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      Accurate detection of m 6A RNA modifications in native RNA sequences

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          Abstract

          The epitranscriptomics field has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here, we show that using direct RNA sequencing, N 6-methyladenosine (m 6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Specifically, we find that our algorithm, trained with m 6A-modified and unmodified synthetic sequences, can predict m 6A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m 6A RNA modifications in vivo with an accuracy of 87%. Moreover, we further validate our method by showing that these ‘errors’ are typically not observed in yeast ime4-knockout strains, which lack m 6A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context.

          Abstract

          We currently lack generic methods to map RNA modifications across the entire transcriptome. Here, the authors demonstrate that m 6A RNA modifications can be detected with high accuracy using nanopore direct RNA sequencing.

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          Pseudouridine profiling reveals regulated mRNA pseudouridylation in yeast and human cells

          Post-transcriptional modification of RNA nucleosides occurs in all living organisms. Pseudouridine, the most abundant modified nucleoside in non-coding RNAs 1 , enhances the function of transfer RNA and ribosomal RNA by stabilizing RNA structure 2–8 . mRNAs were not known to contain pseudouridine, but artificial pseudouridylation dramatically affects mRNA function – it changes the genetic code by facilitating non-canonical base pairing in the ribosome decoding center 9,10 . However, without evidence of naturally occurring mRNA pseudouridylation, its physiological was unclear. Here we present a comprehensive analysis of pseudouridylation in yeast and human RNAs using Pseudo-seq, a genome-wide, single-nucleotide-resolution method for pseudouridine identification. Pseudo-seq accurately identifies known modification sites as well as 100 novel sites in non-coding RNAs, and reveals hundreds of pseudouridylated sites in mRNAs. Genetic analysis allowed us to assign most of the new modification sites to one of seven conserved pseudouridine synthases, Pus1–4, 6, 7 and 9. Notably, the majority of pseudouridines in mRNA are regulated in response to environmental signals, such as nutrient deprivation in yeast and serum starvation in human cells. These results suggest a mechanism for the rapid and regulated rewiring of the genetic code through inducible mRNA modifications. Our findings reveal unanticipated roles for pseudouridylation and provide a resource for identifying the targets of pseudouridine synthases implicated in human disease 11–13 .
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            Transcriptome-wide mapping reveals widespread dynamic-regulated pseudouridylation of ncRNA and mRNA.

            Pseudouridine is the most abundant RNA modification, yet except for a few well-studied cases, little is known about the modified positions and their function(s). Here, we develop Ψ-seq for transcriptome-wide quantitative mapping of pseudouridine. We validate Ψ-seq with spike-ins and de novo identification of previously reported positions and discover hundreds of unique sites in human and yeast mRNAs and snoRNAs. Perturbing pseudouridine synthases (PUS) uncovers which pseudouridine synthase modifies each site and their target sequence features. mRNA pseudouridinylation depends on both site-specific and snoRNA-guided pseudouridine synthases. Upon heat shock in yeast, Pus7p-mediated pseudouridylation is induced at >200 sites, and PUS7 deletion decreases the levels of otherwise pseudouridylated mRNA, suggesting a role in enhancing transcript stability. rRNA pseudouridine stoichiometries are conserved but reduced in cells from dyskeratosis congenita patients, where the PUS DKC1 is mutated. Our work identifies an enhanced, transcriptome-wide scope for pseudouridine and methods to dissect its underlying mechanisms and function. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Acetylation of Cytidine in mRNA Promotes Translation Efficiency

              Generation of the “epitranscriptome” through post-transcriptional ribonucleoside modification embeds a layer of regulatory complexity into RNA structure and function. Here we describe N4-acetylcytidine (ac4C) as an mRNA modification that is catalyzed by the acetyltransferase NAT10. Transcriptome-wide mapping of ac4C revealed discretely acetylated regions that were enriched within coding sequences. Ablation of NAT10 reduced ac4C detection at the mapped mRNA sites and was globally associated with target mRNA down-regulation. Analysis of mRNA half-lives revealed a NAT10-dependent increase in stability in the cohort of acetylated mRNAs. mRNA acetylation was further demonstrated to enhance substrate translation in vitro and in vivo . Codon content analysis within ac4C peaks uncovered a biased representation of cytidine within wobble sites that was empirically determined to influence mRNA decoding efficiency. These findings expand the repertoire of mRNA modifications to include an acetylated residue and establish a role for ac4C in the regulation of mRNA translation. Post-transcriptional acetylation of cytidines in mammalian mRNAs enhances RNA stability and translation.
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                Author and article information

                Contributors
                eva.novoa@crg.eu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 September 2019
                9 September 2019
                2019
                : 10
                : 4079
                Affiliations
                [1 ]GRID grid.473715.3, Centre for Genomic Regulation (CRG), , The Barcelona Institute of Science and Technology, ; 08003 Barcelona, Spain
                [2 ]ISNI 0000 0000 9983 6924, GRID grid.415306.5, Department of Neuroscience, , Garvan Institute of Medical Research, ; Darlinghurst, New South Wales 2010 Australia
                [3 ]ISNI 0000 0004 4902 0432, GRID grid.1005.4, St-Vincent’s Clinical School, UNSW Sydney, ; Darlinghurst, New South Wales 2010 Australia
                [4 ]ISNI 0000 0001 2172 2676, GRID grid.5612.0, Universitat Pompeu Fabra (UPF), ; Barcelona, Spain
                [5 ]ISNI 000000041936877X, GRID grid.5386.8, Department of Physiology and Biophysics, , Weill Cornell Medicine, ; New York, NY 10021 USA
                [6 ]ISNI 000000041936877X, GRID grid.5386.8, The Feil Family Brain and Mind Institute, , Weill Cornell Medicine, ; New York, NY 10021 USA
                [7 ]ISNI 000000041936877X, GRID grid.5386.8, The WorldQuant Initiative for Quantitative Prediction, , Weill Cornell Medicine, ; New York, NY 10021 USA
                [8 ]ISNI 0000 0004 0604 7563, GRID grid.13992.30, Department of Molecular Genetics, , Weizmann Institute of Science, ; Rehovot, Israel
                [9 ]ISNI 0000 0000 9983 6924, GRID grid.415306.5, Kinghorn Centre for Clinical Genomics, , Garvan Institute of Medical Research, ; Darlinghurst, New South Wales 2010 Australia
                [10 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Present Address: Green templeton College, ; Oxford, OX2 6HG UK
                Author information
                http://orcid.org/0000-0002-8663-4586
                http://orcid.org/0000-0001-7654-9137
                http://orcid.org/0000-0002-1850-1642
                http://orcid.org/0000-0003-2259-1713
                http://orcid.org/0000-0002-9367-6311
                Article
                11713
                10.1038/s41467-019-11713-9
                6734003
                31501426
                910f932b-4edf-4c2c-9af1-9480eba754d7
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 February 2019
                : 29 July 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000923, Department of Education and Training | Australian Research Council (ARC);
                Award ID: DP180103571
                Award ID: DE170100506
                Award Recipient :
                Categories
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                © The Author(s) 2019

                Uncategorized
                rna modification,software
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                rna modification, software

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