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      Limits in the detection of m 6A changes using MeRIP/m 6A-seq

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          Abstract

          Many cellular mRNAs contain the modified base m 6A, and recent studies have suggested that various stimuli can lead to changes in m 6A. The most common method to map m 6A and to predict changes in m 6A between conditions is methylated RNA immunoprecipitation sequencing (MeRIP-seq), through which methylated regions are detected as peaks in transcript coverage from immunoprecipitated RNA relative to input RNA. Here, we generated replicate controls and reanalyzed published MeRIP-seq data to estimate reproducibility across experiments. We found that m 6A peak overlap in mRNAs varies from ~30 to 60% between studies, even in the same cell type. We then assessed statistical methods to detect changes in m 6A peaks as distinct from changes in gene expression. However, from these published data sets, we detected few changes under most conditions and were unable to detect consistent changes across studies of similar stimuli. Overall, our work identifies limits to MeRIP-seq reproducibility in the detection both of peaks and of peak changes and proposes improved approaches for analysis of peak changes.

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          Most cited references31

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          Rethinking m6A Readers, Writers, and Erasers.

          In recent years, m6A has emerged as an abundant and dynamically regulated modification throughout the transcriptome. Recent technological advances have enabled the transcriptome-wide identification of m6A residues, which in turn has provided important insights into the biology and regulation of this pervasive regulatory mark. Also central to our current understanding of m6A are the discovery and characterization of m6A readers, writers, and erasers. Over the last few years, studies into the function of these proteins have led to important discoveries about the regulation and function of m6A. However, during this time our understanding of these proteins has also evolved considerably, sometimes leading to the reversal of early concepts regarding the reading, writing and erasing of m6A. In this review, we summarize recent advances in m6A research, and we highlight how these new findings have reshaped our understanding of how m6A is regulated in the transcriptome.
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            m(6)A RNA methylation is regulated by microRNAs and promotes reprogramming to pluripotency.

            N(6)-methyladenosine (m(6)A) has been recently identified as a conserved epitranscriptomic modification of eukaryotic mRNAs, but its features, regulatory mechanisms, and functions in cell reprogramming are largely unknown. Here, we report m(6)A modification profiles in the mRNA transcriptomes of four cell types with different degrees of pluripotency. Comparative analysis reveals several features of m(6)A, especially gene- and cell-type-specific m(6)A mRNA modifications. We also show that microRNAs (miRNAs) regulate m(6)A modification via a sequence pairing mechanism. Manipulation of miRNA expression or sequences alters m(6)A modification levels through modulating the binding of METTL3 methyltransferase to mRNAs containing miRNA targeting sites. Increased m(6)A abundance promotes the reprogramming of mouse embryonic fibroblasts (MEFs) to pluripotent stem cells; conversely, reduced m(6)A levels impede reprogramming. Our results therefore uncover a role for miRNAs in regulating m(6)A formation of mRNAs and provide a foundation for future functional studies of m(6)A modification in cell reprogramming.
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              N6-Methyladenosine in Flaviviridae Viral RNA Genomes Regulates Infection

              Summary The RNA modification N6-methyladenosine (m6A) post-transcriptionally regulates RNA function. The cellular machinery that controls m6A includes methyltransferases and demethylases that add or remove this modification, as well as m6A-binding YTHDF proteins that promote the translation or degradation of m6A-modified mRNA. We demonstrate that m6A modulates infection by hepatitis C virus (HCV). Depletion of m6A methyltransferases or an m6A demethylase, respectively, increases or decreases infectious HCV particle production. During HCV infection, YTHDF proteins relocalize to lipid droplets, sites of viral assembly, and their depletion increases infectious viral particles. We further mapped m6A sites across the HCV genome and determined that inactivating m6A in one viral genomic region increases viral titer without affecting RNA replication. Additional mapping of m6A on the RNA genomes of other Flaviviridae, including dengue, Zika, yellow fever, and West Nile virus, identifies conserved regions modified by m6A. Altogether, this work identifies m6A as a conserved regulatory mark across Flaviviridae genomes.
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                Author and article information

                Contributors
                abm237@cornell.edu
                stacy.horner@duke.edu
                chm2042@med.cornell.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 April 2020
                20 April 2020
                2020
                : 10
                : 6590
                Affiliations
                [1 ]ISNI 000000041936877X, GRID grid.5386.8, Department of Physiology and Biophysics, , Weill Cornell Medicine, ; New York City, NY 10065 USA
                [2 ]Tri-Institutional Program in Computational Biology and Medicine, New York City, NY 10065 USA
                [3 ]ISNI 0000000100241216, GRID grid.189509.c, Department of Molecular Genetics and Microbiology, , Duke University Medical Center, ; Durham, NC 27710 USA
                [4 ]ISNI 000000041936877X, GRID grid.5386.8, Division of Hematology and Medical Oncology, , Weill Cornell Medicine, ; New York City, NY 10065 USA
                [5 ]ISNI 000000041936877X, GRID grid.5386.8, Department of Pharmacology, , Weill Cornell Medicine, ; New York City, NY 10065 USA
                [6 ]ISNI 0000000100241216, GRID grid.189509.c, Department of Medicine, , Duke University Medical Center, ; Durham, NC 27710 USA
                [7 ]ISNI 000000041936877X, GRID grid.5386.8, The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, , Weill Cornell Medicine, ; New York, NY 10021 USA
                [8 ]ISNI 000000041936877X, GRID grid.5386.8, The Feil Family Brain and Mind Research Institute, , Weill Cornell Medicine, ; New York, NY 10065 USA
                [9 ]ISNI 000000041936877X, GRID grid.5386.8, The WorldQuant Initiative for Quantitative Prediction, , Weill Cornell Medicine, ; New York, NY 10021 USA
                Article
                63355
                10.1038/s41598-020-63355-3
                7170965
                32313079
                54c8348d-5d0b-4bbb-976c-7ca94c3035ea
                © The Author(s) 2020

                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
                : 8 March 2020
                : 19 March 2020
                Categories
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                Custom metadata
                © The Author(s) 2020

                Uncategorized
                software,standards,statistical methods,rna modification,rna sequencing
                Uncategorized
                software, standards, statistical methods, rna modification, rna sequencing

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