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      Understanding RNA modifications: the promises and technological bottlenecks of the ‘epitranscriptome’

      review-article
      , ,
      Open Biology
      The Royal Society
      RNA, transcriptome, chemical modification, epigenetics

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          Abstract

          The discovery of mechanisms that alter genetic information via RNA editing or introducing covalent RNA modifications points towards a complexity in gene expression that challenges long-standing concepts. Understanding the biology of RNA modifications represents one of the next frontiers in molecular biology. To this date, over 130 different RNA modifications have been identified, and improved mass spectrometry approaches are still adding to this list. However, only recently has it been possible to map selected RNA modifications at single-nucleotide resolution, which has created a number of exciting hypotheses about the biological function of RNA modifications, culminating in the proposition of the ‘epitranscriptome’. Here, we review some of the technological advances in this rapidly developing field, identify the conceptual challenges and discuss approaches that are needed to rigorously test the biological function of specific RNA modifications.

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          Most cited references120

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          Sperm tsRNAs contribute to intergenerational inheritance of an acquired metabolic disorder.

          Increasing evidence indicates that metabolic disorders in offspring can result from the father's diet, but the mechanism remains unclear. In a paternal mouse model given a high-fat diet (HFD), we showed that a subset of sperm transfer RNA-derived small RNAs (tsRNAs), mainly from 5' transfer RNA halves and ranging in size from 30 to 34 nucleotides, exhibited changes in expression profiles and RNA modifications. Injection of sperm tsRNA fractions from HFD males into normal zygotes generated metabolic disorders in the F1 offspring and altered gene expression of metabolic pathways in early embryos and islets of F1 offspring, which was unrelated to DNA methylation at CpG-enriched regions. Hence, sperm tsRNAs represent a paternal epigenetic factor that may mediate intergenerational inheritance of diet-induced metabolic disorders.
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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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              Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.

              Our understanding of the development and maintenance of tissues has been greatly aided by large-scale gene expression analysis. However, tissues are invariably complex, and expression analysis of a tissue confounds the true expression patterns of its constituent cell types. Here we describe a novel strategy to access such complex samples. Single-cell RNA-seq expression profiles were generated, and clustered to form a two-dimensional cell map onto which expression data were projected. The resulting cell map integrates three levels of organization: the whole population of cells, the functionally distinct subpopulations it contains, and the single cells themselves-all without need for known markers to classify cell types. The feasibility of the strategy was demonstrated by analyzing the transcriptomes of 85 single cells of two distinct types. We believe this strategy will enable the unbiased discovery and analysis of naturally occurring cell types during development, adult physiology, and disease.
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                Author and article information

                Journal
                Open Biol
                Open Biol
                RSOB
                royopenbio
                Open Biology
                The Royal Society
                2046-2441
                May 2017
                31 May 2017
                31 May 2017
                : 7
                : 5
                : 170077
                Affiliations
                Center for Anatomy and Cell Biology, Medical University Vienna , Schwarzspanierstrasse 17-I, 1090 Vienna, Austria
                Author notes
                Author information
                http://orcid.org/0000-0003-1952-8115
                http://orcid.org/0000-0003-1747-0853
                Article
                rsob170077
                10.1098/rsob.170077
                5451548
                28566301
                c0cd5657-4b31-4cd5-8b62-27ff6ef88727
                © 2017 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 30 March 2017
                : 2 May 2017
                Funding
                Funded by: Austrian Science Fund, http://dx.doi.org/10.13039/501100002428;
                Award ID: P 26845
                Award ID: P 29094
                Categories
                1001
                33
                58
                198
                129
                181
                Review
                Review Article
                Custom metadata
                May 2017

                Life sciences
                rna,transcriptome,chemical modification,epigenetics
                Life sciences
                rna, transcriptome, chemical modification, epigenetics

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