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      Genome-wide analysis of EGR2/SOX10 binding in myelinating peripheral nerve

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          Abstract

          Myelin is essential for the rapidity of saltatory nerve conduction, and also provides trophic support for axons to prevent axonal degeneration. Two critical determinants of myelination are SOX10 and EGR2/KROX20. SOX10 is required for specification of Schwann cells from neural crest, and is required at every stage of Schwann cell development. Egr2/Krox20 expression is activated by axonal signals in myelinating Schwann cells, and is required for cell cycle arrest and myelin formation. To elucidate the integrated function of these two transcription factors during peripheral nerve myelination, we performed in vivo ChIP-Seq analysis of myelinating peripheral nerve. Integration of these binding data with loss-of-function array data identified a range of genes regulated by these factors. In addition, although SOX10 itself regulates Egr2/Krox20 expression, leading to coordinate activation of several major myelin genes by the two factors, there is a large subset of genes that are activated independent of EGR2. Finally, the results identify a set of SOX10-dependent genes that are expressed in early Schwann cell development, but become subsequently repressed by EGR2/KROX20.

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          Most cited references75

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          PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls.

          Chromatin immunoprecipitation (ChIP) followed by tag sequencing (ChIP-seq) using high-throughput next-generation instrumentation is fast, replacing chromatin immunoprecipitation followed by genome tiling array analysis (ChIP-chip) as the preferred approach for mapping of sites of transcription-factor binding and chromatin modification. Using two deeply sequenced data sets for human RNA polymerase II and STAT1, each with matching input-DNA controls, we describe a general scoring approach to address unique challenges in ChIP-seq data analysis. Our approach is based on the observation that sites of potential binding are strongly correlated with signal peaks in the control, likely revealing features of open chromatin. We develop a two-pass strategy called PeakSeq to compensate for this. A two-pass strategy compensates for signal caused by open chromatin, as revealed by inclusion of the controls. The first pass identifies putative binding sites and compensates for genomic variation in the 'mappability' of sequences. The second pass filters out sites not significantly enriched compared to the normalized control, computing precise enrichments and significances. Our scoring procedure enables us to optimize experimental design by estimating the depth of sequencing required for a desired level of coverage and demonstrating that more than two replicates provides only a marginal gain in information.
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            Krox-20 controls myelination in the peripheral nervous system.

            The molecular mechanisms controlling the process of myelination by Schwann cells remain elusive, despite recent progress in the identification and characterization of genes encoding myelin components (reviewed in ref. 1). We have created a null allele in the mouse Krox-20 gene, which encodes a zinc-finger transcription factor, by in-frame insertion of the Escherichia coli lacZ gene, and have shown that hindbrain segmentation is affected in Krox-20-/- embryos. We demonstrate here that Krox-20 is also activated in Schwann cells before the onset of myelination and that its disruption blocks Schwann cells at an early stage in their differentiation, thus preventing myelination in the peripheral nervous system. In Krox-20-/- mice, Schwann cells wrap their cytoplasmic processes only one and a half turns around the axon, and although they express the early myelin marker, myelin-associated glycoprotein, late myelin gene products are absent, including those for protein zero and myelin basic protein. Therefore Krox-20 is likely to control a set of genes required for completion of myelination in the peripheral nervous system.
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              Animal transcription networks as highly connected, quantitative continua.

              To understand how transcription factors function, it is essential to determine the range of genes that they each bind and regulate in vivo. Here I review evidence that most animal transcription factors each bind to a majority of genes over a quantitative series of DNA occupancy levels. These continua span functional, quasifunctional, and nonfunctional DNA binding events. Factor regulatory specificities are distinguished by quantitative differences in DNA occupancy patterns. I contrast these results with models for transcription networks that define discrete sets of direct target and nontarget genes and consequently do not fully capture the complexity observed in vivo. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                August 2012
                August 2012
                9 April 2012
                9 April 2012
                : 40
                : 14
                : 6449-6460
                Affiliations
                1Waisman Center, 2Department of Statistics, 3Department of Biostatistics and Medical Informatics, 4Program in Cellular and Molecular Biology and, 5Department of Comparative Biosciences, University of Wisconsin, Madison, WI, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +1 608 263 4246; Fax: +1 608 263 3926; Email: jpsvaren@ 123456wisc.edu
                Article
                gks313
                10.1093/nar/gks313
                3413122
                22492709
                76afd0b8-e8a2-469d-b493-fab37429c6a6
                © The Author(s) 2012. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 October 2011
                : 25 March 2012
                : 26 March 2012
                Page count
                Pages: 12
                Categories
                Gene Regulation, Chromatin and Epigenetics

                Genetics
                Genetics

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