HAMR: high-throughput annotation of modified ribonucleotides

Transcriptome-wide mapping of N3-methylcytidine modification at single-base resolution

3-Methylcytidine (m3C), a prevalent modification of transfer RNAs (tRNAs), was recently identified in eukaryotic messenger RNAs (mRNAs). However, its precise distribution and formation mechanisms in mRNAs remain elusive. Here, we develop a novel approach, m3C immunoprecipitation and sequencing (m3C-IP-seq), utilizing antibody enrichment to profile the m3C methylome at single-nucleotide resolution. m3C-IP-seq captures 12 cytoplasmic tRNA isoacceptors and 2 mitochondrial tRNA isoacceptors containing m3C modifications. Moreover, m3C-IP-seq permits the comprehensive profiling of m3C sites in mRNAs and long noncoding RNAs, with their presence reliant on a nuclear isoform of METTL8. A significant proportion of m3C sites is concentrated in the 3' untranslated region (3' UTR) of mRNAs and is associated with mRNA degradation. Additionally, m3C methylation is dynamic and responds to hypoxia. Collectively, our data demonstrate the widespread presence of m3C modification in the human transcriptome and provide a resource for functional studies of m3C-mediated RNA metabolism.

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.

A ligation-independent sequencing method reveals tRNA-derived RNAs with blocked 3' termini

Despite the numerous sequencing methods available, the diversity in RNA size and chemical modification makes it difficult to capture all RNAs in a cell. We developed a method that combines quasi-random priming with template switching to construct sequencing libraries from RNA molecules of any length and with any type of 3' modifications, allowing for the sequencing of virtually all RNA species. Our ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to identify and quantify all classes of coding and non-coding RNAs. With LIDAR, we comprehensively characterized the transcriptomes of mouse embryonic stem cells, neural progenitor cells, mouse tissues, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared with traditional ligation-dependent sequencing methods and uncovered tDRs with blocked 3' ends that had previously escaped detection. Therefore, LIDAR can capture all RNAs in a sample and uncover RNA species with potential regulatory functions.

Comparative analyses suggest a link between mRNA splicing, stability, and RNA covalent modifications in flowering plants

BACKGROUND

In recent years, covalent modifications on RNA nucleotides have emerged as pivotal moieties influencing the structure, function, and regulatory processes of RNA Polymerase II transcripts such as mRNAs and lncRNAs. However, our understanding of their biological roles and whether these roles are conserved across eukaryotes remains limited.

RESULTS

In this study, we leveraged standard polyadenylation-enriched RNA-sequencing data to identify and characterize RNA modifications that introduce base-pairing errors into cDNA reads. Our investigation incorporated data from three Poaceae (Zea mays, Sorghum bicolor, and Setaria italica), as well as publicly available data from a range of stress and genetic contexts in Sorghum and Arabidopsis thaliana. We uncovered a strong enrichment of RNA covalent modifications (RCMs) deposited on a conserved core set of nuclear mRNAs involved in photosynthesis and translation across these species. However, the cohort of modified transcripts changed based on environmental context and developmental program, a pattern that was also conserved across flowering plants. We determined that RCMs can partly explain accession-level differences in drought tolerance in Sorghum, with stress-associated genes receiving a higher level of RCMs in a drought tolerant accession. To address function, we determined that RCMs are significantly enriched near exon junctions within coding regions, suggesting an association with splicing. Intriguingly, we found that these base-pair disrupting RCMs are associated with stable mRNAs, are highly correlated with protein abundance, and thus likely associated with facilitating translation.

CONCLUSIONS

Our data point to a conserved role for RCMs in mRNA stability and translation across the flowering plant lineage.

General Principles and Limitations for Detection of RNA Modifications by Sequencing

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

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.

Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing

Transfer RNAs (tRNAs) play a central role in protein translation. Studying them has been difficult in part because a simple method to simultaneously quantify their abundance and chemical modifications is lacking. Here we introduce Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations that provides quantitative estimates of both tRNA abundances and modification dynamics in a single experiment. We show that default nanopore sequencing settings discard the vast majority of tRNA reads, leading to poor sequencing yields and biased representations of tRNA abundances based on their transcript length. Re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads and enables recapitulation of accurate tRNA abundances. We then apply Nano-tRNAseq to Saccharomyces cerevisiae tRNA populations, revealing crosstalks and interdependencies between different tRNA modification types within the same molecule and changes in tRNA populations in response to oxidative stress.

Analysis approaches for the identification and prediction of N6-methyladenosine sites

The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m⁶A sites, in particular full-transcriptome m⁶A. And individual m⁶A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single nucleotide resolution. Currently, the identification of m⁶A sites is mainly carried out by experiment and prediction methods, based on high-throughput sequencing and machine learning model respectively. This review summarizes the recent topics and progress made in bioinformatics methods of deciphering the m⁶A methylation, including the experimental detection of m⁶A methylation sites, techniques of data analysis, the way of predicting m⁶A methylation sites, m⁶A methylation databases, and detection of m⁶A modification in circRNA. At the end, the essay makes a brief discussion for the development perspective in this area.

m6A RNA demethylase AtALKBH9B promotes mobilization of a heat-activated long terminal repeat retrotransposon in Arabidopsis

Transposons are mobile and ubiquitous DNA molecules that can cause vast genomic alterations. In plants, it is well documented that transposon mobilization is strongly repressed by DNA methylation; however, its regulation at the posttranscriptional level remains relatively uninvestigated. Here, we suggest that transposon RNA is marked by m6A RNA methylation and can be localized in stress granules (SGs). Intriguingly, SG-localized AtALKBH9B selectively demethylates a heat-activated retroelement, Onsen, and thereby releases it from spatial confinement, allowing for its mobilization. In addition, we show evidence that m6A RNA methylation contributes to transpositional suppression by inhibiting virus-like particle assembly and extrachromosomal DNA production. In summary, this study unveils a previously unknown role for m6A in the suppression of transposon mobility and provides insight into how transposons counteract the m6A-mediated repression mechanism by hitchhiking the RNA demethylase of the host.

Identifying N6-Methyladenosine Sites in HepG2 Cell Lines Using Oxford Nanopore Technology

RNA modifications, particularly N6-methyladenosine (m6A), are pivotal regulators of RNA functionality and cellular processes. We analyzed m6A modifications by employing Oxford Nanopore technology and the m6Anet algorithm, focusing on the HepG2 cell line. We identified 3968 potential m6A modification sites in 2851 transcripts, corresponding to 1396 genes. A gene functional analysis revealed the active involvement of m6A-modified genes in ubiquitination, transcription regulation, and protein folding processes, aligning with the known role of m6A modifications in histone ubiquitination in cancer. To ensure data robustness, we assessed reproducibility across technical replicates. This study underscores the importance of evaluating algorithmic reproducibility, especially in supervised learning. Furthermore, we examined correlations between transcriptomic, translatomic, and proteomic levels. A strong transcriptomic-translatomic correlation was observed. In conclusion, our study deepens our understanding of m6A modifications' multifaceted impacts on cellular processes and underscores the importance of addressing reproducibility concerns in analytical approaches.

MRT-ModSeq - Rapid Detection of RNA Modifications with MarathonRT

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

Shining a spotlight on m6A and the vital role of RNA modification in endometrial cancer: a review

RNA modifications are mostly dynamically reversible post-transcriptional modifications, of which m6A is the most prevalent in eukaryotic mRNAs. A growing number of studies indicate that RNA modification can finely tune gene expression and modulate RNA metabolic homeostasis, which in turn affects the self-renewal, proliferation, apoptosis, migration, and invasion of tumor cells. Endometrial carcinoma (EC) is the most common gynecologic tumor in developed countries. Although it can be diagnosed early in the onset and have a preferable prognosis, some cases might develop and become metastatic or recurrent, with a worse prognosis. Fortunately, immunotherapy and targeted therapy are promising methods of treating endometrial cancer patients. Gene modifications may also contribute to these treatments, as is especially the case with recent developments of new targeted therapeutic genes and diagnostic biomarkers for EC, even though current findings on the relationship between RNA modification and EC are still very limited, especially m6A. For example, what is the elaborate mechanism by which RNA modification affects EC progression? Taking m6A modification as an example, what is the conversion mode of methylation and demethylation for RNAs, and how to achieve selective recognition of specific RNA? Understanding how they cope with various stimuli as part of in vivo and in vitro biological development, disease or tumor occurrence and development, and other processes is valuable and RNA modifications provide a distinctive insight into genetic information. The roles of these processes in coping with various stimuli, biological development, disease, or tumor development in vivo and in vitro are self-evident and may become a new direction for cancer in the future. In this review, we summarize the category, characteristics, and therapeutic precis of RNA modification, m6A in particular, with the purpose of seeking the systematic regulation axis related to RNA modification to provide a better solution for the treatment of EC.

Epitranscriptomic subtyping, visualization, and denoising by global motif visualization

Advances in sequencing technologies have empowered epitranscriptomic profiling at the single-base resolution. Putative RNA modification sites identified from a single high-throughput experiment may contain one type of modification deposited by different writers or different types of modifications, along with false positive results because of the challenge of distinguishing signals from noise. However, current tools are insufficient for subtyping, visualization, and denoising these signals. Here, we present iMVP, which is an interactive framework for epitranscriptomic analysis with a nonlinear dimension reduction technique and density-based partition. As exemplified by the analysis of mRNA m5C and ModTect variant data, we show that iMVP allows the identification of previously unknown RNA modification motifs and writers and the discovery of false positives that are undetectable by traditional methods. Using putative m6A/m6Am sites called from 8 profiling approaches, we illustrate that iMVP enables comprehensive comparison of different approaches and advances our understanding of the difference and pattern of true positives and artifacts in these methods. Finally, we demonstrate the ability of iMVP to analyze an extremely large human A-to-I editing dataset that was previously unmanageable. Our work provides a general framework for the visualization and interpretation of epitranscriptomic data.

Single-Base Resolution Detection of N6-Methyladenosine in RNA by Adenosine Deamination Sequencing

N⁶-Methyladenosine (m⁶A) is one of the most abundant and prevalent natural modifications occurring in diverse RNA species. m⁶A plays a wide range of roles in physiological and pathological processes. Revealing the functions of m⁶A relies on the faithful detection of individual m⁶A sites in RNA. However, developing a simple method for the single-base resolution detection of m⁶A is still a challenging task. Herein, we report an adenosine deamination sequencing (AD-seq) technique for the facile detection of m⁶A in RNA at single-base resolution. The AD-seq approach capitalizes on the selective deamination of adenosine, but not m⁶A, by the evolved tRNA adenosine deaminase (TadA) variant of TadA8e or the dimer protein of TadA-TadA8e. In AD-seq, adenosine is deaminated by TadA8e or TadA-TadA8e to form inosine, which pairs with cytidine and is read as guanosine in sequencing. m⁶A resists deamination due to the interference of the methyl group at the N6 position of adenosine. Thus, the m⁶A base pairs with thymine and is still read as adenosine in sequencing. The differential readouts from A and m⁶A in sequencing can achieve the single-base resolution detection of m⁶A in RNA. Application of the proposed AD-seq successfully identified individual m⁶A sites in Escherichia coli 23S rRNA. Taken together, the proposed AD-seq allows simple and cost-effective detection of m⁶A at single-base resolution in RNA, which provides a valuable tool to decipher the functions of m⁶A in RNA.

Artifacts and biases of the reverse transcription reaction in RNA sequencing

RNA sequencing has spurred a significant number of research areas in recent years. Most protocols rely on synthesizing a more stable complementary DNA (cDNA) copy of the RNA molecule during the reverse transcription reaction. The resulting cDNA pool is often wrongfully assumed to be quantitatively and molecularly similar to the original RNA input. Sadly, biases and artifacts confound the resulting cDNA mixture. These issues are often overlooked or ignored in the literature by those that rely on the reverse transcription process. In this review, we confront the reader with intra- and intersample biases and artifacts caused by the reverse transcription reaction during RNA sequencing experiments. To fight the reader's despair, we also provide solutions to most issues and inform on good RNA sequencing practices. We hope the reader can use this review to their advantage, thereby contributing to scientifically sound RNA studies.

A ligation-independent sequencing method reveals tRNA-derived RNAs with blocked 3' termini

Despite the numerous sequencing methods available, the vast diversity in size and chemical modifications of RNA molecules makes the capture of the full spectrum of cellular RNAs a difficult task. By combining quasi-random hexamer priming with a custom template switching strategy, we developed a method to construct sequencing libraries from RNA molecules of any length and with any type of 3' terminal modification, allowing the sequencing and analysis of virtually all RNA species. Ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to comprehensively characterize changes in small non-coding RNAs and mRNAs simultaneously, with performance comparable to separate dedicated methods. With LIDAR, we comprehensively characterized the coding and non-coding transcriptome of mouse embryonic stem cells, neural progenitor cells, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared to traditional ligation-dependent sequencing methods, and uncovered the presence of tDRs with blocked 3' ends that had previously escaped detection. Our findings highlight the potential of LIDAR to systematically detect all RNAs in a sample and uncover new RNA species with potential regulatory functions.

Linking discoveries, mechanisms, and technologies to develop a clearer perspective on plant long noncoding RNAs

Long noncoding RNAs (lncRNAs) are a large and diverse class of genes in eukaryotic genomes that contribute to a variety of regulatory processes. Functionally characterized lncRNAs play critical roles in plants, ranging from regulating flowering to controlling lateral root formation. However, findings from the past decade have revealed that thousands of lncRNAs are present in plant transcriptomes, and characterization has lagged far behind identification. In this setting, distinguishing function from noise is challenging. However, the plant community has been at the forefront of discovery in lncRNA biology, providing many functional and mechanistic insights that have increased our understanding of this gene class. In this review, we examine the key discoveries and insights made in plant lncRNA biology over the past two and a half decades. We describe how discoveries made in the pregenomics era have informed efforts to identify and functionally characterize lncRNAs in the subsequent decades. We provide an overview of the functional archetypes into which characterized plant lncRNAs fit and speculate on new avenues of research that may uncover yet more archetypes. Finally, this review discusses the challenges facing the field and some exciting new molecular and computational approaches that may help inform lncRNA comparative and functional analyses.

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

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

MRT-ModSeq - Rapid detection of RNA modifications with MarathonRT

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

The role of post-transcriptional modification on a new tRNAIle(GAU) identified from Ganoderma lucidum in its fragments' cytotoxicity on cancer cells

Ganoderma lucidum (Ganoderma) is a famous Chinese herbal medicine which has been used clinically for thousands of years in China. Despite numerous studies on triterpenes and polysaccharides, the bioactivity of RNAs abundant in Ganoderma remains unknown. Here, based on LC-MS techniques, dihydrouracil, 5-methyluridine (m⁵U) and pseudouridine were identified at position 19, 52 and 53 of a new tRNA^Ile(GAU) which was isolated as the most abundant tRNA species in Ganoderma, and is the first purified tRNA from fungus. Cytotoxic screening of tRNA-half (t-half) and tRNA fragment (tRF) derived from this tRNA, as well as their mimics (t-half or tRF as antisense strand), demonstrated that the double-stranded form, i.e., tRF and t-halve mimics, exhibited stronger cytotoxicity than their single-stranded form, and the cytotoxicity of t-half mimic is significantly stronger than that of tRF mimic. Notably, the cytotoxicity of 3'-t-half mimic is not only much more potent than that of taxol, but also is much more potent than that of ganoderic acids, the major bioactive components in Ganoderma. Furthermore, 3'-t-half mimic_M2 (m⁵U modified) exhibited significantly stronger cytotoxicity than unmodified 3'-t-half mimic, which is consistent with the computational simulation showing that m⁵U modification enhances the stability of the tertiary structure of 3'-t-half mimic. Overall, the present study not only indicates t-halves are bioactive components in Ganoderma which should not be neglected, but also reveals an important role of post-transcriptional modification on tRNA in its fragments' cytotoxicity against cancer cells, which benefits the design and development of RNAi drugs from natural resource.

Occurrence of RNA post-transcriptional modifications in plant viruses and viroids and their correlation with structural and functional features

Post-transcriptional modifications of RNA bases are widespread across all the tree of life and have been linked to RNA maturation, stability, and molecular interactions. RNA modifications have been extensively described in endogenous eukaryotic mRNAs, however, little is known about the presence of RNA modifications in plant viral and subviral RNAs. Here, we used a computational approach to infer RNA modifications in plant-pathogenic viruses and viroids using high-throughput annotation of modified ribonucleotides (HAMR), a software that predicts modified ribonucleotides using high-throughput RNA sequencing data. We analyzed datasets from representative members of different plant viruses and viroids and compared them to plant-endogenous mRNAs. Our approach was able to predict potential RNA chemical modifications (RCMs) in all analyzed pathogens. We found that both DNA and RNA viruses presented a wide range of RCM proportions while viroids had lowest values. Furthermore, we found that for viruses with segmented genomes, some genomic RNAs had a higher proportion of RCM. Interestingly, nuclear-replicating viroids showed most of the predicted modifications located in the pathogenesis region, pointing towards a possible functional role of RCMs in their infectious cycle. Thus, our results strongly suggest that plant viral and subviral RNAs might contain a variety of previously unreported RNA modifications, thus opening a new perspective in the multifaceted process of plant-pathogen interactions.

Nano3P-seq: transcriptome-wide analysis of gene expression and tail dynamics using end-capture nanopore cDNA sequencing

RNA polyadenylation plays a central role in RNA maturation, fate, and stability. In response to developmental cues, polyA tail lengths can vary, affecting the translation efficiency and stability of mRNAs. Here we develop Nanopore 3' end-capture sequencing (Nano3P-seq), a method that relies on nanopore cDNA sequencing to simultaneously quantify RNA abundance, tail composition, and tail length dynamics at per-read resolution. By employing a template-switching-based sequencing protocol, Nano3P-seq can sequence RNA molecule from its 3' end, regardless of its polyadenylation status, without the need for PCR amplification or ligation of RNA adapters. We demonstrate that Nano3P-seq provides quantitative estimates of RNA abundance and tail lengths, and captures a wide diversity of RNA biotypes. We find that, in addition to mRNA and long non-coding RNA, polyA tails can be identified in 16S mitochondrial ribosomal RNA in both mouse and zebrafish models. Moreover, we show that mRNA tail lengths are dynamically regulated during vertebrate embryogenesis at an isoform-specific level, correlating with mRNA decay. Finally, we demonstrate the ability of Nano3P-seq in capturing non-A bases within polyA tails of various lengths, and reveal their distribution during vertebrate embryogenesis. Overall, Nano3P-seq is a simple and robust method for accurately estimating transcript levels, tail lengths, and tail composition heterogeneity in individual reads, with minimal library preparation biases, both in the coding and non-coding transcriptome.

tncRNA Toolkit: A pipeline for convenient identification of RNA (tRNA)-derived non-coding RNAs

Insights into the eukaryotic gene regulation networks have improved due to the advent of diverse classes of non-coding RNAs. The transfer RNA (tRNA)-derived non-coding RNAs or tncRNAs is a novel class of non-coding RNAs, shown to regulate gene expression at transcription and translation levels. Here, we present a pipeline 'tncRNA Toolkit' for accurately identifying tncRNAs using small RNA sequencing (sRNA-seq) data. Previously, we identified tncRNA in six major angiosperms by utilizing our pipeline and highlighted the significant points regarding their generation and functions. The 'tncRNA Toolkit' is available at the URL: http://www.nipgr.ac.in/tncRNA. The scripts are written in bash and Python3 programming languages. The program can be efficiently run as a standalone command-line tool and installed in any Linux-based Operating System (OS). The user can run this program by providing the input of sRNA-seq data and genome file.The various features of the 'tncRNA Toolkit' are as follows:•Major tncRNA classes identified by this tool include tRF-5, tRF-3, tRF-1, 5'tRH, 3'tRH, and leader tRF. Also, it categorizes miscellaneous tncRNAs as other tRF.•It provides the following information for each identified tncRNA viz. tncRNA class, raw and normalized read count (RPM), read length, progenitor tRNA information (amino acid, anticodon, locus, strand), tncRNA sequence, and tRNA modification sites.•We hope to facilitate quick and reliable tncRNA identification, which will boost the exploration of this novel class of non-coding RNAs and their relevance in the living world, including plants.

Dynamic regulation and key roles of ribonucleic acid methylation

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

Exploring the epitranscriptome by native RNA sequencing

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

Detection technologies for RNA modifications

To date, more than 170 chemical modifications have been characterized in RNA, providing a new layer of gene expression regulation termed the 'epitranscriptome'. RNA modification detection methods and tools advance the functional studies of the epitranscriptome. According to the detection throughput and principles, existing RNA modification detection technologies can be categorized into four classes, including quantification methods, locus-specific detection methods, next-generation sequencing-based detection technologies and nanopore direct RNA sequencing-based technologies. In this review, we summarize the current knowledge about these RNA modification detection technologies and discuss the challenges for the existing detection tools, providing information for a comprehensive understanding of the epitranscriptome.

Analysis of queuosine and 2-thio tRNA modifications by high throughput sequencing

Queuosine (Q) is a conserved tRNA modification at the wobble anticodon position of tRNAs that read the codons of amino acids Tyr, His, Asn, and Asp. Q-modification in tRNA plays important roles in the regulation of translation efficiency and fidelity. Queuosine tRNA modification is synthesized de novo in bacteria, whereas in mammals the substrate for Q-modification in tRNA is queuine, the catabolic product of the Q-base of gut bacteria. This gut microbiome dependent tRNA modification may play pivotal roles in translational regulation in different cellular contexts, but extensive studies of Q-modification biology are hindered by the lack of high throughput sequencing methods for its detection and quantitation. Here, we describe a periodate-treatment method that enables single base resolution profiling of Q-modification in tRNAs by Nextgen sequencing from biological RNA samples. Periodate oxidizes the Q-base, which results in specific deletion signatures in the RNA-seq data. Unexpectedly, we found that periodate-treatment also enables the detection of several 2-thio-modifications including τm5s2U, mcm5s2U, cmnm5s2U, and s2C by sequencing in human and E. coli tRNA. We term this method periodate-dependent analysis of queuosine and sulfur modification sequencing (PAQS-seq). We assess Q- and 2-thio-modifications at the tRNA isodecoder level, and 2-thio modification changes in stress response. PAQS-seq should be widely applicable in the biological studies of Q- and 2-thio-modifications in mammalian and microbial tRNAs.

Dysregulated mitochondrial and cytosolic tRNA m1A methylation in Alzheimer's disease

RNA modifications affect many aspects of RNA metabolism and are involved in the regulation of many different biological processes. Mono-methylation of adenosine in the N1 position, N1-methyladensoine (m1A), is a reversible modification that is known to target rRNAs and tRNAs. m1A has been shown to increase tRNA structural stability and induce correct tRNA folding. Recent studies have begun to associate the dysregulation of epitranscriptomic control with age-related disorders such as Alzheimer's disease. Here, we applied the newly developed m1A-quant-seq approach to map the brain abundant m1A RNA modification in the cortex of an Alzheimer's disease mouse model, 5XFAD. We observed hypomethylation in both mitochondrial and cytosolic tRNAs in 5XFAD mice compared with wild type. Furthermore, the main enzymes responsible for the addition of m1A in mitochondrial (TRMT10C, HSD17B10) and cytosolic tRNAs (TRMT61A) displayed decreased expression in 5XFAD compared with wild-type mice. Knockdown of these enzymes results in a more severe phenotype in a Drosophila tau model, and differential m1A methylation is correlated with differences in mature mitochondrial tRNA expression. Collectively, this work suggests that hypo m1A modification in tRNAs may play a role in Alzheimer's disease pathogenesis.

PhOxi-Seq: Single-Nucleotide Resolution Sequencing of N2-Methylation at Guanosine in RNA by Photoredox Catalysis

Chemical modifications regulate the fate and function of cellular RNAs. Newly developed sequencing methods have allowed a deeper understanding of the biological role of RNA modifications; however, the vast majority of post-transcriptional modifications lack a well-defined sequencing method. Here, we report a photo-oxidative sequencing (PhOxi-seq) approach for guanosine N²-methylation, a common methylation mark seen in N²-methylguanosine (m²G) and N²,N²-dimethylguanosine (m²₂G). Using visible light-mediated organic photoredox catalysis, m²G and m²₂G are chemoselectively oxidized in the presence of canonical RNA nucleosides, which results in a strong mutation signature observed during sequencing. PhOxi-seq was demonstrated on various tRNAs and rRNA to reveal N²-methylation with excellent response and markedly improved read-through at m²₂G sites.

Functions and consequences of AID/APOBEC-mediated DNA and RNA deamination

The AID/APOBEC polynucleotide cytidine deaminases have historically been classified as either DNA mutators or RNA editors based on their first identified nucleic acid substrate preference. DNA mutators can generate functional diversity at antibody genes but also cause genomic instability in cancer. RNA editors can generate informational diversity in the transcriptome of innate immune cells, and of cancer cells. Members of both classes can act as antiviral restriction factors. Recent structural work has illuminated differences and similarities between AID/APOBEC enzymes that can catalyse DNA mutation, RNA editing or both, suggesting that the strict functional classification of members of this family should be reconsidered. As many of these enzymes have been employed for targeted genome (or transcriptome) editing, a more holistic understanding will help improve the design of therapeutically relevant programmable base editors.

In this Perspective, Pecori et al. provide an overview of the AID/APOBEC cytidine deaminase family, discussing key structural features, how they contribute to viral and tumour evolution and how they can be harnessed for (potentially therapeutic) base-editing purposes.

tRNA modification dynamics from individual organisms to metaepitranscriptomics of microbiomes

tRNA is the most extensively modified RNA in cells. On average, a bacterial tRNA contains 8 modifications per molecule and a eukaryotic tRNA contains 13 modifications per molecule. Recent studies reveal that tRNA modifications are highly dynamic and respond extensively to environmental conditions. Functions of tRNA modification dynamics include enhanced, on-demand decoding of specific codons in response genes and regulation of tRNA fragment biogenesis. This review summarizes recent advances in the studies of tRNA modification dynamics in biological processes, tRNA modification erasers, and human-associated bacteria. Furthermore, we use the term "metaepitranscriptomics" to describe the potential and approach of tRNA modification studies in natural biological communities such as microbiomes. tRNA is highly modified in cells, and tRNA modifications respond extensively to environmental conditions to enhance translation of specific genes and produce tRNA fragments on demand. We review recent advances in tRNA sequencing methods, tRNA modification dynamics in biological processes, and tRNA modification studies in natural communities such as the microbiomes.

A versatile tRNA modification-sensitive northern blot method with enhanced performance

The 22 mitochondrial and ∼45 cytosolic tRNAs in human cells contain several dozen different post-transcriptional modified nucleotides such that each carries a unique constellation that complements its function. Many tRNA modifications are linked to altered gene expression, and deficiencies due to mutations in tRNA modification enzymes (TMEs) are responsible for numerous diseases. Easily accessible methods to detect tRNA hypomodifications can facilitate progress in advancing such molecular studies. Our laboratory developed a northern blot method that can quantify relative levels of base modifications on multiple specific tRNAs ∼10 yr ago, which has been used to characterize four different TME deficiencies and is likely further extendable. The assay method depends on differential annealing efficiency of a DNA-oligo probe to the modified versus unmodified tRNA. The signal of this probe is then normalized by a second probe elsewhere on the same tRNA. This positive hybridization in the absence of modification (PHAM) assay has proven useful for i6A37, t6A37, m3C32, and m2,2G26 in multiple laboratories. Yet, over the years we have observed idiosyncratic inconsistency and variability in the assay. Here we document these for some tRNAs and probes and illustrate principles and practices for improved reliability and uniformity in performance. We provide an overview of the method and illustrate benefits of the improved conditions. This is followed by data that demonstrate quantitative validation of PHAM using a TME deletion control, and that nearby modifications can falsely alter the calculated apparent modification efficiency. Finally, we include a calculator tool for matching probe and hybridization conditions.

Dysregulation of Human Somatic piRNA Expression in Parkinson's Disease Subtypes and Stages

Piwi interacting RNAs (piRNAs) are small non-coding single-stranded RNA species 20–31 nucleotides in size generated from distinct loci. In germline tissues, piRNAs are amplified via a “ping-pong cycle” to produce secondary piRNAs, which act in transposon silencing. In contrast, the role of somatic-derived piRNAs remains obscure. Here, we investigated the identity and distribution of piRNAs in human somatic tissues to determine their function and potential role in Parkinson’s disease (PD). Human datasets were curated from the Gene Expression Omnibus (GEO) database and a workflow was developed to identify piRNAs, which revealed 902 somatic piRNAs of which 527 were expressed in the brain. These were mainly derived from chromosomes 1, 11, and 19 compared to the germline tissues, which were from 15 and 19. Approximately 20% of somatic piRNAs mapped to transposon 3′ untranslated regions (UTRs), but a large proportion were sensed to the transcript in contrast to germline piRNAs. Gene set enrichment analysis suggested that somatic piRNAs function in neurodegenerative disease. piRNAs undergo dysregulation in different PD subtypes (PD and Parkinson’s disease dementia (PDD)) and stages (premotor and motor). piR-has-92056, piR-hsa-150797, piR-hsa-347751, piR-hsa-1909905, piR-hsa-2476630, and piR-hsa-2834636 from blood small extracellular vesicles were identified as novel biomarkers for PD diagnosis using a sparse partial least square discriminant analysis (sPLS-DA) (accuracy: 92%, AUC = 0.89). This study highlights a role for piRNAs in PD and provides tools for novel biomarker development.

Detection of m6A from direct RNA sequencing using a multiple instance learning framework

RNA modifications such as m6A methylation form an additional layer of complexity in the transcriptome. Nanopore direct RNA sequencing can capture this information in the raw current signal for each RNA molecule, enabling the detection of RNA modifications using supervised machine learning. However, experimental approaches provide only site-level training data, whereas the modification status for each single RNA molecule is missing. Here we present m6Anet, a neural-network-based method that leverages the multiple instance learning framework to specifically handle missing read-level modification labels in site-level training data. m6Anet outperforms existing computational methods, shows similar accuracy as experimental approaches, and generalizes with high accuracy to different cell lines and species without retraining model parameters. In addition, we demonstrate that m6Anet captures the underlying read-level stoichiometry, which can be used to approximate differences in modification rates. Overall, m6Anet offers a tool to capture the transcriptome-wide identification and quantification of m6A from a single run of direct RNA sequencing.

The ribosome epitranscriptome: inert-or a platform for functional plasticity?

A universal property of all rRNAs explored to date is the prevalence of post-transcriptional ("epitranscriptional") modifications, which expand the chemical and topological properties of the four standard nucleosides. Are these modifications an inert, constitutive part of the ribosome? Or could they, in part, also regulate the structure or function of the ribosome? In this review, we summarize emerging evidence that rRNA modifications are more heterogeneous than previously thought, and that they can also vary from one condition to another, such as in the context of a cellular response or a developmental trajectory. We discuss the implications of these results and key open questions on the path toward connecting such heterogeneity with function.

Transfer RNA-derived non-coding RNAs (tncRNAs): Hidden regulation of plants' transcriptional regulatory circuits

The emergence of distinct classes of non-coding RNAs has led to better insights into the eukaryotic gene regulatory networks. Amongst them, the existence of transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs) demands exploration in the plant kingdom. We have designed a methodology to uncover the entire perspective of tncRNAome in plants. Using this pipeline, we have identified diverse tncRNAs with a size ranging from 14 to 50 nucleotides (nt) by utilizing 2448 small RNA-seq samples from six angiosperms, and studied their various features, including length, codon-usage, cleavage pattern, and modified tRNA nucleosides. Codon-dependent generation of tncRNAs suggests that the tRNA cleavage is highly specific rather than random tRNA degradation. The nucleotide composition analysis of tncRNA cleavage positions indicates that they are generated through precise endoribonucleolytic cleavage machinery. Certain nucleoside modifications detected on tncRNAs were found to be conserved across the plants, and hence may influence tRNA cleavage, as well as tncRNA functions. Pathway enrichment analysis revealed that common tncRNA targets are majorly enriched during metabolic and developmental processes. Further distinct tissue-specific tncRNA clusters highlight their role in plant development. Significant number of tncRNAs differentially expressed under abiotic and biotic stresses highlights their potential role in stress resistance. In summary, this study has developed a platform that will help in the understanding of tncRNAs and their involvement in growth, development, and response to various stresses. The workflow, software package, and results are freely available at http://nipgr.ac.in/tncRNA.

General Principles for the Detection of Modified Nucleotides in RNA by Specific Reagents

Epitranscriptomics heavily rely on chemical reagents for the detection, quantification, and localization of modified nucleotides in transcriptomes. Recent years have seen a surge in mapping methods that use innovative and rediscovered organic chemistry in high throughput approaches. While this has brought about a leap of progress in this young field, it has also become clear that the different chemistries feature variegated specificity and selectivity. The associated error rates, e.g., in terms of false positives and false negatives, are in large part inherent to the chemistry employed. This means that even assuming technically perfect execution, the interpretation of mapping results issuing from the application of such chemistries are limited by intrinsic features of chemical reactivity. An important but often ignored fact is that the huge stochiometric excess of unmodified over-modified nucleotides is not inert to any of the reagents employed. Consequently, any reaction aimed at chemical discrimination of modified versus unmodified nucleotides has optimal conditions for selectivity that are ultimately anchored in relative reaction rates, whose ratio imposes intrinsic limits to selectivity. Here chemical reactivities of canonical and modified ribonucleosides are revisited as a basis for an understanding of the limits of selectivity achievable with chemical methods.

Repurposing RNA sequencing for discovery of RNA modifications in clinical cohorts

The study of RNA modifications in large clinical cohorts can reveal relationships between the epitranscriptome and human diseases, although this is especially challenging. We developed ModTect (https://github.com/ktan8/ModTect), a statistical framework to identify RNA modifications de novo by standard RNA-sequencing with deletion and mis-incorporation signals. We show that ModTect can identify both known (N 1-methyladenosine) and previously unknown types of mRNA modifications (N 2,N 2-dimethylguanosine) at nucleotide-resolution. Applying ModTect to 11,371 patient samples and 934 cell lines across 33 cancer types, we show that the epitranscriptome was dysregulated in patients across multiple cancer types and was additionally associated with cancer progression and survival outcomes. Some types of RNA modification were also more disrupted than others in patients with cancer. Moreover, RNA modifications contribute to multiple types of RNA-DNA sequence differences, which unexpectedly escape detection by Sanger sequencing. ModTect can thus be used to discover associations between RNA modifications and clinical outcomes in patient cohorts.

tRNA-derived fragments as New Hallmarks of Aging and Age-related Diseases

tRNA-derived fragments (tRFs), which are non-coding RNAs produced via tRNA cleavage with lengths of 14 to 50 nucleotides, originate from precursor tRNAs or mature tRNAs and exist in a wide range of organisms. tRFs are produced not by random fracture of tRNAs but by specific mechanisms. Considerable evidence shows that tRFs are detectable in model organisms of different ages and are associated with age-related diseases in humans, such as cancer and neurodegenerative diseases. In this literature review, the origin and classification of tRFs and the regulatory mechanisms of tRFs in aging and age-related diseases are summarized. We also describe the available tRF databases and research techniques and lay a foundation for the exploration of tRFs as biomarkers for the diagnosis and treatment of aging and age-related diseases.

A semi-quantitative pull-down assay to study tRNA substrate specificity of modification enzymes

A tRNA interacts with numerous proteins throughout its biogenesis and during translation, and a significant portion of these interacting proteins are involved in post-transcriptional modifications. While some of the modifying enzymes use relatively simple recognition elements for substrate recognition, many enzymes selectively modify a specific subset of tRNA species without obvious recognition rules. In this chapter we describe a semi-quantitative pull-down assay to study tRNA substrate specificity of modification enzymes, by using the yeast Saccharomyces cerevisiae m³C₃₂ methyltransferase Trm140 as an example. We also discuss some overall considerations for a successful pull-down experiment, with a focus on practical applications of the dissociation constant K_D between the protein and the tRNA and the off-rate.

Arrow pushing in RNA modification sequencing

Methods to accurately determine the location and abundance of RNA modifications are critical to understanding their functional role. In this review, we describe recent efforts in which chemical reactivity and next-generation sequencing have been integrated to detect modified nucleotides in RNA. For eleven exemplary modifications, we detail chemical, enzymatic, and metabolic labeling protocols that can be used to differentiate them from canonical nucleobases. By emphasizing the molecular rationale underlying these detection methods, our survey highlights new opportunities for chemistry to define the role of RNA modifications in disease.

Changes of the tRNA Modification Pattern during the Development of Dictyostelium discoideum

Dictyostelium discoideum is a social amoeba, which on starvation develops from a single-cell state to a multicellular fruiting body. This developmental process is accompanied by massive changes in gene expression, which also affect non-coding RNAs. Here, we investigate how tRNAs as key regulators of the translation process are affected by this transition. To this end, we used LOTTE-seq to sequence the tRNA pool of D. discoideum at different developmental time points and analyzed both tRNA composition and tRNA modification patterns. We developed a workflow for the specific detection of modifications from reverse transcriptase signatures in chemically untreated RNA-seq data at single-nucleotide resolution. It avoids the comparison of treated and untreated RNA-seq data using reverse transcription arrest patterns at nucleotides in the neighborhood of a putative modification site as internal control. We find that nucleotide modification sites in D. discoideum tRNAs largely conform to the modification patterns observed throughout the eukaroytes. However, there are also previously undescribed modification sites. We observe substantial dynamic changes of both expression levels and modification patterns of certain tRNA types during fruiting body development. Beyond the specific application to D. discoideum our results demonstrate that the developmental variability of tRNA expression and modification can be traced efficiently with LOTTE-seq.

Recent advances in functional annotation and prediction of the epitranscriptome

RNA modifications, in particular N⁶-methyladenosine (m⁶A), participate in every stages of RNA metabolism and play diverse roles in essential biological processes and disease pathogenesis. Thanks to the advances in sequencing technology, tens of thousands of RNA modification sites can be identified in a typical high-throughput experiment; however, it remains a major challenge to decipher the functional relevance of these sites, such as, affecting alternative splicing, regulation circuit in essential biological processes or association to diseases. As the focus of RNA epigenetics gradually shifts from site discovery to functional studies, we review here recent progress in functional annotation and prediction of RNA modification sites from a bioinformatics perspective. The review covers naïve annotation with associated biological events, e.g., single nucleotide polymorphism (SNP), RNA binding protein (RBP) and alternative splicing, prediction of key sites and their regulatory functions, inference of disease association, and mining the diagnosis and prognosis value of RNA modification regulators. We further discussed the limitations of existing approaches and some future perspectives.

Quantitative nucleotide resolution profiling of RNA cytidine acetylation by ac4C-seq

A prerequisite to defining the transcriptome-wide functions of RNA modifications is the ability to accurately determine their location. Here, we present N4-acetylcytidine (ac4C) sequencing (ac4C-seq), a protocol for the quantitative single-nucleotide resolution mapping of cytidine acetylation in RNA. This method exploits the kinetically facile chemical reaction of ac4C with sodium cyanoborohydride under acidic conditions to form a reduced nucleobase. RNA is then fragmented, ligated to an adapter at its 3' end and reverse transcribed to introduce a non-cognate nucleotide at reduced ac4C sites. After adapter ligation, library preparation and high-throughput sequencing, a bioinformatic pipeline enables identification of ac4C positions on the basis of the presence of C→T misincorporations in reduced samples but not in controls. Unlike antibody-based approaches, ac4C-seq identifies specific ac4C residues and reports on their level of modification. The ac4C-seq library preparation protocol can be completed in ~4 d for transcriptome-wide sequencing.

Nucleotide resolution profiling of m3C RNA modification by HAC-seq

Cellular RNAs are subject to a myriad of different chemical modifications that play important roles in controlling RNA expression and function. Dysregulation of certain RNA modifications, the so-called 'epitranscriptome', contributes to human disease. One limitation in studying the functional, physiological, and pathological roles of the epitranscriptome is the availability of methods for the precise mapping of individual RNA modifications throughout the transcriptome. 3-Methylcytidine (m3C) modification of certain tRNAs is well established and was also recently detected in mRNA. However, methods for the specific mapping of m3C throughout the transcriptome are lacking. Here, we developed a m3C-specific technique, Hydrazine-Aniline Cleavage sequencing (HAC-seq), to profile the m3C methylome at single-nucleotide resolution. We applied HAC-seq to analyze ribosomal RNA (rRNA)-depleted total RNAs in human cells. We found that tRNAs are the predominant m3C-modified RNA species, with 17 m3C modification sites on 11 cytoplasmic and 2 mitochondrial tRNA isoacceptors in MCF7 cells. We found no evidence for m3C-modification of mRNA or other non-coding RNAs at comparable levels to tRNAs in these cells. HAC-seq provides a novel method for the unbiased, transcriptome-wide identification of m3C RNA modification at single-nucleotide resolution, and could be widely applied to reveal the m3C methylome in different cells and tissues.

Instrumental analysis of RNA modifications

Organisms from all domains of life invest a substantial amount of energy for the introduction of RNA modifications into nearly all transcripts studied to date. Instrumental analysis of RNA can focus on the modified residues and reveal the function of these epitranscriptomic marks. Here, we will review recent advances and breakthroughs achieved by NMR spectroscopy, sequencing, and mass spectrometry of the epitranscriptome.

Analysis of RNA Modifications by Second- and Third-Generation Deep Sequencing: 2020 Update

The precise mapping and quantification of the numerous RNA modifications that are present in tRNAs, rRNAs, ncRNAs/miRNAs, and mRNAs remain a major challenge and a top priority of the epitranscriptomics field. After the keystone discoveries of massive m⁶A methylation in mRNAs, dozens of deep sequencing-based methods and protocols were proposed for the analysis of various RNA modifications, allowing us to considerably extend the list of detectable modified residues. Many of the currently used methods rely on the particular reverse transcription signatures left by RNA modifications in cDNA; these signatures may be naturally present or induced by an appropriate enzymatic or chemical treatment. The newest approaches also include labeling at RNA abasic sites that result from the selective removal of RNA modification or the enhanced cleavage of the RNA ribose-phosphate chain (perhaps also protection from cleavage), followed by specific adapter ligation. Classical affinity/immunoprecipitation-based protocols use either antibodies against modified RNA bases or proteins/enzymes, recognizing RNA modifications. In this survey, we review the most recent achievements in this highly dynamic field, including promising attempts to map RNA modifications by the direct single-molecule sequencing of RNA by nanopores.

Subcellular relocalization and nuclear redistribution of the RNA methyltransferases TRMT1 and TRMT1L upon neuronal activation

RNA modifications are dynamic chemical entities that expand the RNA lexicon and regulate RNA fate. The most abundant modification present in mRNAs, N6-methyladenosine (m⁶A), has been implicated in neurogenesis and memory formation. However, whether additional RNA modifications may be playing a role in neuronal functions and in response to environmental queues is largely unknown. Here we characterize the biochemical function and cellular dynamics of two human RNA methyltransferases previously associated with neurological dysfunction, TRMT1 and its homolog, TRMT1-like (TRMT1L). Using a combination of next-generation sequencing, LC-MS/MS, patient-derived cell lines and knockout mouse models, we confirm the previously reported dimethylguanosine (m^2,2G) activity of TRMT1 in tRNAs, as well as reveal that TRMT1L, whose activity was unknown, is responsible for methylating a subset of cytosolic tRNA^Ala(AGC) isodecoders at position 26. Using a cellular in vitro model that mimics neuronal activation and long term potentiation, we find that both TRMT1 and TRMT1L change their subcellular localization upon neuronal activation. Specifically, we observe a major subcellular relocalization from mitochondria and other cytoplasmic domains (TRMT1) and nucleoli (TRMT1L) to different small punctate compartments in the nucleus, which are as yet uncharacterized. This phenomenon does not occur upon heat shock, suggesting that the relocalization of TRMT1 and TRMT1L is not a general reaction to stress, but rather a specific response to neuronal activation. Our results suggest that subcellular relocalization of RNA modification enzymes may play a role in neuronal plasticity and transmission of information, presumably by addressing new targets.

High-resolution quantitative profiling of tRNA abundance and modification status in eukaryotes by mim-tRNAseq

Measurements of cellular tRNA abundance are hampered by pervasive blocks to cDNA synthesis at modified nucleosides and the extensive similarity among tRNA genes. We overcome these limitations with modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which combines a workflow for full-length cDNA library construction from endogenously modified tRNA with a comprehensive and user-friendly computational analysis toolkit. Our method accurately captures tRNA abundance and modification status in yeast, fly, and human cells and is applicable to any organism with a known genome. We applied mim-tRNAseq to discover a dramatic heterogeneity of tRNA isodecoder pools among diverse human cell lines and a surprising interdependence of modifications at distinct sites within the same tRNA transcript.

•

mim-tRNAseq overcomes experimental and computational hurdles to tRNA quantitation

•

mim-tRNAseq includes a comprehensive computational toolkit for tRNA read analysis

•

tRNA abundance, aminoacylation, and modification status quantified in one reaction

•

mim-tRNAseq reveals an interdependence of modifications at distinct tRNA positions