Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library

Mild and ultrafast GLORI enables absolute quantification of m6A methylome from low-input samples

Methods for absolute quantification of N6-methyladenosine (m6A) have emerged as powerful tools in epitranscriptomics. We previously reported GLORI, a chemical-assisted approach to achieve unbiased and precise m6A measurement. However, its lengthy reaction time and severe RNA degradation have limited its applicability, particularly for low-input samples. Here, we present two updated GLORI approaches that are ultrafast, mild and enable absolute m6A quantification from one to two orders of magnitude less than the RNA starting material: GLORI 2.0 is compatible with RNA from ~10,000 cells and enhances sensitivity for both transcriptome-wide and locus-specific m6A detection; GLORI 3.0 further utilizes a reverse transcription-silent carrier RNA to achieve m6A quantification from as low as 500-1,000 cells. Using limited RNA from mouse dorsal hippocampus, we reveal a high modification level in synapse-related gene sets. We envision that the updated GLORI methods will greatly expand the applicability of absolute quantification of m6A in biology.

N 6-methyladenosine modifications stabilize phosphate starvation response-related mRNAs in plant adaptation to nutrient-deficient stress

N6-methyladenosine (m6A), an abundant internal mRNA modification, is induced by various stress conditions and post-transcriptionally regulates gene expression. However, how m6A modifications help plants respond to nutrient-deficiency stress remains unclear. Here, we profile high-confidence m6A modifications in Arabidopsis transcriptome-wide under normal and inorganic orthophosphate (Pi)-deficient conditions (-P). High-confidence m6A modifications are identified using synthetic modification-free RNA libraries for systematic calibration. Pi starvation induces widespread m6A modifications, mediated by the Pi starvation response (PSR) master regulator PHOSPHATE STARVATION RESPONSE1 (PHR1) and its family members. Many Pi starvation-induced (PSI) m6A modifications occur on PSR-related mRNAs, including PHR1. In addition, PHR1 proteins interact with the m6A writers MRNA ADENOSINE METHYLASE (MTA) and METHYLTRANSFERASE B (MTB) in nuclei under -P conditions. m6A modifications facilitate systemic PSR signaling, as reflected by the reduced Pi content and PSR signaling in a knockdown artificial miRNA line targeting MTA, which shows a global decrease in m6A. Transcriptome-wide mRNA decay analysis reveals that PSI-m6A increases the stability of PSR-related mRNAs, but not through alternative polyadenylation site shifts. Analysis of transgenic plants with mutations in m6A loci demonstrates that m6A stabilizes PHR1 transcripts via a positive feedback loop. Our findings indicate that PSI-m6A modifications facilitate PSR signaling by enhancing the stability of certain mRNAs, shedding light on the role of m6A modifications in nutrient stress responses in plants.

Long-read RNA sequencing reveals allele-specific N 6-methyladenosine modifications

Long-read sequencing technology enables highly accurate detection of allele-specific RNA expression, providing insights into the effects of genetic variation on splicing and RNA abundance. Furthermore, the ability to directly sequence RNA enables the detection of RNA modifications in tandem with ascertaining the allelic origin of each molecule. Here, we leverage these advantages to determine allele-biased patterns of N 6-methyladenosine (m6A) modifications in native mRNA. We used human and mouse cells with known genetic variants to assign the allelic origin of each mRNA molecule combined with a supervised machine learning model to detect read-level m6A modification ratios. Our analyses reveal the importance of sequences adjacent to the DRACH motif in determining m6A deposition, in addition to allelic differences that directly alter the motif. Moreover, we discover allele-specific m6A modification events with no genetic variants in close proximity to the differentially modified nucleotide, demonstrating the unique advantage of using long-reads and surpassing the capabilities of antibody-based short-read approaches. This technological advance will further our understanding of the role of genetics in determining mRNA modifications.

5-Methylcytosine RNA modification and its roles in cancer and cancer chemotherapy resistance

Recent advancements in cancer therapies have improved clinical outcomes, yet therapeutic resistance remains a significant challenge because of its complex mechanisms. Among epigenetic factors, m5C RNA modification is emerging as a key player in cancer drug resistance, similar to the well-known m6A modification. m5C affects RNA metabolism processes, including splicing, export, translation, and stability, thereby influencing drug efficacy. This review highlights the critical roles of m5C in modulating resistance to chemotherapy, targeted therapy, radiotherapy, and immunotherapy. This review also discusses the functions of key regulators, including methyltransferases, demethylases, and m5C-binding proteins, as essential modulators of the m5C epigenetic landscape that contribute to its dynamic and complex regulatory network. Targeting these regulatory components offers a promising strategy to overcome resistance. We highlight the need for further research to elucidate the specific mechanisms by which m5C contributes to resistance and to develop precise m5C-targeted therapies, presenting m5C-focused strategies as potential novel anticancer treatments.

RNA modifications in the tumor microenvironment: insights into the cancer-immunity cycle and beyond

The chemical modification of biological molecules is a critical regulatory mechanism for controlling molecular functions. Although research has long focused on DNA and proteins, RNA modifications have recently attracted substantial interest with the advancement in detection technologies. In oncology, many studies have identified dysregulated RNA modifications including m6A, m1A, m5C, m7G, pseudouridylation and A to I editing, leading to disrupted downstream pathways. As the concept of the tumor microenvironment has gained prominence, studies have increasingly examined the role of RNA modifications in this context, focusing on interactions among cancer cells, immune cells, stromal cells, and other components. Here we review the RNA modifications in the tumor microenvironment through the perspective of the Cancer-Immunity Cycle. The extracellular RNA modifications including exosomes and influence of microbiome in RNA modifications are potential research questions. Additionally, RNA modifying enzymes including FTO, ALKBH5, METTL3, PUS7 are under investigation as potential biomarkers and targets for combination with immunotherapies. ADCs and mimetics of modified RNA could be potential novel drugs. This review discusses the regulatory roles of RNA modifications within the tumor microenvironment.

Decoding m6Am by simultaneous transcription-start mapping and methylation quantification

N 6,2'-O-dimethyladenosine (m6Am) is a modified nucleotide located at the first transcribed position in mRNA and snRNA that is essential for diverse physiological processes. m6Am mapping methods assume each gene uses a single start nucleotide. However, gene transcription usually involves multiple start sites, generating numerous 5' isoforms. Thus, gene-level annotations cannot capture the diversity of m6Am modification in the transcriptome. Here, we describe CROWN-seq, which simultaneously identifies transcription-start nucleotides and quantifies m6Am stoichiometry for each 5' isoform that initiates with adenosine. Using CROWN-seq, we map the m6Am landscape in nine human cell lines. Our findings reveal that m6Am is nearly always a high stoichiometry modification, with only a small subset of cellular mRNAs showing lower m6Am stoichiometry. We find that m6Am is associated with increased transcript expression and provide evidence that m6Am may be linked to transcription initiation associated with specific promoter sequences and initiation mechanisms. These data suggest a potential new function for m6Am in influencing transcription.

Protocol for profiling RNA m5C methylation at base resolution using m5C-TAC-seq

RNA 5-methylcytosine (m5C) is a widespread modification and plays a crucial role in gene expression regulation. Here, we present a protocol for transcriptome-wide m5C methylome profiling at base resolution using bisulfite-free m5C detection strategy enabled by ten-eleven translocation (TET)-assisted chemical labeling sequencing (m5C-TAC-seq). We detail steps for TET-assisted chemical labeling, library construction, and data analysis. m5C-TAC-seq enables accurate and robust m5C detection in various RNA species. For complete details on the use and execution of this protocol, please refer to Lu et al.1.

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

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

De novo basecalling of RNA modifications at single molecule and nucleotide resolution

RNA modifications influence RNA function and fate, but detecting them in individual molecules remains challenging for most modifications. Here we present a novel methodology to generate training sets and build modification-aware basecalling models. Using this approach, we develop the m6ABasecaller, a basecalling model that predicts m6A modifications from raw nanopore signals. We validate its accuracy in vitro and in vivo, revealing stable m6A modification stoichiometry across isoforms, m6A co-occurrence within RNA molecules, and m6A-dependent effects on poly(A) tails. Finally, we demonstrate that our method generalizes to other RNA and DNA modifications, paving the path towards future efforts detecting other modifications.

Decoding m6Am by simultaneous transcription-start mapping and methylation quantification

N 6,2'-O-dimethyladenosine (m6Am) is a modified nucleotide located at the first transcribed position in mRNA and snRNA that is essential for diverse physiological processes. m6Am mapping methods assume each gene uses a single start nucleotide. However, gene transcription usually involves multiple start sites, generating numerous 5' isoforms. Thus, gene levels annotations cannot capture the diversity of m6Am modification in the transcriptome. Here we describe CROWN-seq, which simultaneously identifies transcription-start nucleotides and quantifies m6Am stoichiometry for each 5' isoform that initiates with adenosine. Using CROWN-seq, we map the m6Am landscape in nine human cell lines. Our findings reveal that m6Am is nearly always a high stoichiometry modification, with only a small subset of cellular mRNAs showing lower m6Am stoichiometry. We find that m6Am is associated with increased transcript expression and provide evidence that m6Am may be linked to transcription initiation associated with specific promoter sequences and initiation mechanisms. These data suggest a potential new function for m6Am in influencing transcription.

A Comparative Evaluation of Computational Models for RNA modification detection using Nanopore sequencing with RNA004 Chemistry

Direct RNA sequencing from Oxford Nanopore Technologies (ONT) has become a valuable method for studying RNA modifications such as N6-methyladenosine (m6A), pseudouridine (ψ), and 5-methylcytosine (m5C). Recent advancements in the RNA004 chemistry substantially reduce sequencing errors compared to previous chemistries (e.g., RNA002), thereby promising enhanced accuracy for epitranscriptomic analysis. In this study, we benchmark the performance of two state-of-the-art RNA modification detection models capable of handling RNA004 data - ONT's Dorado and m6Anet - using two wild-type (WT) cell lines, HEK293T and HeLa, with respective ground truths from GLORI and eTAM-seq, and their paired in vitro transcribed (IVT) RNA as negative controls. We found that under default settings and considering sites with ≥10% modification ratio and ≥10X coverage, Dorado has higher recall (~0.92) than m6Anet (~0.51) for m6A detection. Among the overlapping methylated sites between ground truth and computational predictions, there are high correlations of site-specific m6A modification stoichiometry, with correlation coefficient of ~0.89 for Dorado-truth comparison and ~0.72 for m6Anet-truth comparison. However, combined assessment of WT and IVT datasets show that while the per-site false positive rate (FPR) can be lower (~8% for Dorado and ~33% for m6Anet), both computational tools can have high per-site false discovery rate (FDR) of m6A (~40% for Dorado and ~80% for m6Anet) due to the low prevalence of m6A in transcriptome, with a similar trend observed for pseudouridine (~95% FDR for Dorado). Additional motif analysis reveals that both Dorado and m6Anet exhibit high heterogeneity of false positive calls across sequence contexts, suggesting that sequence contexts help determine accuracy of specific modification calls. There is also a substantial overlap of false positive calls between the two IVT samples, suggesting a post-filtering strategy to improve modification calling by compiling a set of low-confidence sites with a probabilistic model from several IVT samples across diverse cells/tissues. Our analysis highlights key strengths and limitations of the current generation of m6A detection algorithms and offers insights into optimizing thresholds and interpretability. The IVT datasets generated by the RNA004 chemistry provides a publicly available benchmark resource for further development and refinement of computational methods.

Advanced reactivity-based sequencing methods for mRNA epitranscriptome profiling

Currently, over 170 chemical modifications identified in RNA introduce an additional regulatory attribute to gene expression, known as the epitranscriptome. The development of detection methods to pinpoint the location and quantify these dynamic and reversible modifications has significantly expanded our understanding of their roles. This review goes deep into the latest progress in enzyme- and chemical-assisted sequencing methods, highlighting the opportunities presented by these reactivity-based techniques for detailed characterization of RNA modifications. Our survey provides a deeper understanding of the function and biological roles of RNA modification.

Charting the epitranscriptomic landscape across RNA biotypes using native RNA nanopore sequencing

RNA modifications are conserved chemical features found in all domains of life and across diverse RNA biotypes, shaping gene expression profiles and enabling rapid responses to environmental changes. Their broad chemical diversity and dynamic nature pose significant challenges for studying them comprehensively. These limitations can now be addressed through direct RNA nanopore sequencing (DRS), which allows simultaneous identification of diverse RNA modification types at single-molecule and single-nucleotide resolution. Here, we review recent efforts pioneering the use of DRS to better understand the epitranscriptomic landscape. We highlight how DRS can be applied to investigate different RNA biotypes, emphasizing the use of specialized library preparation protocols and downstream bioinformatic workflows to detect both natural and synthetic RNA modifications. Finally, we provide a perspective on the future role of DRS in epitranscriptomic research, highlighting remaining challenges and emerging opportunities from improved sequencing yields and accuracy enabled by the latest DRS chemistry.

Most m5C Modifications in Mammalian mRNAs are Nonadaptive

5-Methylation (m5C) on mRNA molecules is a prevalent internal posttranscriptional modification in eukaryotes. Although m5C modification has been reported to regulate some biological processes, whether most mRNA m5C modifications are functional is unknown. To address this question, we analyzed the genome-wide evolutionary characteristics of m5C modifications in protein-coding genes of humans and mice. Our analysis of RNA sequencing data from 13 tissues of both species revealed that (i) the occurrence of m5C modification is exceedingly low, (ii) the fraction of m5Cs decreases with the amount of Cs across genes or tissues, (iii) m5C modifications are mostly unshared between species, and (iv) m5C sites and motifs do not exhibit greater evolutionary conservation. Additionally, we estimate that a large fraction of the observed mRNA m5C modifications may be deleterious. Together, these observations suggest that most m5C modifications in mammalian mRNAs are nonadaptive, which has important implications for understanding the biological significance of m5C and other posttranscriptional modifications.

Mapping epigenetic modifications by sequencing technologies

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

AI techniques have facilitated the understanding of epitranscriptome distribution

N6-methyladenosine (m6A), the most prevalent internal mRNA modification in higher eukaryotes, plays diverse roles in cellular regulation. By incorporating both sequence- and genome-derived features, Fan et al.1 designed a novel Transformer-BiGRU framework that achieves superior performance in computational m6A identification, thus demonstrating the potential of AI in genomic studies.

NAT10-mediated mRNA N4-acetylcytidine reprograms serine metabolism to drive leukaemogenesis and stemness in acute myeloid leukaemia

RNA modification has emerged as an important epigenetic mechanism that controls abnormal metabolism and growth in acute myeloid leukaemia (AML). However, the roles of RNA N4-acetylcytidine (ac4C) modification in AML remain elusive. Here, we report that ac4C and its catalytic enzyme NAT10 drive leukaemogenesis and sustain self-renewal of leukaemic stem cells/leukaemia-initiating cells through reprogramming serine metabolism. Mechanistically, NAT10 facilitates exogenous serine uptake and de novo biosynthesis through ac4C-mediated translation enhancement of the serine transporter SLC1A4 and the transcription regulators HOXA9 and MENIN that activate transcription of serine synthesis pathway genes. We further characterize fludarabine as an inhibitor of NAT10 and demonstrate that pharmacological inhibition of NAT10 targets serine metabolic vulnerability, triggering substantial anti-leukaemia effects both in vitro and in vivo. Collectively, our study demonstrates the functional importance of ac4C and NAT10 in metabolism control and leukaemogenesis, providing insights into the potential of targeting NAT10 for AML therapy.

Detecting m6A RNA modification from nanopore sequencing using a semisupervised learning framework

Direct nanopore-based RNA sequencing can be used to detect posttranscriptional base modifications, such as N6-methyladenosine (m6A) methylation, based on the electric current signals produced by the distinct chemical structures of modified bases. A key challenge is the scarcity of adequate training data with known methylation modifications. We present Xron, a hybrid encoder-decoder framework that delivers a direct methylation-distinguishing basecaller by training on synthetic RNA data and immunoprecipitation (IP)-based experimental data in two steps. First, we generate data with more diverse modification combinations through in silico cross-linking. Second, we use this data set to train an end-to-end neural network basecaller followed by fine-tuning on IP-based experimental data with label smoothing. The trained neural network basecaller outperforms existing methylation detection methods on both read-level and site-level prediction scores. Xron is a standalone, end-to-end m6A-distinguishing basecaller capable of detecting methylated bases directly from raw sequencing signals, enabling de novo methylome assembly.

Absolute quantitative and base-resolution sequencing reveals comprehensive landscape of pseudouridine across the human transcriptome

Pseudouridine (Ψ) is one of the most abundant modifications in cellular RNA. However, its function remains elusive, mainly due to the lack of highly sensitive and accurate detection methods. Here, we introduced 2-bromoacrylamide-assisted cyclization sequencing (BACS), which enables Ψ-to-C transitions, for quantitative profiling of Ψ at single-base resolution. BACS allowed the precise identification of Ψ positions, especially in densely modified Ψ regions and consecutive uridine sequences. BACS detected all known Ψ sites in human rRNA and spliceosomal small nuclear RNAs and generated the quantitative Ψ map of human small nucleolar RNA and tRNA. Furthermore, BACS simultaneously detected adenosine-to-inosine editing sites and N1-methyladenosine. Depletion of pseudouridine synthases TRUB1, PUS7 and PUS1 elucidated their targets and sequence motifs. We further identified a highly abundant Ψ114 site in Epstein-Barr virus-encoded small RNA EBER2. Surprisingly, applying BACS to a panel of RNA viruses demonstrated the absence of Ψ in their viral transcripts or genomes, shedding light on differences in pseudouridylation across virus families.

Microbiome-induced reprogramming in post-transcriptional landscape using nanopore direct RNA sequencing

It has been widely recognized that the microbiota has the capacity to shape host gene expression and physiological functions. However, there remains a paucity of comprehensive study revealing the host transcriptional landscape regulated by the microbiota. Here, we comprehensively examined mRNA landscapes in mouse tissues (brain and cecum) from specific-pathogen-free and germ-free mice using nanopore direct RNA sequencing. Our results show that the microbiome has global influence on a host's RNA modifications (m6A, m5C, Ψ), isoform generation, poly(A) tail length, and transcript abundance in both brain and cecum tissues. Moreover, the microbiome exerts tissue-specific effects on various post-transcriptional regulatory processes. In addition, the microbiome impacts the coordination of multiple RNA modifications in host brain and cecum tissues. In conclusion, we establish the relationship between microbial regulation and gene expression. Our results help the understanding of the mechanisms by which the microbiome reprograms host gene expression.

Ultrafast bisulfite sequencing detection of 5-methylcytosine in DNA and RNA

Bisulfite sequencing (BS-seq) to detect 5-methylcytosine (5mC) is limited by lengthy reaction times, severe DNA damage, overestimation of 5mC level and incomplete C-to-U conversion of certain DNA sequences. We present ultrafast BS-seq (UBS-seq), which uses highly concentrated bisulfite reagents and high reaction temperatures to accelerate the bisulfite reaction by ~13-fold, resulting in reduced DNA damage and lower background noise. UBS-seq allows library construction from small amounts of purified genomic DNA, such as from cell-free DNA or directly from 1 to 100 mouse embryonic stem cells, with less overestimation of 5mC level and higher genome coverage than conventional BS-seq. Additionally, UBS-seq quantitatively maps RNA 5-methylcytosine (m5C) from low inputs of mRNA and allows the detection of m5C stoichiometry in highly structured RNA sequences. Our UBS-seq results identify NSUN2 as the major 'writer' protein responsible for the deposition of ~90% of m5C sites in HeLa mRNA and reveal enriched m5C sites in 5'-regions of mammalian mRNA, which may have functional roles in mRNA translation regulation.

Comprehensive Review and Assessment of Computational Methods for Prediction of N6-Methyladenosine Sites

N6-methyladenosine (m6A) plays a crucial regulatory role in the control of cellular functions and gene expression. Recent advances in sequencing techniques for transcriptome-wide m6A mapping have accelerated the accumulation of m6A site information at a single-nucleotide level, providing more high-confidence training data to develop computational approaches for m6A site prediction. However, it is still a major challenge to precisely predict m6A sites using in silico approaches. To advance the computational support for m6A site identification, here, we curated 13 up-to-date benchmark datasets from nine different species (i.e., H. sapiens, M. musculus, Rat, S. cerevisiae, Zebrafish, A. thaliana, Pig, Rhesus, and Chimpanzee). This will assist the research community in conducting an unbiased evaluation of alternative approaches and support future research on m6A modification. We revisited 52 computational approaches published since 2015 for m6A site identification, including 30 traditional machine learning-based, 14 deep learning-based, and 8 ensemble learning-based methods. We comprehensively reviewed these computational approaches in terms of their training datasets, calculated features, computational methodologies, performance evaluation strategy, and webserver/software usability. Using these benchmark datasets, we benchmarked nine predictors with available online websites or stand-alone software and assessed their prediction performance. We found that deep learning and traditional machine learning approaches generally outperformed scoring function-based approaches. In summary, the curated benchmark dataset repository and the systematic assessment in this study serve to inform the design and implementation of state-of-the-art computational approaches for m6A identification and facilitate more rigorous comparisons of new methods in the future.

Long-read RNA sequencing reveals allele-specific N6-methyladenosine modifications

Long-read sequencing technology enables highly accurate detection of allele-specific RNA expression, providing insights into the effects of genetic variation on splicing and RNA abundance. Furthermore, the ability to directly sequence RNA promises the detection of RNA modifications in tandem with ascertaining the allelic origin of each molecule. Here, we leverage these advantages to determine allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNA. We utilized human and mouse cells with known genetic variants to assign allelic origin of each mRNA molecule combined with a supervised machine learning model to detect read-level m6A modification ratios. Our analyses revealed the importance of sequences adjacent to the DRACH-motif in determining m6A deposition, in addition to allelic differences that directly alter the motif. Moreover, we discovered allele-specific m6A modification (ASM) events with no genetic variants in close proximity to the differentially modified nucleotide, demonstrating the unique advantage of using long reads and surpassing the capabilities of antibody-based short-read approaches. This technological advancement promises to advance our understanding of the role of genetics in determining mRNA modifications.

RNA modifications in physiology and pathology: Progressing towards application in clinical settings

The potential to modify individual nucleotides through chemical means in order to impact the electrostatic charge, hydrophobic properties, and base pairing of RNA molecules is harnessed in the medical application of stable synthetic RNAs like mRNA vaccines and synthetic small RNA molecules. These modifications are used to either increase or decrease the production of therapeutic proteins. Additionally, naturally occurring biochemical alterations of nucleotides play a role in regulating RNA metabolism and function, thereby modulating essential cellular processes. Research elucidating the mechanisms through which RNA modifications govern fundamental cellular functions in multicellular organisms has enhanced our comprehension of how irregular RNA modification profiles can lead to human diseases. Collectively, these fundamental scientific findings have unveiled the molecular and cellular functions of RNA modifications, offering new opportunities for therapeutic intervention and paving the way for a variety of innovative clinical strategies.

Analysis of bacterial transcriptome and epitranscriptome using nanopore direct RNA sequencing

Bacterial gene expression is a complex process involving extensive regulatory mechanisms. Along with growing interests in this field, Nanopore Direct RNA Sequencing (DRS) provides a promising platform for rapid and comprehensive characterization of bacterial RNA biology. However, the DRS of bacterial RNA is currently deficient in the yield of mRNA-mapping reads and has yet to be exploited for transcriptome-wide RNA modification mapping. Here, we showed that pre-processing of bacterial total RNA (size selection followed by ribosomal RNA depletion and polyadenylation) guaranteed high throughputs of sequencing data and considerably increased the amount of mRNA reads. This way, complex transcriptome architectures were reconstructed for Escherichia coli and Staphylococcus aureus and extended the boundaries of 225 known E. coli operons and 89 defined S. aureus operons. Utilizing unmodified in vitro-transcribed (IVT) RNA libraries as a negative control, several Nanopore-based computational tools globally detected putative modification sites in the E. coli and S. aureus transcriptomes. Combined with Next-Generation Sequencing-based N6-methyladenosine (m6A) detection methods, 75 high-confidence m6A candidates were identified in the E. coli protein-coding transcripts, while none were detected in S. aureus. Altogether, we demonstrated the potential of Nanopore DRS in systematic and convenient transcriptome and epitranscriptome analysis.

Base-resolution m5C profiling across the mammalian transcriptome by bisulfite-free enzyme-assisted chemical labeling approach

5-methylcytosine (m5C) is a prevalent RNA modification crucial for gene expression regulation. However, accurate and sensitive m5C sites identification remains challenging due to severe RNA degradation and reduced sequence complexity during bisulfite sequencing (BS-seq). Here, we report m5C-TAC-seq, a bisulfite-free approach combining TET-assisted m5C-to-f5C oxidation with selective chemical labeling, therefore enabling direct base-resolution m5C detection through pre-enrichment and C-to-T transitions at m5C sites. With m5C-TAC-seq, we comprehensively profiled the m5C methylomes in human and mouse cells, identifying a substantially larger number of confident m5C sites. Through perturbing potential m5C methyltransferases, we deciphered the responsible enzymes for most m5C sites, including the characterization of NSUN5's involvement in mRNA m5C deposition. Additionally, we characterized m5C dynamics during mESC differentiation. Notably, the mild reaction conditions and preservation of nucleotide composition in m5C-TAC-seq allow m5C detection in chromatin-associated RNAs. The accurate and robust m5C-TAC-seq will advance research into m5C methylation functional investigation.

Current progress in strategies to profile transcriptomic m6A modifications

Various methods have been developed so far for detecting N 6-methyladenosine (m6A). The total m6A level or the m6A status at individual positions on mRNA can be detected and quantified through some sequencing-independent biochemical methods, such as LC/MS, SCARLET, SELECT, and m6A-ELISA. However, the m6A-detection techniques relying on high-throughput sequencing have more effectively advanced the understanding about biological significance of m6A-containing mRNA and m6A pathway at a transcriptomic level over the past decade. Various SGS-based (Second Generation Sequencing-based) methods with different detection principles have been widely employed for this purpose. These principles include m6A-enrichment using antibodies, discrimination of m6A from unmodified A-base by nucleases, a fusion protein strategy relying on RNA-editing enzymes, and marking m6A with chemical/biochemical reactions. Recently, TGS-based (Third Generation Sequencing-based) methods have brought a new trend by direct m6A-detection. This review first gives a brief introduction of current knowledge about m6A biogenesis and function, and then comprehensively describes m6A-profiling strategies including their principles, procedures, and features. This will guide users to pick appropriate methods according to research goals, give insights for developing novel techniques in varying areas, and continue to expand our boundary of knowledge on m6A.

Accurate identification of 8-oxoguanine in RNA with single-nucleotide resolution using ligase-dependent qPCR

8-oxoguanine (o8G), a prevalent oxidative modification in RNA induced by reactive oxygen species (ROS), plays a pivotal role in regulating RNA functions. Accurate detection and quantification of o8G modifications is critical to understanding their biological significance and potential as disease biomarkers, but effective detection methods remain limited. Here, we have developed a highly specific T3 DNA ligase-dependent qPCR assay that exploits the enzyme's ability to discriminate o8G from guanine (G) with single-nucleotide resolution. This method can detect o8G in RNA at levels as low as 500 fM, with an up to 18-fold higher selectivity for discriminating o8G from G. By simulating oxidative stress conditions in SH-SY5Y and HS683 cell lines treated with rotenone, we successfully identified site-specific o8G modifications in key miRNAs associated with neuroprotective responses, including miR-124, let-7a and miR-29a. The developed assay holds significant promise for the practical identification of o8G, facilitating its potential for detailed studies of o8G dynamics in various biological contexts and diseases.

Multicellular, IVT-derived, unmodified human transcriptome for nanopore-direct RNA analysis

Nanopore direct RNA sequencing (DRS) enables measurements of RNA modifications. Modification-free transcripts are a practical and targeted control for DRS, providing a baseline measurement for canonical nucleotides within a matched and biologically-derived sequence context. However, these controls can be challenging to generate and carry nanopore-specific nuances that can impact analyses. We produced DRS datasets using modification-free transcripts from in vitro transcription of cDNA from six immortalized human cell lines. We characterized variation across cell lines and demonstrated how these may be interpreted. These data will serve as a versatile control and resource to the community for RNA modification analyses of human transcripts.

RNA m6A detection using raw current signals and basecalling errors from Nanopore direct RNA sequencing reads

MOTIVATION

Nanopore direct RNA sequencing (DRS) enables the detection of RNA N6-methyladenosine (m6A) without extra laboratory techniques. A number of supervised or comparative approaches have been developed to identify m6A from Nanopore DRS reads. However, existing methods typically utilize either statistical features of the current signals or basecalling-error features, ignoring the richer information of the raw signals of DRS reads.

RESULTS

Here, we propose RedNano, a deep-learning method designed to detect m6A from Nanopore DRS reads by utilizing both raw signals and basecalling errors. RedNano processes the raw-signal feature and basecalling-error feature through residual networks. We validated the effectiveness of RedNano using synthesized, Arabidopsis, and human DRS data. The results demonstrate that RedNano surpasses existing methods by achieving higher area under the ROC curve (AUC) and area under the precision-recall curve (AUPRs) in all three datasets. Furthermore, RedNano performs better in cross-species validation, demonstrating its robustness. Additionally, when detecting m6A from an independent dataset of Populus trichocarpa, RedNano achieves the highest AUC and AUPR, which are 3.8%-9.9% and 5.5%-13.8% higher than other methods, respectively.

AVAILABILITY AND IMPLEMENTATION

The source code of RedNano is freely available at https://github.com/Derryxu/RedNano.

Multicellular, IVT-derived, unmodified human transcriptome for nanopore-direct RNA analysis

Nanopore direct RNA sequencing (DRS) enables measurements of RNA modifications. Modification-free transcripts are a practical and targeted control for DRS, providing a baseline measurement for canonical nucleotides within a matched and biologically derived sequence context. However, these controls can be challenging to generate and carry nanopore-specific nuances that can impact analysis. We produced DRS datasets using modification-free transcripts from in vitro transcription (IVT) of cDNA from six immortalized human cell lines. We characterized variation across cell lines and demonstrated how these may be interpreted. These data will serve as a versatile control and resource to the community for RNA modification analysis of human transcripts.

m6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq

We present m6ACali, a novel machine-learning framework aimed at enhancing the accuracy of N6-methyladenosine (m6A) epitranscriptome profiling by reducing the impact of non-specific antibody enrichment in MeRIP-Seq. The calibration model serves as a genomic feature-based classifier that refines the identification of m6A sites, distinguishing those genuinely present from those that can be detected in in-vitro transcribed (IVT) control experiments. We find that m6ACali effectively identifies non-specific binding peaks reported by exomePeak2 and MACS2 in novel MeRIP-Seq datasets without the need for paired IVT controls. The model interpretation revealed that off-target antibody binding sites commonly occur at short exons and short mRNAs, originating from high read coverage regions that share the motif sequence with true m6A sites. We also reveal that the ML strategy can efficiently adjust differentially methylated peaks and other antibody-dependent, base-resolution m6A detection techniques. As a result, m6ACali offers a promising method for the universal enhancement of m6A profiles generated by MeRIP-Seq experiments, elevating the benchmark for omics-level m6A data integration.

Elevated WTAP promotes hyperinflammation by increasing m6A modification in inflammatory disease models

Emerging evidence has linked the dysregulation of N6-methyladenosine (m6A) modification to inflammation and inflammatory diseases, but the underlying mechanism still needs investigation. Here, we found that high levels of m6A modification in a variety of hyperinflammatory states are p65-dependent because Wilms tumor 1-associated protein (WTAP), a key component of the "writer" complex, is transcriptionally regulated by p65, and its overexpression can lead to increased levels of m6A modification. Mechanistically, upregulated WTAP is more prone to phase separation to facilitate the aggregation of the writer complex to nuclear speckles and the deposition of m6A marks on transcriptionally active inflammatory transcripts, thereby accelerating the proinflammatory response. Further, a myeloid deficiency in WTAP attenuates the severity of LPS-induced sepsis and DSS-induced IBD. Thus, the proinflammatory effect of WTAP is a general risk-increasing mechanism, and interrupting the assembly of the m6A writer complex to reduce the global m6A levels by targeting the phase separation of WTAP may be a potential and promising therapeutic strategy for alleviating hyperinflammation.

Challenges to mapping and defining m6A function in viral RNA

Viral RNA molecules contain multiple layers of regulatory information. This includes features beyond the primary sequence, such as RNA structures and RNA modifications, including N6-methyladenosine (m6A). Many recent studies have identified the presence and location of m6A in viral RNA and have found diverse regulatory roles for this modification during viral infection. However, to date, viral m6A mapping strategies have limitations that prevent a complete understanding of the function of m6A on individual viral RNA molecules. While m6A sites have been profiled on bulk RNA from many viruses, the resulting m6A maps of viral RNAs described to date present a composite picture of m6A across viral RNA molecules in the infected cell. Thus, for most viruses, it is unknown if unique viral m6A profiles exist throughout infection, nor if they regulate specific viral life cycle stages. Here, we describe several challenges to defining the function of m6A in viral RNA molecules and provide a framework for future studies to help in the understanding of how m6A regulates viral infection.

GLORI for absolute quantification of transcriptome-wide m6A at single-base resolution

N6-methyladenosine (m6A) is the most abundant posttranscriptional chemical modification in mRNA, involved in regulating various physiological and pathological processes throughout mRNA metabolism. Recently, we developed GLORI, a sequencing method that enables the production of a globally absolute-quantitative m6A map at single-base resolution. Our technique utilizes the glyoxal- and nitrite-based chemical reaction, which selectively deaminates unmethylated adenosines while leaving m6A intact. The RNA library can then be prepared using a modified library construction protocol from enhanced UV crosslinking and immunoprecipitation (eCLIP) or commercial kits. Here we provide a detailed protocol for proper RNA sample handling and provide further guidelines for the use of a tailored bioinformatics pipeline (GLORI-tools) for subsequent data analysis. Compared with current methods, this new method is both exceptionally sensitive and robust, capable of identifying ~80,000 m6A sites with 50 Gb sequencing data in mammalian cells. It also provides a quantitative readout for m6A sites at single-base resolution. We hope the technique will provide a precise and unbiased tool for investigating m6A biology across various fields. Basic expertise in molecular biology and knowledge of bioinformatics are required for the protocol. The entire procedure can be completed within a week, with the library construction process taking ~4 d.

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

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

An integrative platform for detection of RNA 2'-O-methylation reveals its broad distribution on mRNA

Ribose 2'-O-methylation is involved in critical biological processes, but its biological functions and significance in mRNAs remain underexplored. We have developed NJU-seq, a sensitive method for unbiased 2'-O-methylation (Nm) profiling, and Nm-VAQ, a site-specific quantification tool. Using these tools in tandem, we identified thousands of Nm sites on mRNAs of human and mouse cell lines, of which 68 of 84 selected sites were further validated to be more than 1% 2'-O-methylated. Unlike rRNA, most mRNA Nm sites were from 1% to 30% methylated. In addition, mRNA Nm was dynamic, changing according to the circumstance. Furthermore, we show that fibrillarin is involved as a methyltransferase. By mimicking the detected Nm sites and the context sequence, the RNA fragments could be 2'-O-methylated and demonstrated higher stability but lower translation efficiency. Last, profiling of Nm sites in lung surgery samples revealed common signatures of lung cancer pathogenesis, providing potential new diagnostic markers.

N6-methyladenosine modification is not a general trait of viral RNA genomes

Despite the nuclear localization of the m6A machinery, the genomes of multiple exclusively-cytoplasmic RNA viruses, such as chikungunya (CHIKV) and dengue (DENV), are reported to be extensively m6A-modified. However, these findings are mostly based on m6A-Seq, an antibody-dependent technique with a high rate of false positives. Here, we address the presence of m6A in CHIKV and DENV RNAs. For this, we combine m6A-Seq and the antibody-independent SELECT and nanopore direct RNA sequencing techniques with functional, molecular, and mutagenesis studies. Following this comprehensive analysis, we find no evidence of m6A modification in CHIKV or DENV transcripts. Furthermore, depletion of key components of the host m6A machinery does not affect CHIKV or DENV infection. Moreover, CHIKV or DENV infection has no effect on the m6A machinery's localization. Our results challenge the prevailing notion that m6A modification is a general feature of cytoplasmic RNA viruses and underscore the importance of validating RNA modifications with orthogonal approaches.

Detecting m6A RNA modification from nanopore sequencing using a semi-supervised learning framework

Direct nanopore-based RNA sequencing can be used to detect post-transcriptional base modifications, such as m6A methylation, based on the electric current signals produced by the distinct chemical structures of modified bases. A key challenge is the scarcity of adequate training data with known methylation modifications. We present Xron, a hybrid encoder-decoder framework that delivers a direct methylation-distinguishing basecaller by training on synthetic RNA data and immunoprecipitation-based experimental data in two steps. First, we generate data with more diverse modification combinations through in silico cross-linking. Second, we use this dataset to train an end-to-end neural network basecaller followed by fine-tuning on immunoprecipitation-based experimental data with label-smoothing. The trained neural network basecaller outperforms existing methylation detection methods on both read-level and site-level prediction scores. Xron is a standalone, end-to-end m6A-distinguishing basecaller capable of detecting methylated bases directly from raw sequencing signals, enabling de novo methylome assembly.

Methylation-Powered Assembly of a Single Quantum Dot-Based FRET Nanosensor for Antibody-Free and Enzyme-Free Monitoring of Locus-Specific N6-Methyladenosine in Clinical Tissues

N6-Methyladenosine (m6A) is the most pervasive and evolutionarily conserved epitranscriptomic modification in long noncoding RNA (lncRNA), and its dysregulation may induce aberrant transcription and translation programs. Herein, we demonstrate the methylation-powered assembly of a single quantum dot (QD)-based fluorescence resonance energy transfer (FRET) nanosensor for antibody- and enzyme-free monitoring of locus-specific m6A in clinical tissues. The m6A-sensitive DNAzyme VMC10 is employed to identify a specific m6A site in lncRNA, and it catalyzes the hydrolytic cleavage of unmethylated lncRNA. The cleaved lncRNA fails to trigger the subsequent catalytic hairpin assembly (CHA) reaction due to the energy barrier. In contrast, when m6A-lncRNA is present, the methyl group in m6A protects lncRNA from VMC10-mediated cleavage. With the aid of an assistant probe, the retained intact m6A-lncRNA is released from the VMC10/lncRNA complex and subsequently triggers the CHA reaction, generating abundant AF647/biotin dual-labeled duplexes. The assembly of AF647/biotin dual-labeled duplexes onto 605QD results in efficient FRET between 605QD and AF647. The FRET signal can be simply quantified by single-molecule detection. Notably, this assay can be implemented in an antibody-free and enzyme-free manner. This nanosensor can sensitively quantify target m6A with a detection limit of 0.47 fM, and it can discriminate as low as a 0.001% m6A level from excess coexisting counterparts. Importantly, this nanosensor can monitor the cellular m6A level with single-cell sensitivity and profile target m6A expression in breast cancer and healthy para-cancerous tissues, providing a powerful tool for studying the physiological and pathological functions of m6A.

Identification of Bona Fide RNA Editing Sites: History, Challenges, and Opportunities

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by the adenosine deaminase acting on the RNA (ADAR) family of enzymes of which there are three members (ADAR1, ADAR2, and ADAR3), is a major gene regulatory mechanism that diversifies the transcriptome. It is widespread in many metazoans, including humans. As inosine is interpreted by cellular machineries mainly as guanosine, A-to-I editing effectively gives A-to-G nucleotide changes. Depending on its location, an editing event can generate new protein isoforms or influence other RNA processing pathways. Researchers have found that ADAR-mediated editing performs diverse functions. For example, it enables living organisms such as cephalopods to adapt rapidly to fluctuating environmental conditions such as water temperature. In development, the loss of ADAR1 is embryonically lethal partly because endogenous double-stranded RNAs (dsRNAs) are no longer marked by inosines, which signal "self", and thus cause the melanoma differentiation-associated protein 5 (MDA5) sensor to trigger a deleterious interferon response. Hence, ADAR1 plays a key role in preventing aberrant activation of the innate immune system. Furthermore, ADAR enzymes have been implicated in myriad human diseases. Intriguingly, some cancer cells are known to exploit ADAR1 activity to dodge immune responses. However, the exact identities of immunogenic RNAs in different biological contexts have remained elusive. Consequently, there is tremendous interest in identifying inosine-containing RNAs in the cell.The identification of A-to-I RNA editing sites is dependent on the sequencing of nucleic acids. Technological and algorithmic advancements over the past decades have revolutionized the way editing events are detected. At the beginning, the discovery of editing sites relies on Sanger sequencing, a first-generation technology. Both RNA, which is reverse transcribed into complementary DNA (cDNA), and genomic DNA (gDNA) from the same source are analyzed. After sequence alignment, one would require an adenosine to be present in the genome but a guanosine to be detected in the RNA sample for a position to be declared as an editing site. However, an issue with Sanger sequencing is its low throughput. Subsequently, Illumina sequencing, a second-generation technology, was invented. By permitting the simultaneous interrogation of millions of molecules, it enables many editing sites to be identified rapidly. However, a key challenge is that the Illumina platform produces short sequencing reads that can be difficult to map accurately. To tackle the challenge, we and others developed computational workflows with a series of filters to discard sites that are likely to be false positives. When Illumina sequencing data sets are properly analyzed, A-to-G variants should emerge as the most dominant mismatch type. Moreover, the quantitative nature of the data allows us to build a comprehensive atlas of editing-level measurements across different biological contexts, providing deep insights into the spatiotemporal dynamics of RNA editing. However, difficulties remain in identifying true A-to-I editing sites in short protein-coding exons or in organisms and diseases where DNA mutations and genomic polymorphisms are prevalent and mostly unknown. Nanopore sequencing, a third-generation technology, promises to address the difficulties, as it allows native RNAs to be sequenced without conversion to cDNA, preserving base modifications that can be directly detected through machine learning. We recently demonstrated that nanopore sequencing could be used to identify A-to-I editing sites in native RNA directly. Although further work is needed to enhance the detection accuracy in single molecules from fewer cells, the nanopore technology holds the potential to revolutionize epitranscriptomic studies.

Quantitative profiling of pseudouridylation landscape in the human transcriptome

Pseudouridine (Ψ) is an abundant post-transcriptional RNA modification in ncRNA and mRNA. However, stoichiometric measurement of individual Ψ sites in human transcriptome remains unaddressed. Here we develop 'PRAISE', via selective chemical labeling of Ψ by bisulfite to induce nucleotide deletion signature during reverse transcription, to realize quantitative assessment of the Ψ landscape in the human transcriptome. Unlike traditional bisulfite treatment, our approach is based on quaternary base mapping and revealed an ~10% median modification level for 2,209 confident Ψ sites in HEK293T cells. By perturbing pseudouridine synthases, we obtained differential mRNA targets of PUS1, PUS7, TRUB1 and DKC1, with TRUB1 targets showing the highest modification stoichiometry. In addition, we quantified known and new Ψ sites in mitochondrial mRNA catalyzed by PUS1. Collectively, we provide a sensitive and convenient method to measure transcriptome-wide Ψ; we envision this quantitative approach would facilitate emerging efforts to elucidate the function and mechanism of mRNA pseudouridylation.

Deciphering m6A dynamics at a single-base level during planarian anterior-posterior axis specification

BACKGROUND

The establishment of the anterior-posterior (A-P) axis is a crucial step during tissue repair and regeneration. Despite the association reported recently of N6-methyladenosine (m6A) with regeneration, the mechanism underlying the regulation of m6A in A-P axis specification during regeneration remains unknown. Herein, we deciphered the m6A landscape at a single-base resolution at multiple time points during A-P axis regeneration and constructed the de novo transcriptome assembly of the Dugesia japonica planarian.

RESULTS

Immunofluorescence staining and comparative analysis revealed that m6A is widespread across the planarian and dynamically regulated during regeneration along the A-P axis, exhibiting a strong spatiotemporal feature. The resulting datasets of m6A-modified genes identified 80 anterior-specific genes and 13 posterior-specific genes, respectively. In addition, we showed that YTHDC1 serves as the primary m6A reader to be involved in the m6A-mediated specification of A-P axis during regeneration in Dugesia japonica planarian.

CONCLUSIONS

Our study provides an RNA epigenetic explanation for the specification of the A-P axis during tissue regeneration in planarian.

Transcriptome-wide profiling and quantification of N6-methyladenosine by enzyme-assisted adenosine deamination

N6-methyladenosine (m6A), the most abundant internal messenger RNA modification in higher eukaryotes, serves myriad roles in regulating cellular processes. Functional dissection of m6A is, however, hampered in part by the lack of high-resolution and quantitative detection methods. Here we present evolved TadA-assisted N6-methyladenosine sequencing (eTAM-seq), an enzyme-assisted sequencing technology that detects and quantifies m6A by global adenosine deamination. With eTAM-seq, we analyze the transcriptome-wide distribution of m6A in HeLa and mouse embryonic stem cells. The enzymatic deamination route employed by eTAM-seq preserves RNA integrity, facilitating m6A detection from limited input samples. In addition to transcriptome-wide m6A profiling, we demonstrate site-specific, deep-sequencing-free m6A quantification with as few as ten cells, an input demand orders of magnitude lower than existing quantitative profiling methods. We envision that eTAM-seq will enable researchers to not only survey the m6A landscape at unprecedented resolution, but also detect m6A at user-specified loci with a simple workflow.

Navigating the pitfalls of mapping DNA and RNA modifications

Chemical modifications to nucleic acids occur across the kingdoms of life and carry important regulatory information. Reliable high-resolution mapping of these modifications is the foundation of functional and mechanistic studies, and recent methodological advances based on next-generation sequencing and long-read sequencing platforms are critical to achieving this aim. However, mapping technologies may have limitations that sometimes lead to inconsistent results. Some of these limitations are technical in nature and specific to certain types of technology. Here, however, we focus on common (yet not always widely recognized) pitfalls that are shared among frequently used mapping technologies and discuss strategies to help technology developers and users mitigate their effects. Although the emphasis is primarily on DNA modifications, RNA modifications are also discussed.

RNA Modification in the Immune System

Characterization of RNA modifications has identified their distribution features and molecular functions. Dynamic changes in RNA modification on various forms of RNA are essential for the development and function of the immune system. In this review, we discuss the value of innovative RNA modification profiling technologies to uncover the function of these diverse, dynamic RNA modifications in various immune cells within healthy and diseased contexts. Further, we explore our current understanding of the mechanisms whereby aberrant RNA modifications modulate the immune milieu of the tumor microenvironment and point out outstanding research questions.

Systematic comparison of tools used for m6A mapping from nanopore direct RNA sequencing

N6-methyladenosine (m6A) has been increasingly recognized as a new and important regulator of gene expression. To date, transcriptome-wide m6A detection primarily relies on well-established methods using next-generation sequencing (NGS) platform. However, direct RNA sequencing (DRS) using the Oxford Nanopore Technologies (ONT) platform has recently emerged as a promising alternative method to study m6A. While multiple computational tools are being developed to facilitate the direct detection of nucleotide modifications, little is known about the capabilities and limitations of these tools. Here, we systematically compare ten tools used for mapping m6A from ONT DRS data. We find that most tools present a trade-off between precision and recall, and integrating results from multiple tools greatly improve performance. Using a negative control could improve precision by subtracting certain intrinsic bias. We also observed variation in detection capabilities and quantitative information among motifs, and identified sequencing depth and m6A stoichiometry as potential factors affecting performance. Our study provides insight into the computational tools currently used for mapping m6A based on ONT DRS data and highlights the potential for further improving these tools, which may serve as the basis for future research.

The essential roles of small non-coding RNAs and RNA modifications in normal and malignant hematopoiesis

Hematopoietic stem cells (HSCs) developing from mesoderm during embryogenesis are important for the blood circulatory system and immune system. Many factors such as genetic factors, chemical exposure, physical radiation, and viral infection, can lead to the dysfunction of HSCs. Hematological malignancies (involving leukemia, lymphoma, and myeloma) were diagnosed in more than 1.3 million people globally in 2021, taking up 7% of total newly-diagnosed cancer patients. Although many treatments like chemotherapy, bone marrow transplantation, and stem cell transplantation have been applied in clinical therapeutics, the average 5-year survival rate for leukemia, lymphoma, and myeloma is about 65%, 72%, and 54% respectively. Small non-coding RNAs play key roles in a variety of biological processes, including cell division and proliferation, immunological response and cell death. With the development of technologies in high-throughput sequencing and bioinformatic analysis, there is emerging research about modifications on small non-coding RNAs, as well as their functions in hematopoiesis and related diseases. In this study, we summarize the updated information of small non-coding RNAs and RNA modifications in normal and malignant hematopoiesis, which sheds lights into the future application of HSCs into the treatment of blood diseases.

Dynamics of RNA m5C modification during brain development

Post-transcriptional RNA modifications have been recognized as key regulators of neuronal differentiation and synapse development in the mammalian brain. While distinct sets of 5-methylcytosine (m⁵C) modified mRNAs have been detected in neuronal cells and brain tissues, no study has been performed to characterize methylated mRNA profiles in the developing brain. Here, together with regular RNA-seq, we performed transcriptome-wide bisulfite sequencing to compare RNA cytosine methylation patterns in neural stem cells (NSCs), cortical neuronal cultures, and brain tissues at three postnatal stages. Among 501 m⁵C sites identified, approximately 6% are consistently methylated across all five conditions. Compared to m⁵C sites identified in NSCs, 96% of them were hypermethylated in neurons and enriched for genes involved in positive transcriptional regulation and axon extension. In addition, brains at the early postnatal stage demonstrated substantial changes in both RNA cytosine methylation and gene expression of RNA cytosine methylation readers, writers, and erasers. Furthermore, differentially methylated transcripts were significantly enriched for genes regulating synaptic plasticity. Altogether, this study provides a brain epitranscriptomic dataset as a new resource and lays the foundation for further investigations into the role of RNA cytosine methylation during brain development.

Absolute quantification of single-base m6A methylation in the mammalian transcriptome using GLORI

N6-methyladenosine (m6A) is the most abundant RNA modification in mammalian cells and the best-studied epitranscriptomic mark. Despite the development of various tools to map m6A, a transcriptome-wide method that enables absolute quantification of m6A at single-base resolution is lacking. Here we use glyoxal and nitrite-mediated deamination of unmethylated adenosines (GLORI) to develop an absolute m6A quantification method that is conceptually similar to bisulfite-sequencing-based quantification of DNA 5-methylcytosine. We apply GLORI to quantify the m6A methylomes of mouse and human cells and reveal clustered m6A modifications with differential distribution and stoichiometry. In addition, we characterize m6A dynamics under stress and examine the quantitative landscape of m6A modification in gene expression regulation. GLORI is an unbiased, convenient method for the absolute quantification of the m6A methylome.