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Chemical and enzymatic properties of 2′-O-methylated RNA chains (a) Internal 2′-Omethylation increases the resistance of RNA to nucleolytic cleavage at alkaline conditions; (b) resistance of 3′-terminal 2′-O-methylated residues to periodate (IO4 − ) oxidation; (c) RNA ligase and polyA-polymerase activities are affected at the 2′-O-methylated RNA 3′-terminal residues.
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Ribose 2′-O-methylation is certainly one of the most common RNA modifications found in almost any type of cellular RNA. It decorates transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), small nuclear RNAs (snRNAs) (and most probably small nucleolar RNAs, snoRNAs), as well as regulatory RNAs like microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), and...
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... 2′-O-methylation (RNA 2′-O-methylation, Figure 1a,b), confers to the RNA polynucleotide chain particular physico-chemical properties and specific reactivity, which differ considerably from unmodified RNA. Most of these changes are now exploited for specific detection of ribose 2′-O-methylation. ...
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... of all, the presence of a methyl (-CH3) group at the 2′-OH of the ribose preferentially stabilizes 3′-endo ribose conformation, typical for nucleotides in A-type RNA chain [2][3][4][5][6]. Secondly, methylation of the ribose 2′-OH almost completely abolishes the nucleophilic property of the 2′-OH oxygen atom, leading to a greatly increased resistance of the 3′-adjacent phosphodiester bond to alkaline hydrolysis (Figure 1a), as well as to nuclease cleavage (RNase T2 and RNase H, for example). Thirdly, when a 2′-O-Me is present at the 3′-terminal nucleotide, the methyl group prevents the coordination with bidentate oxidative agents, such as periodate (IO4 − ) ion, and thus protects the terminal ribose [7] (Figure 1b). ...
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... methylation of the ribose 2′-OH almost completely abolishes the nucleophilic property of the 2′-OH oxygen atom, leading to a greatly increased resistance of the 3′-adjacent phosphodiester bond to alkaline hydrolysis (Figure 1a), as well as to nuclease cleavage (RNase T2 and RNase H, for example). Thirdly, when a 2′-O-Me is present at the 3′-terminal nucleotide, the methyl group prevents the coordination with bidentate oxidative agents, such as periodate (IO4 − ) ion, and thus protects the terminal ribose [7] (Figure 1b). Such 3′-terminal 2′-O-methylation also negatively affects the ligation efficiency by RNA ligase [8,9] and the 3′-end activity of polyA-polymerase [10,11] (Figure 1c). ...
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... when a 2′-O-Me is present at the 3′-terminal nucleotide, the methyl group prevents the coordination with bidentate oxidative agents, such as periodate (IO4 − ) ion, and thus protects the terminal ribose [7] (Figure 1b). Such 3′-terminal 2′-O-methylation also negatively affects the ligation efficiency by RNA ligase [8,9] and the 3′-end activity of polyA-polymerase [10,11] (Figure 1c). ...
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... examples of analytical strategies include isolation and analysis by combination of high- performance liquid chromatography with mass spectrometry (HPLC/MS) of mung bean or RNase T1 fragments of rRNA, an approach which allowed to finalize the modification profile of yeast Saccharomyces cerevisiae and human ribosome [30][31][32][33]. Even if the analyses were done using different cell lines and certainly different conditions of culture, modern mass-spectrometry approaches [32,33] demonstrate an excellent correlation with the quantitative methylation data obtained by various RiboMethSeq protocols (R 2 > 0.98, see supplementary Figure S1). ...
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... is first randomly fragmented by a nuclease (benzonase for RibOxi-Seq or fragmentation reagent followed by end repair for Nm-Seq) leaving 5′-phosphates and 3′-OH extremities and these RNA fragments are subjected to periodate oxidation (Figure 4c). Protected 2′-O-Me 3′-termini are quite resistant to periodate, but all unmodified cis-diol riboses are destroyed and converted to dialdehydes (see Figure 1b). These oxidized riboses are not anymore competent to 3′-adapter ligation and thus, they were excluded from the generated library, allowing enrichment of only 2′-O-methylated extremities in the obtained sequencing reads. ...
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High-throughput RNA-seq has revolutionized the process of small RNA (sRNA) discovery, leading to a rapid expansion of sRNA categories. In addition to the previously well-characterized sRNAs such as microRNAs (miRNAs), Piwi-interacting RNA (piRNAs), and small nucleolar RNA (snoRNAs), recent emerging studies have spotlighted on tRNA-derived sRNAs (ts...
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... However, each of these methods has exhibited significant limitations. For example, RiboMethseq [11,12] was introduced as a sequencing-based method for mapping and quantifying Nm modifications based on a simple chemical principle -the considerable difference in nucleophilicity between a 2′-OH and a 2′-O-Me. This method uses a proprietary ligation protocol for direct ligation to 5′-OH and 3′-P ends, followed by alkaline fragmentation to prepare RNA for sequencing. ...
2´-O-methylation (Nm) is one of the most abundant modifications found in both mRNAs and noncoding RNAs. It contributes to many biological processes, such as the normal functioning of tRNA, the protection of mRNA against degradation by the decapping and exoribonuclease (DXO) protein, and the biogenesis and specificity of rRNA. Recent advancements in single-molecule sequencing techniques for long read RNA sequencing data offered by Oxford Nanopore technologies have enabled the direct detection of RNA modifications from sequencing data. In this study, we propose a bio-computational framework, Nm-Nano, for predicting the presence of Nm sites in direct RNA sequencing data generated from two human cell lines. The Nm-Nano framework integrates two supervised machine learning (ML) models for predicting Nm sites: Extreme Gradient Boosting (XGBoost) and Random Forest (RF) with K-mer embedding. Evaluation on benchmark datasets from direct RNA sequecing of HeLa and HEK293 cell lines, demonstrates high accuracy (99% with XGBoost and 92% with RF) in identifying Nm sites. Deploying Nm-Nano on HeLa and HEK293 cell lines reveals genes that are frequently modified with Nm. In HeLa cell lines, 125 genes are identified as frequently Nm-modified, showing enrichment in 30 ontologies related to immune response and cellular processes. In HEK293 cell lines, 61 genes are identified as frequently Nm-modified, with enrichment in processes like glycolysis and protein localization. These findings underscore the diverse regulatory roles of Nm modifications in metabolic pathways, protein degradation, and cellular processes. The source code of Nm-Nano can be freely accessed at https://github.com/Janga-Lab/Nm-Nano.
... More recently, several reports have described internal Nm modifications in mRNA, with evidence of physiologic relevance despite seemingly low stoichiometry of modification (Dai et al. 2017;Tang et al. 2023; Bartoli et al. 2018;Elliott and Holley 2021;Leighton et al. 2022). However, the accurate mapping of internal Nm in mRNA remains a challenge, and the true abundance, distribution, and physiologic relevance of internal Nm in mRNA remain controversial (Motorin and Marchand 2018). The stoichiometry of Nm in noncoding RNAs varies in different physiologic and pathologic states, and the modulation of Nm levels has functional consequences in diverse processes including translation, splicing, and innate immunity (Monaco et al. 2018;Bohnsack and Sloan 2018;Hyde and Diamond 2015). ...
... Of the high-throughput methods for Nm mapping, only RiboMeth-seq has been shown to quantitatively measure absolute Nm fraction, yet it is impractical for application to mRNA due to the high depth of sequencing required (Motorin and Marchand et al. 2016). For Nm sites in rRNA, the stoichiometry of Nm determined by RiboMeth-seq correlates well with the Nm stoichiometry measured by liquid chromatography (LC) with tandem mass spectrometry (MS) (Motorin and Marchand 2018;Marchand et al. 2016;Taoka et al. 2018). 2OMe-seq, Nm-Mut-seq, and NJU-seq can capture relative but not absolute Nm fraction with the use of spiked-in in vitro transcribed RNA controls (Incarnato et al. 2017;Chen et al. 2023;Tang et al. 2023). ...
... Low-throughput methods can also measure Nm fraction: RT-based methods such as RTL-P (RT at low dNTP concentrations followed by PCR) provide a semiquantitative measure of Nm fraction (Dong et al. 2012b;Elliott and Holley 2021), while Nm-VAQ (Nm validation and absolute quantification), which uses site-specific chimeric RNA/DNA probes to detect resistance to RNase H cleavage, is reported to allow absolute quantification of Nm stoichiometry . The combination of LC and tandem MS (LC-MS/MS) can also be used to quantitatively measure Nm stoichiometry (Motorin and Marchand 2018). Digestion of RNA into single nucleosides or cap dinucleotides allows for the measurement of Nm content by LC-MS/MS (Elliott 2004;Dai et al. 2017;Wang et al. 2019), while analysis of intact or partially digested RNA by LC-MS/MS has enabled the site-specific mapping and quantification of Nm in rRNA and tRNA (Taoka et al. 2016;Wein et al. 2020). ...
RNA 2′- O -methylation (Nm) is highly abundant in noncoding RNAs including ribosomal RNA (rRNA), transfer RNA (tRNA), and small nuclear RNA (snRNA), and occurs in the 5′ cap of virtually all messenger RNAs (mRNAs) in higher eukaryotes. More recently, Nm has also been reported to occur at internal sites in mRNA. High-throughput methods have been developed for the transcriptome-wide detection of Nm. However, these methods have mostly been applied to abundant RNAs such as rRNA, and the validity of the internal mRNA Nm sites detected with these approaches remains controversial. Nonetheless, Nm in both coding and noncoding RNAs has been demonstrated to impact cellular processes, including translation and splicing. In addition, Nm modifications at the 5′ cap and possibly at internal sites in mRNA serve to prevent the binding of nucleic acid sensors, thus preventing the activation of the innate immune response by self-mRNAs. Finally, Nm has been implicated in a variety of diseases including cancer, cardiovascular diseases, and neurologic syndromes. In this review, we discuss current challenges in determining the distribution, regulation, function, and disease relevance of Nm, as well as potential future directions for the field.
... RiboMethSeq protocol allowed us to map 2′-O-methylations by assessing their protection against alkaline cleavage (Marchand et al., 2016(Marchand et al., , 2017. To further enhance our analysis, we also extracted reverse transcriptase (RT) misincorporation signatures at RT-arresting nucleotides (Motorin and Marchand, 2018;Werner et al., 2020). As part of the RiboMethSeq tRNA analysis, total RNA from B. henselae was fragmented under alkaline conditions, followed by library preparation and sequencing (Marchand et al., 2017). ...
Transfer RNA (tRNA) modifications play a crucial role in maintaining translational fidelity and efficiency, and they may function as regulatory elements in stress response and virulence. Despite their pivotal roles, a comprehensive mapping of tRNA modifications and their associated synthesis genes is still limited, with a predominant focus on free-living bacteria. In this study, we employed a multidisciplinary approach, incorporating comparative genomics, mass spectrometry, and next-generation sequencing, to predict the set of tRNA modification genes responsible for tRNA maturation in two intracellular pathogens—Bartonella henselae Houston I and Bartonella quintana Toulouse, which are causative agents of cat-scratch disease and trench fever, respectively. This analysis presented challenges, particularly because of host RNA contamination, which served as a potential source of error. However, our approach predicted 26 genes responsible for synthesizing 23 distinct tRNA modifications in B. henselae and 22 genes associated with 23 modifications in B. quintana. Notably, akin to other intracellular and symbiotic bacteria, both Bartonella species have undergone substantial reductions in tRNA modification genes, mostly by simplifying the hypermodifications present at positions 34 and 37. Bartonella quintana exhibited the additional loss of four modifications and these were linked to examples of gene decay, providing snapshots of reductive evolution.
... highthroughput datasets consist of -seq ( 18 ), CeU-seq ( 19 ), Pseudo-seq ( 20 ) and PSI-seq ( 21 ), BID-seq ( 22 ) and PRAISE ( 23 ). 2 -O -Me high-throughput datasets include Nm-seq, RiboMeth-seq, RibOxi-seq and 2OMe-seq ( 24 ). ac 4 C highthroughput datasets include ac4C-seq ( 25 ) and acRIP-seq ( 26 ). ...
Although over 170 chemical modifications have been identified, their prevalence, mechanism and function remain largely unknown. To enable integrated analysis of diverse RNA modification profiles, we have developed RMBase v3.0 (http:////bioinformaticsscience.cn//rmbase//), a comprehensive platform consisting of eight modules. These modules facilitate the exploration of transcriptome-wide landscape, biogenesis, interactome and functions of RNA modifications. By mining thousands of epitranscriptome datasets with novel pipelines, the ‘RNA Modifications’ module reveals the map of 73 RNA modifications of 62 species. the ‘Genes’ module allows to retrieve RNA modification profiles and clusters by gene and transcript. The ‘Mechanisms’ module explores 23 382 enzyme-catalyzed or snoRNA-guided modified sites to elucidate their biogenesis mechanisms. The ‘Co-localization’ module systematically formulates potential correlations between 14 histone modifications and 6 RNA modifications in various cell-lines. The ‘RMP’ module investigates the differential expression profiles of 146 RNA-modifying proteins (RMPs) in 18 types of cancers. The ‘Interactome’ integrates the interactional relationships between 73 RNA modifications with RBP binding events, miRNA targets and SNPs. The ‘Motif’ illuminates the enriched motifs for 11 types of RNA modifications identified from epitranscriptome datasets. The ‘Tools’ introduces a novel web-based ‘modGeneTool’ for annotating modifications. Overall, RMBase v3.0 provides various resources and tools for studying RNA modifications.
... Additionally, internal Nm modification of mRNAs could affect mRNAs' abundance and protein levels both in vitro and in vivo [34]. Nm modifications are present at the 3' termini of mature miRNAs, where they contributed to enhancing the stability of miRNAs [35][36][37]; however, the presence of Nm modifications on pri-miRNAs and their possible biological functions have not been reported. Here, we found that SNORD11B could regulate the expression of let-7family miRNAs. ...
Evidence indicates that small nucleolar RNAs (snoRNAs) participate in tumorigenesis and development and could be promising biomarkers for colorectal cancer (CRC). Here, we examine the profile of snoRNAs in CRC and find that expression of SNORD11B is increased in CRC tumor tissues and cell lines, with a significant positive correlation between SNORD11B expression and that of its host gene NOP58. SNORD11B promotes CRC cell proliferation and invasion and inhibits apoptosis. Mechanistically, SNORD11B promotes the processing and maturation of 18 S ribosomal RNA (rRNA) by mediating 2'-O-methylated (Nm) modification on the G509 site of 18 S rRNA. Intriguingly, SNORD11B mediates Nm modification on the G225 site of MIRLET7A1HG (pri-let-7a) with a canonical motif, resulting in degradation of pri-let-7a, inhibition of DGCR8 binding, reduction in mature tumor suppressor gene let-7a-5p expression, and upregulation of downstream oncogene translation. SNORD11B performs comparably to CEA and CA199 in diagnosing CRC. High expression of SNORD11B is significantly correlated with a more advanced TNM stage and lymph node metastasis, which indicates poor prognosis.
... A prerequisite for the successful exploitation of the biomarker and therapeutic potential of ribosomal Nm is the availability of quick, accurate and affordable detection methodologies that can be performed under standard laboratory conditions. Several methods for Nm detection and quantification have been developed, for example, HPLC coupled with tandem mass spectrometry, primer extension preceded by endonuclease digestion and reverse transcription (RT) and, more recently, next-generation sequencing (NGS)-based methods, such as RiboMeth-Seq, 2 O-Me-Seq and Nm-seq [6,7]. However, these techniques are laborious and time-consuming, require specialized equipment or could require as much as 1000 ng of total RNA. ...
Ribose 2'O-methylation (Nm, ribomethylation) is the most abundant RNA modification present in rRNA. It has been shown that alterations in ribosomal 2'O-methylation at individual Nm sites likely reflect regulated cellular processes. Although several analytical approaches for Nm detection and profiling have been developed, a simple and affordable method for the screening and measurement of individual Nm sites in large numbers of tissue samples is required to examine their potential for clinical translation. Here, we describe a new quantitative reverse transcription PCR-based method that can sensitively assess ribomethylation levels at specific rRNA sites at single-nucleotide resolution in low input amounts of total RNA.
... In Drosophila melanogaster, Nm sites have only been predicted based on their complementarity to snoRNA ASEs, which themselves have been partly annotated based on motif predictions from genomic data (13). Various methods have been developed to detect and quantify Nm-modified sites (14,15). In this study, we use both RiboMethSeq, a nucleotide-resolution sequencing method that employs chemical probing coupled to next generation sequencing, and direct RNA nanopore sequencing (DRS), a longread sequencing technology that can sequence native RNA molecules, in which modified sites can be identified based on alterations in the current intensity when the RNA molecules are translocated through the nanopores (16). ...
During their maturation, ribosomal RNAs (rRNAs) are decorated by hundreds of chemical modifications that participate in proper folding of rRNA secondary structures and therefore in ribosomal function. Along with pseudouridine, methylation of the 2′-hydroxyl ribose moiety (Nm) is the most abundant modification of rRNAs. The majority of Nm modifications in eukaryotes are placed by Fibrillarin, a conserved methyltransferase belonging to a ribonucleoprotein complex guided by C/D box small nucleolar RNAs (C/D box snoRNAs). These modifications impact interactions between rRNAs, tRNAs and mRNAs, and some are known to fine tune translation rates and efficiency. In this study, we built the first comprehensive map of Nm sites in Drosophila melanogaster rRNAs using two complementary approaches (RiboMethSeq and Nanopore direct RNA sequencing) and identified their corresponding C/D box snoRNAs by whole-transcriptome sequencing. We de novo identified 61 Nm sites, from which 55 are supported by both sequencing methods, we validated the expression of 106 C/D box snoRNAs and we predicted new or alternative rRNA Nm targets for 31 of them. Comparison of methylation level upon different stresses show only slight but specific variations, indicating that this modification is relatively stable in D. melanogaster. This study paves the way to investigate the impact of snoRNA-mediated 2′-O-methylation on translation and proteostasis in a whole organism.
... In normal or high dNTP concentrations, reverse transcriptase cannot differentiate between modified and unmodified bases. But in the case of low dNTP concentrations enzyme falls off at a base prior to modified base resulting in two amplified products(Dong et al. 2012;Anonymous 2018;Elliott et al. 2019;Motorin and Marchand 2018). ...
Long-range ribonucleic acid (RNA)-RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA-RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2's mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps and shed light on the impact of mutations on the RRI space in viral genomes. Investigating the evolution of long-range RNA interactions and that of virus-host interactions can contribute to the understanding of new and emerging variants as well as aid in developing improved RNA therapeutics critical for combating future outbreaks.
... RNase T2 liberates the cap structures from mRNA as it cleaves all phosphodiester bonds in RNA except those after N m (ref. 12 ) (Fig. 1b). Thus, RNase T2 digestion of Cap1 mRNA releases m 7 G-ppp-N m -N, whereas the digestion of Cap2 mRNA releases m 7 G-ppp-N m -N m -N (Fig. 1b). ...
The mRNA cap structure is a major site of dynamic mRNA methylation. mRNA caps exist in either the Cap1 or Cap2 form, depending on the presence of 2′-O-methylation on the first transcribed nucleotide or both the first and second transcribed nucleotides, respectively1,2. However, the identity of Cap2-containing mRNAs and the function of Cap2 are unclear. Here we describe CLAM-Cap-seq, a method for transcriptome-wide mapping and quantification of Cap2. We find that unlike other epitranscriptomic modifications, Cap2 can occur on all mRNAs. Cap2 is formed through a slow continuous conversion of mRNAs from Cap1 to Cap2 as mRNAs age in the cytosol. As a result, Cap2 is enriched on long-lived mRNAs. Large increases in the abundance of Cap1 leads to activation of RIG-I, especially in conditions in which expression of RIG-I is increased. The methylation of Cap1 to Cap2 markedly reduces the ability of RNAs to bind to and activate RIG-I. The slow methylation rate of Cap2 allows Cap2 to accumulate on host mRNAs, yet ensures that low levels of Cap2 occur on newly expressed viral RNAs. Overall, these results reveal an immunostimulatory role for Cap1, and that Cap2 functions to reduce activation of the innate immune response.
... Box C/D snoRNAs (snoRD) recruit fibrillarin enzyme to cause 2′-O-methylation, while Box H/ACA snoRNAs (snoRA) recruit Dyskerin enzyme to pseudo-uridylate rRNA sites. These modifications affect ribosome interactions and are important for translation (16,(19)(20)(21)(22). ...
... To test the outcome of FXR1 regulation of snoRNA levels, we analyzed FXR1 KD or OE cells for 2′-O-methylation [by low deoxynucleotide triphosphate (dNTP) reverse transcription qPCR (RT-qPCR)] and pseudouridylation [after N-cyclohexyl-N′-(2-morpholinoethyl) carbodiimide metho-p-toluenesulfonate (CMC metho-p-toluene sulfonate) treatment followed by low dNTP RT-qPCR (21,23,24)] at the rRNA sites of specific snoRNAs that increase in G0 cells but decrease in G0 FXR1 KD cells (table S1, A to C). To globally examine rRNA modification changes, with or without FXR1, we enriched rRNA [devoid of poly(A) RNA and RNAs fractionated, to remove tRNAs and other RNAs less than 200 nucleotides (nt)] from FXR1 KD G0 and control shRNA G0 cells and subjected the nucleosides to liquid chromatography-mass spectrometry (LC-MS) analysis ( fig. ...
... FXR1 depletion and overexpression also alters U3 and U8 snoRNAs (Fig. 2B and fig. S2A) that cleave and process 47S Pol I precursor rRNA (16,(19)(20)(21)(22), which would lead to the observed alteration in mature 28S, 18S, and 5.8S rRNA levels ( Fig. 2A and fig. S2A). ...
Quiescent leukemic cells survive chemotherapy, with translation changes. Our data reveal that FXR1, a protein amplified in several aggressive cancers, is elevated in quiescent and chemo-treated leukemic cells and promotes chemosurvival. This suggests undiscovered roles for this RNA- and ribosome-associated protein in chemosurvival. We find that FXR1 depletion reduces translation, with altered rRNAs, snoRNAs, and ribosomal proteins (RPs). FXR1 regulates factors that promote transcription and processing of ribosomal genes and snoRNAs. Ribosome changes in FXR1-overexpressing cells, including RPLP0/uL10 levels, activate eIF2α kinases. Accordingly, phospho-eIF2α increases, enabling selective translation of survival and immune regulators in FXR1-overexpressing cells. Overriding these genes or phospho-eIF2α with inhibitors reduces chemosurvival. Thus, elevated FXR1 in quiescent or chemo-treated leukemic cells alters ribosomes that trigger stress signals to redirect translation for chemosurvival.
