiomyocyte RNA-Binding Proteome: Links to Intermediary Metabolism and Heart Disease

RNA functions through the dynamic formation of complexes with RNA-binding proteins (RBPs) in all clades of life. We determined the RBP repertoire of beating cardiomyocytic HL-1 cells by jointly employing two in vivo proteomic methods, mRNA interactome capture and RBDmap. Together, these yielded 1,148 RBPs, 391 of which are shared with all other available mammalian RBP repertoires, while 393 are thus far unique to cardiomyocytes. RBDmap further identified 568 regions of RNA contact within 368 RBPs. The cardiomyocyte mRNA interactome composition reflects their unique biology. Proteins with roles in cardiovascular physiology or disease, mitochondrial function, and intermediary metabolism are all highly represented. Notably, we identified 73 metabolic enzymes as RBPs. RNA-enzyme contacts frequently involve Rossmann fold domains with examples in evidence of both, mutual exclusivity of, or compatibility between RNA binding and enzymatic function. Our findings raise the prospect of previously hidden RNA-mediated regulatory interactions among cardiomyocyte gene expression, physiology, and metabolism.

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mRNA interactome capture and RBDmap reveal the cardiomyocyte RNA-binding proteome

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1,148 RBPs are identified, 393 of which are thus far unique to cardiomyocytes

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Many cardiac RBPs have links to heart disease and mitochondrial metabolism

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Contacts of metabolic enzymes with RNA frequently involve Rossmann fold domains

Fluorescent RNA Aptamers as a Tool to Study RNA-Modifying Enzymes

RNA-modifying enzymes are difficult to assay due to the absence of fluorometric substrates. Here we show that the Broccoli, a previously reported fluorescent RNA-dye complex, can be modified to contain N(6)-methyladenosine, a prevalent mRNA base modification. Methylated Broccoli is nonfluorescent but, upon demethylation by the RNA demethylases fat mass and obesity-associated protein (FTO) or ALKBH5, it binds and activates the fluorescence of its cognate fluorophore. We describe a high-throughput screen (HTS) for FTO inhibitors using the fluorogenic methylated Broccoli substrate HTS assay, which performs robustly with a Z' factor >0.8 in the LOPAC1280 library. This allowed the identification of novel high-affinity FTO inhibitors. Several of these compounds were selective for FTO over the related demethylase, ALKBH5, and increase methylation of endogenous FTO target mRNAs in cells. Lastly, we show that Broccoli can be modified to contain other base modifications, suggesting that this approach could be generally applicable for assaying diverse RNA-modifying enzymes.

DRME: Count-based differential RNA methylation analysis at small sample size scenario

Differential methylation, which concerns difference in the degree of epigenetic regulation via methylation between two conditions, has been formulated as a beta or beta-binomial distribution to address the within-group biological variability in sequencing data. However, a beta or beta-binomial model is usually difficult to infer at small sample size scenario with discrete reads count in sequencing data. On the other hand, as an emerging research field, RNA methylation has drawn more and more attention recently, and the differential analysis of RNA methylation is significantly different from that of DNA methylation due to the impact of transcriptional regulation. We developed DRME to better address the differential RNA methylation problem. The proposed model can effectively describe within-group biological variability at small sample size scenario and handles the impact of transcriptional regulation on RNA methylation. We tested the newly developed DRME algorithm on simulated and 4 MeRIP-Seq case-control studies and compared it with Fisher's exact test. It is in principle widely applicable to several other RNA-related data types as well, including RNA Bisulfite sequencing and PAR-CLIP. The code together with an MeRIP-Seq dataset is available online (https://github.com/lzcyzm/DRME) for evaluation and reproduction of the figures shown in this article.

High-resolution measurement of long-range distances in RNA: pulse EPR spectroscopy with TEMPO-labeled nucleotides

Distance measurements in RNAs by pulse EPR with TEMPO-labeled nucleotides allow for model free conversion of distances into base-pair separation.

Structural information at atomic resolution of biomolecular assemblies, such as RNA and RNA protein complexes, is fundamental to comprehend biological function. Modern spectroscopic methods offer exceptional opportunities in this direction. Here we present the capability of pulse EPR to report high-resolution long-range distances in RNAs by means of a recently developed spin labeled nucleotide, which carries the TEMPO group directly attached to the nucleobase and preserves Watson–Crick base-pairing. In a representative RNA duplex with spin-label separations up to 28 base pairs (≈8 nm) we demonstrate that the label allows for a model-free conversion of inter-spin distances into base-pair separation (Δbp) if broad-band pulse excitation at Q band frequencies (34 GHz) is applied. The observed distance distribution increases from ±0.2 nm for Δbp = 10 to only ±0.5 nm for Δbp = 28, consistent with only small deviations from the “ideal” A-form RNA structure. Molecular dynamics (MD) simulations conducted at 20 °C show restricted conformational freedom of the label. MD-generated structural deviations from an “ideal” A-RNA geometry help disentangle the contributions of local flexibility of the label and its neighboring nucleobases and global deformations of the RNA double helix to the experimental distance distributions. The study demonstrates that our simple but strategic spin labeling procedure can access detailed structural information on RNAs at atomic resolution over distances that match the size of macromolecular RNA complexes.

The emerging epitranscriptomics of long noncoding RNAs

The pervasive transcription of genomes into long noncoding RNAs has been amply demonstrated in recent years and garnered much attention. Similarly, emerging 'epitranscriptomics' research has shown that chemically modified nucleosides, thought to be largely the domain of tRNAs and other infrastructural RNAs, are far more widespread and can exert unexpected influence on RNA utilization. Both areas are characterized by the often-ephemeral nature of the subject matter in that few individual examples have been fully assessed for their molecular or cellular function, and effects might often be subtle and cumulative. Here we review available information at the intersection of these two exciting areas of biology, by focusing on four RNA modifications that have been mapped transcriptome-wide: 5-methylcytidine, N6-methyladenosine, pseudouridine as well as adenosine to inosine (A-to-I) editing, and their incidence and function in long noncoding RNAs. This article is part of a Special Issue entitled: Clues to long noncoding RNA taxonomy, edited by Dr. Tetsuro Hirose and Dr. Shinichi Nakagawa.

HNRNPA2B1 Is a Mediator of m(6)A-Dependent Nuclear RNA Processing Events

N(6)-methyladenosine (m(6)A) is the most abundant internal modification of messenger RNA. While the presence of m(6)A on transcripts can impact nuclear RNA fates, a reader of this mark that mediates processing of nuclear transcripts has not been identified. We find that the RNA-binding protein HNRNPA2B1 binds m(6)A-bearing RNAs in vivo and in vitro and its biochemical footprint matches the m(6)A consensus motif. HNRNPA2B1 directly binds a set of nuclear transcripts and elicits similar alternative splicing effects as the m(6)A writer METTL3. Moreover, HNRNPA2B1 binds to m(6)A marks in a subset of primary miRNA transcripts, interacts with the microRNA Microprocessor complex protein DGCR8, and promotes primary miRNA processing. Also, HNRNPA2B1 loss and METTL3 depletion cause similar processing defects for these pri-miRNA precursors. We propose HNRNPA2B1 to be a nuclear reader of the m(6)A mark and to mediate, in part, this mark's effects on primary microRNA processing and alternative splicing. PAPERCLIP.

Revisiting Caffeine Biosynthesis – Speculations about the Proximate Source of its Purine Ring

The prevailing hypothesis of caffeine biosynthesis starting from xanthosine was combined with Kremers’ speculation on NAD as a biochemical precursor of caffeine and trigonelline in coffee. This bold sketch together with a few free-spirited ideas may channel future caffeine biosynthesis studies into novel directions.