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      The SMAD2/3 interactome reveals that TGFβ controls m 6A mRNA methylation in pluripotency

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          Abstract

          The TGFβ pathway plays an essential role in embryonic development, organ homeostasis, tissue repair, and disease 1, 2. This diversity of tasks is achieved through the intracellular effector SMAD2/3, whose canonical function is to control activity of target genes by interacting with transcriptional regulators 3. Nevertheless, a complete description of the factors interacting with SMAD2/3 in any given cell type is still lacking. Here we address this limitation by describing the interactome of SMAD2/3 in human pluripotent stem cells (hPSCs). This analysis reveals that SMAD2/3 is involved in multiple molecular processes in addition to its role in transcription. In particular, we identify a functional interaction with the METTL3-METTL14-WTAP complex, which deposits N 6-methyladenosine (m6A) 4. We uncover that SMAD2/3 promotes binding of the m6A methyltransferase complex onto a subset of transcripts involved in early cell fate decisions. This mechanism destabilizes specific SMAD2/3 transcriptional targets, including the pluripotency factor NANOG, thereby poising them for rapid downregulation upon differentiation to enable timely exit from pluripotency. Collectively, these findings reveal the mechanism by which extracellular signalling can induce rapid cellular responses through regulations of the epitranscriptome. These novel aspects of TGFβ signalling could have far-reaching implications in many other cell types and in diseases such as cancer 5.

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          Most cited references73

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Is Open Access

            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              Trimmomatic: a flexible trimmer for Illumina sequence data

              Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                2 May 2018
                28 February 2018
                08 March 2018
                28 August 2018
                : 555
                : 7695
                : 256-259
                Affiliations
                [1 ]Wellcome Trust - MRC Cambridge Stem Cell Institute Anne McLaren Laboratory and Department of Surgery, University of Cambridge, UK
                [2 ]Wellcome Trust Sanger Institute, Hinxton UK
                [3 ]Department of Molecular Biology, Radboud University Nijmegen, The Netherlands
                [4 ]Francis Crick Institute and Department of Molecular Neuroscience, University College London, UK
                [5 ]Department of Pathology, University of Cambridge, UK
                Author notes
                [* ]Correspondence and requests for materials should be addressed to Ludovic Vallier ( lv225@ 123456cam.ac.uk ).
                [†]

                Current address: Department of Pathology, University of Washington, Seattle, WA, USA.

                [‡]

                Current address: Institute of Molecular Biotechnology, Vienna, Austria.

                Article
                EMS75858
                10.1038/nature25784
                5951268
                29489750
                18e987af-c8bd-4ebd-933c-a97b5d07c99c

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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