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      Methods for RNA Modification Mapping Using Deep Sequencing: Established and New Emerging Technologies

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          Abstract

          New analytics of post-transcriptional RNA modifications have paved the way for a tremendous upswing of the biological and biomedical research in this field. This especially applies to methods that included RNA-Seq techniques, and which typically result in what is termed global scale modification mapping. In this process, positions inside a cell’s transcriptome are receiving a status of potential modification sites (so called modification calling), typically based on a score of some kind that issues from the particular method applied. The resulting data are thought to represent information that goes beyond what is contained in typical transcriptome data, and hence the field has taken to use the term “epitranscriptome”. Due to the high rate of newly published mapping techniques, a significant number of chemically distinct RNA modifications have become amenable to mapping, albeit with variegated accuracy and precision, depending on the nature of the technique. This review gives a brief overview of known techniques, and how they were applied to modification calling.

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          Most cited references58

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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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              Transcriptome-wide mapping of N(6)-methyladenosine by m(6)A-seq based on immunocapturing and massively parallel sequencing.

              N(6)-methyladenosine-sequencing (m(6)A-seq) is an immunocapturing approach for the unbiased transcriptome-wide localization of m(6)A in high resolution. To our knowledge, this is the first protocol to allow a global view of this ubiquitous RNA modification, and it is based on antibody-mediated enrichment of methylated RNA fragments followed by massively parallel sequencing. Building on principles of chromatin immunoprecipitation-sequencing (ChIP-seq) and methylated DNA immunoprecipitation (MeDIP), read densities of immunoprecipitated RNA relative to untreated input control are used to identify methylated sites. A consensus motif is deduced, and its distance to the point of maximal enrichment is assessed; these measures further corroborate the success of the protocol. Identified locations are intersected in turn with gene architecture to draw conclusions regarding the distribution of m(6)A between and within gene transcripts. When applied to human and mouse transcriptomes, m(6)A-seq generated comprehensive methylation profiles revealing, for the first time, tenets governing the nonrandom distribution of m(6)A. The protocol can be completed within ~9 d for four different sample pairs (each consists of an immunoprecipitation and corresponding input).
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                Author and article information

                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                09 January 2019
                January 2019
                : 10
                : 1
                : 35
                Affiliations
                [1 ]Laboratoire IMoPA, UMR7365 National Centre for Scientific Research (CNRS)-Lorraine University, Biopôle, 9 Avenue de la Forêt de Haye, 54505 Vandoeuvre-les-Nancy, France
                [2 ]Institute of Pharmacy and Biochemistry, Johannes Gutenberg-University Mainz, Staudingerweg 5, 55128 Mainz, Germany
                Author notes
                [* ]Correspondence: Yuri.Motorin@ 123456univ-lorraine.fr (Y.M.); mhelm@ 123456uni-mainz.de (M.H.); Tel.: +33-3-7274-6629 (Y.M.); +49-6131-392-5731 (M.H.)
                Author information
                https://orcid.org/0000-0002-8018-334X
                https://orcid.org/0000-0002-0154-0928
                Article
                genes-10-00035
                10.3390/genes10010035
                6356707
                30634534
                3e53fa0a-ce91-4fe1-9e1f-c1b733719c29
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 November 2018
                : 04 January 2019
                Categories
                Review

                rna modification,epitranscriptome,deep sequencing,next generation sequencing,rna-seq,chemical treatment,engineered reverse transcriptase enzymes

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