Prediction of m6A and m5C at single-molecule resolution reveals a transcriptome-wide co-occurrence of RNA modifications.

The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytosine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI's capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.

Direct Analysis of HIV mRNA m6A Methylation by Nanopore Sequencing.

The post-transcriptional processing and chemical modification of HIV RNA are understudied aspects of HIV virology, primarily due to the limited ability to accurately map and quantify RNA modifications. Modification-specific antibodies or modification-sensitive endonucleases coupled with short-read RNA sequencing technologies have allowed for low-resolution or limited mapping of important regulatory modifications of HIV RNA such as N6-methyladenosine (m6A). However, a high-resolution map of where these sites occur on HIV transcripts is needed for detailed mechanistic understanding. This has recently become possible with new sequencing technologies. Here, we describe the direct RNA sequencing of HIV transcripts using an Oxford Nanopore Technologies sequencer and the use of this technique to map m6A at near single nucleotide resolution. This technology also provides the ability to identify splice variants with long RNA reads and thus, can provide high-resolution RNA modification maps that distinguish between overlapping splice variants. The protocols outlined here for m6A also provide a powerful paradigm for studying any other RNA modifications that can be detected on the nanopore platform.

Identifying Individual Pseudouridine (Ψ) Sites Across Transcripts from HIV-1 Infected Cells.

The identification of RNA modifications at single nucleotide resolution has become an emerging area of interest within biology and specifically among virologists seeking to ascertain how this untapped area of RNA regulation may be altered or hijacked upon viral infection. Herein, we describe a straightforward biochemical approach modified from two original published Ψ mapping protocols, BID-seq and PRAISE, to specifically identify pseudouridine modifications on mRNA transcripts from an HIV-1 infected T cell line. This protocol could readily be adapted for other viral infected cell types and additionally for populations of purified virions from infected cells.

Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing.

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.

RNA m5C methylation modification: a potential therapeutic target for SARS-CoV-2-associated myocarditis.

The Corona Virus Disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has quickly spread worldwide and resulted in significant morbidity and mortality. Although most infections are mild, some patients can also develop severe and fatal myocarditis. In eukaryotic RNAs, 5-methylcytosine (m5C) is a common kind of post-transcriptional modification, which is involved in regulating various biological processes (such as RNA export, translation, and stability maintenance). With the rapid development of m5C modification detection technology, studies related to viral m5C modification are ever-increasing. These studies have revealed that m5C modification plays an important role in various stages of viral replication, including transcription and translation. According to recent studies, m5C methylation modification can regulate SARS-CoV-2 infection by modulating innate immune signaling pathways. However, the specific role of m5C modification in SARS-CoV-2-induced myocarditis remains unclear. Therefore, this review aims to provide insights into the molecular mechanisms of m5C methylation in SARS-CoV-2 infection. Moreover, the regulatory role of NSUN2 in viral infection and host innate immune response was also highlighted. This review may provide new directions for developing therapeutic strategies for SARS-CoV-2-associated myocarditis.

A role for a Trypanosoma brucei cytosine RNA methyltransferase homolog in ribosomal RNA processing.

In Trypanosoma brucei, gene expression is primarily regulated posttranscriptionally making RNA metabolism critical. T. brucei has an epitranscriptome containing modified RNA bases. Yet, the identity of the enzymes catalyzing modified RNA base addition and the functions of the enzymes and modifications remain unclear. Homology searches indicate the presence of numerous T. brucei cytosine RNA methyltransferase homologs. One such homolog, TbNop2 was studied in detail. TbNop2 contains the six highly conserved motifs found in cytosine RNA methyltransferases and is evolutionarily related to the Nop2 protein family required for rRNA modification and processing. RNAi experiments targeting TbNop2 resulted in reduced levels of TbNop2 RNA and protein, and a cessation of parasite growth. Next generation sequencing of bisulfite-treated RNA (BS-seq) detected the presence of two methylation sites in the large rRNA; yet TbNop2 RNAi did not result in a significant reduction of methylation. However, TbNop2 RNAi resulted in the retention of 28S internal transcribed spacer RNAs, indicating a role for TbNop2 in rRNA processing.

Regulation by the RNA-binding protein Unkempt at its effector interface.

How RNA-binding proteins (RBPs) convey regulatory instructions to the core effectors of RNA processing is unclear. Here, we document the existence and functions of a multivalent RBP-effector interface. We show that the effector interface of a conserved RBP with an essential role in metazoan development, Unkempt, is mediated by a novel type of 'dual-purpose' peptide motifs that can contact two different surfaces of interacting proteins. Unexpectedly, we find that the multivalent contacts do not merely serve effector recruitment but are required for the accuracy of RNA recognition by Unkempt. Systems analyses reveal that multivalent RBP-effector contacts can repurpose the principal activity of an effector for a different function, as we demonstrate for the reuse of the central eukaryotic mRNA decay factor CCR4-NOT in translational control. Our study establishes the molecular assembly and functional principles of an RBP-effector interface.

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

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

Dnttip2 is essential for 18S rRNA processing and digestive organ development in zebrafish.

Dnttip2 is one of the components of the small subunit (SSU) processome. In yeast, depletion of dnttip2 leads to an inefficient processing of pre-rRNA and a decrease in synthesis of the mature 18S rRNA. However, the biological roles of Dnttip2 in higher organisms are poorly defined. In this study, we demonstrate that dnttip2 is a maternal gene in zebrafish. Depletion of Dnttip2 leads to embryonic lethal with severe digestive organs hypoplasia. The loss of function of Dnttip2 also leads to partial defects in cleavage at the A0-site and E-site during 18S rRNA processing. In conclusion, Dnttip2 is essential for 18S rRNA processing and digestive organ development in zebrafish.

The Post-Transcriptional Regulatory Element of Hepatitis B Virus: From Discovery to Therapy.

The post-transcriptional regulatory element (PRE) is present in all HBV mRNAs and plays a major role in their stability, nuclear export, and enhancement of viral gene expression. Understanding PRE's structure, function, and mode of action is essential to leverage its potential as a therapeutic target. A wide range of PRE-based reagents and tools have been developed and assessed in preclinical and clinical settings for therapeutic and biotechnology applications. This manuscript aims to provide a systematic review of the characteristics and mechanism of action of PRE, as well as elucidating its current applications in basic and clinical research. Finally, we discuss the promising opportunities that PRE may provide to antiviral development, viral biology, and potentially beyond.

Role of Rmd9p in 3'-end processing of mitochondrial 15S rRNA in Saccharomyces cerevisiae.

Ribosome biogenesis, involving processing/assembly of rRNAs and r-proteins is a vital process. In Saccharomyces cerevisiae mitochondria, ribosomal small subunit comprises 15S rRNA (15S). While the 15S 5'-end processing uses Ccm1p and Pet127p, the mechanisms of the 3'-end processing remain unclear. We reveal involvement of Rmd9p in safeguarding/processing 15S 3'-end. Rmd9p deficiency results in a cleavage at a position 183 nucleotides upstream of 15S 3'-end, and in the loss of the 3'-minor domain. Rmd9p binds to the sequences in the 3'-end region of 15S, and a genetic interaction between rmd9 and dss1 indicates that Rmd9p regulates/limits mtEXO activity during the 3'-end spacer processing.

RNA m6A modification, signals for degradation or stabilisation?

The RNA modification N6-methyladenosine (m6A) is conserved across eukaryotes, and profoundly influences RNA metabolism, including regulating RNA stability. METTL3 and METTL14, together with several accessory components, form a 'writer' complex catalysing m6A modification. Conversely, FTO and ALKBH5 function as demethylases, rendering m6A dynamic. Key to understanding the functional significance of m6A is its 'reader' proteins, exemplified by YTH-domain-containing proteins (YTHDFs) canonical reader and insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) non-canonical reader. These proteins play a crucial role in determining RNA stability: YTHDFs mainly promote mRNA degradation through different cytoplasmic pathways, whereas IGF2BPs function to maintain mRNA stability. Additionally, YTHDC1 functions within the nucleus to degrade or protect certain m6A-containing RNAs, and other non-canonical readers also contribute to RNA stability regulation. Notably, m6A regulates retrotransposon LINE1 RNA stability and/or transcription via multiple mechanisms. However, conflicting observations underscore the complexities underlying m6A's regulation of RNA stability depending upon the RNA sequence/structure context, developmental stage, and/or cellular environment. Understanding the interplay between m6A and other RNA regulatory elements is pivotal in deciphering the multifaceted roles m6A plays in RNA stability regulation and broader cellular biology.

txtools: an R package facilitating analysis of RNA modifications, structures, and interactions.

We present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. txtools' main inputs are BAM files and a transcriptome annotation, and the main output is a table, capturing mismatches, deletions, and the number of reads beginning and ending at each nucleotide in the transcriptomic space. txtools further facilitates downstream visualization and analyses. We showcase, using examples from the epitranscriptomic field, how a few calls to txtools functions can yield insightful and ready-to-publish results. txtools is of broad utility also in the context of structural mapping and RNA:protein interaction mapping. By providing a simple and intuitive framework, we believe that txtools will be a useful and convenient tool and pave the path for future discovery. txtools is available for installation from its GitHub repository at https://github.com/AngelCampos/txtools.

Non-canonical RNA substrates of Drosha lack many of the conserved features found in primary microRNA stem-loops.

The RNase III enzyme Drosha has a central role in microRNA (miRNA) biogenesis, where it is required to release the stem-loop intermediate from primary (pri)-miRNA transcripts. However, it can also cleave stem-loops embedded within messenger (m)RNAs. This destabilizes the mRNA causing target gene repression and appears to occur primarily in stem cells. While pri-miRNA stem-loops have been extensively studied, such non-canonical substrates of Drosha have yet to be characterized in detail. In this study, we employed high-throughput sequencing to capture all polyA-tailed RNAs that are cleaved by Drosha in mouse embryonic stem cells (ESCs) and compared the features of non-canonical versus miRNA stem-loop substrates. mRNA substrates are less efficiently processed than miRNA stem-loops. Sequence and structural analyses revealed that these mRNA substrates are also less stable and more likely to fold into alternative structures than miRNA stem-loops. Moreover, they lack the sequence and structural motifs found in miRNA stem-loops that are required for precise cleavage. Notably, we discovered a non-canonical Drosha substrate that is cleaved in an inverse manner, which is a process that is normally inhibited by features in miRNA stem-loops. Our study thus provides valuable insights into the recognition of non-canonical targets by Drosha.

Structural atlas of human primary microRNAs generated by SHAPE-MaP.

MicroRNA (miRNA) maturation is critically dependent on structural features of primary transcripts (pri-miRNAs). However, the scarcity of determined pri-miRNA structures has limited our understanding of miRNA maturation. Here, we employed selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), a high-throughput RNA structure probing method, to unravel the secondary structures of 476 high-confidence human pri-miRNAs. Our SHAPE-based structures diverge substantially from those inferred solely from computation, particularly in the apical loop and basal segments, underlining the need for experimental data in RNA structure prediction. By comparing the structures with high-throughput processing data, we determined the optimal structural features of pri-miRNAs. The sequence determinants are influenced substantially by their structural contexts. Moreover, we identified an element termed the bulged GWG motif (bGWG) with a 3' bulge in the lower stem, which promotes processing. Our structure-function mapping better annotates the determinants of pri-miRNA processing and offers practical implications for designing small hairpin RNAs and predicting the impacts of miRNA mutations.

m6A-TCPred: a web server to predict tissue-conserved human m6A sites using machine learning approach.

BACKGROUND: N6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotic cells that plays a crucial role in regulating various biological processes, and dysregulation of m6A status is involved in multiple human diseases including cancer contexts. A number of prediction frameworks have been proposed for high-accuracy identification of putative m6A sites, however, none have targeted for direct prediction of tissue-conserved m6A modified residues from non-conserved ones at base-resolution level. RESULTS: We report here m6A-TCPred, a computational tool for predicting tissue-conserved m6A residues using m6A profiling data from 23 human tissues. By taking advantage of the traditional sequence-based characteristics and additional genome-derived information, m6A-TCPred successfully captured distinct patterns between potentially tissue-conserved m6A modifications and non-conserved ones, with an average AUROC of 0.871 and 0.879 tested on cross-validation and independent datasets, respectively. CONCLUSION: Our results have been integrated into an online platform: a database holding 268,115 high confidence m6A sites with their conserved information across 23 human tissues; and a web server to predict the conserved status of user-provided m6A collections. The web interface of m6A-TCPred is freely accessible at: www.rnamd.org/m6ATCPred .

BiPSTP: Sequence feature encoding method for identifying different RNA modifications with bidirectional position-specific trinucleotides propensities.

RNA modification, a posttranscriptional regulatory mechanism, significantly influences RNA biogenesis and function. The accurate identification of modification sites is paramount for investigating their biological implications. Methods for encoding RNA sequence into numerical data play a crucial role in developing robust models for predicting modification sites. However, existing techniques suffer from limitations, including inadequate information representation, challenges in effectively integrating positional and sequential information, and the generation of irrelevant or redundant features when combining multiple approaches. These deficiencies hinder the effectiveness of machine learning models in addressing the performance challenges associated with predicting RNA modification sites. Here, we introduce a novel RNA sequence feature representation method, named BiPSTP, which utilizes bidirectional trinucleotide position-specific propensities. We employ the parameter ξ to denote the interval between the current nucleotide and its adjacent forward or backward dinucleotide, enabling the extraction of positional and sequential information from RNA sequences. Leveraging the BiPSTP method, we have developed the prediction model mRNAPred using support vector machine classifier to identify multiple types of RNA modification sites. We evaluate the performance of our BiPSTP method and mRNAPred model across 12 distinct RNA modification types. Our experimental results demonstrate the superiority of the mRNAPred model compared to state-of-art models in the domain of RNA modification sites identification. Importantly, our BiPSTP method enhances the robustness and generalization performance of prediction models. Notably, it can be applied to feature extraction from DNA sequences to predict other biological modification sites.

Beyond the Anticodon: tRNA Core Modifications and Their Impact on Structure, Translation and Stress Adaptation.

Transfer RNAs (tRNAs) are heavily decorated with post-transcriptional chemical modifications. Approximately 100 different modifications have been identified in tRNAs, and each tRNA typically contains 5-15 modifications that are incorporated at specific sites along the tRNA sequence. These modifications may be classified into two groups according to their position in the three-dimensional tRNA structure, i.e., modifications in the tRNA core and modifications in the anticodon-loop (ACL) region. Since many modified nucleotides in the tRNA core are involved in the formation of tertiary interactions implicated in tRNA folding, these modifications are key to tRNA stability and resistance to RNA decay pathways. In comparison to the extensively studied ACL modifications, tRNA core modifications have generally received less attention, although they have been shown to play important roles beyond tRNA stability. Here, we review and place in perspective selected data on tRNA core modifications. We present their impact on tRNA structure and stability and report how these changes manifest themselves at the functional level in translation, fitness and stress adaptation.

An Overview of Current Detection Methods for RNA Methylation.

Epitranscriptomic mechanisms, which constitute an important layer in post-transcriptional gene regulation, are involved in numerous cellular processes under health and disease such as stem cell development or cancer. Among various such mechanisms, RNA methylation is considered to have vital roles in eukaryotes primarily due to its dynamic and reversible nature. There are numerous RNA methylations that include, but are not limited to, 2'-O-dimethyladenosine (m6Am), N7-methylguanosine (m7G), N6-methyladenosine (m6A) and N1-methyladenosine (m1A). These biochemical modifications modulate the fate of RNA by affecting the processes such as translation, target site determination, RNA processing, polyadenylation, splicing, structure, editing and stability. Thus, it is highly important to quantitatively measure the changes in RNA methylation marks to gain insight into cellular processes under health and disease. Although there are complicating challenges in identifying certain methylation marks genome wide, various methods have been developed recently to facilitate the quantitative measurement of methylated RNAs. To this end, the detection methods for RNA methylation can be classified in five categories such as antibody-based, digestion-based, ligation-based, hybridization-based or direct RNA-based methods. In this review, we have aimed to summarize our current understanding of the detection methods for RNA methylation, highlighting their advantages and disadvantages, along with the current challenges in the field.

RNA processing modification mediated subtypes illustrate the distinctive features of tumor microenvironment in hepatocellular carcinoma.

Multiple transcript isoforms of genes can be formed by processing and modifying the 5' and 3' ends of RNA. Herein, the aim of this study is to uncover the characteristics of RNA processing modification (RPM) in hepatocellular carcinoma (HCC), and to identify novel biomarkers and potential targets for treatment. Firstly, integrated bioinformatics analysis was carried out to identify risk prognostic RPM regulators (RPMRs). Then, we used these RPMRs to identify subtypes of HCC and explore differences in immune microenvironment and cellular function improvement pathways between the sub-types. Finally, we used the principal component analysis algorithms to estimate RPMscore, which were applied to 5 cohorts. Lower RPMscore among patients correlated with a declined survival rate, increased immune infiltration, and raised expression of immune checkpoints, aligning with the "immunity tidal model theory". The RPMscore exhibited robust, which was validated in multiple datasets. Mechanistically, low RPMscore can create an immunosuppressive microenvironment in HCC by manipulating tumor-associated macrophages. Preclinically, patients with high RPMscore might benefit from immunotherapy. The RPMscore is helpful in clustering HCC patients with distinct prognosis and immunotherapy. Our RPMscore model can help clinicians to select personalized therapy for HCC patients, and RPMscore may act a part in the development of HCC.