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      Three-dimensional chromatin interactions remain stable upon CAG/CTG repeat expansion

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          Abstract

          Unexpectedly, the molecular pathogenesis of expanded CAG/CTG diseases does not include changes in 3D chromatin conformation.

          Abstract

          Expanded CAG/CTG repeats underlie 13 neurological disorders, including myotonic dystrophy type 1 (DM1) and Huntington’s disease (HD). Upon expansion, disease loci acquire heterochromatic characteristics, which may provoke changes to chromatin conformation and thereby affect both gene expression and repeat instability. Here, we tested this hypothesis by performing 4C sequencing at the DMPK and HTT loci from DM1 and HD–derived cells. We find that allele sizes ranging from 15 to 1700 repeats displayed similar chromatin interaction profiles. This was true for both loci and for alleles with different DNA methylation levels and CTCF binding. Moreover, the ectopic insertion of an expanded CAG repeat tract did not change the conformation of the surrounding chromatin. We conclude that CAG/CTG repeat expansions are not enough to alter chromatin conformation in cis. Therefore, it is unlikely that changes in chromatin interactions drive repeat instability or changes in gene expression in these disorders.

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          Most cited references43

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

          Heng Li (2011)
          Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
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            Design and analysis of ChIP-seq experiments for DNA-binding proteins

            Recent progress in massively parallel sequencing platforms has allowed for genome-wide measurements of DNA-associated proteins using a combination of chromatin immunoprecipitation and sequencing (ChIP-seq). While a variety of methods exist for analysis of the established microarray alternative (ChIP-chip), few approaches have been described for processing ChIP-seq data. To fill this gap, we propose an analysis pipeline specifically designed to detect protein binding positions with high accuracy. Using three separate datasets, we illustrate new methods for improving tag alignment and correcting for background signals. We also compare sensitivity and spatial precision of several novel and previously described binding detection algorithms. Finally, we analyze the relationship between the depth of sequencing and characteristics of the detected binding positions, and provide a method for estimating the sequencing depth necessary for a desired coverage of protein binding sites.
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              Genome architecture: domain organization of interphase chromosomes.

              The architecture of interphase chromosomes is important for the regulation of gene expression and genome maintenance. Chromosomes are linearly segmented into hundreds of domains with different protein compositions. Furthermore, the spatial organization of chromosomes is nonrandom and is characterized by many local and long-range contacts among genes and other sequence elements. A variety of genome-wide mapping techniques have made it possible to chart these properties at high resolution. Combined with microscopy and computational modeling, the results begin to yield a more coherent picture that integrates linear and three-dimensional (3D) views of chromosome organization in relation to gene regulation and other nuclear functions. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                July 2020
                03 July 2020
                : 6
                : 27
                : eaaz4012
                Affiliations
                [1 ]Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland.
                [2 ]School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
                [3 ]Vital-IT Group, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
                [4 ]Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.
                [5 ]Department of Computational Biology, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland.
                [6 ]UK Dementia Research Institute at Cardiff University at Cardiff University, Hadyn Ellis Building, Maindy Road, CF24 4HQ Cardiff, UK.
                [7 ]Department of Molecular Mechanisms of Disease, University of Zurich, 8057 Zurich, Switzerland.
                [8 ]Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland.
                Author notes
                [* ]Corresponding author. Email: dionv@ 123456cardiff.ac.uk
                Author information
                http://orcid.org/0000-0002-4935-1480
                http://orcid.org/0000-0002-6684-6880
                http://orcid.org/0000-0003-2182-3607
                http://orcid.org/0000-0003-1064-1162
                http://orcid.org/0000-0003-4389-3200
                http://orcid.org/0000-0002-2112-7751
                http://orcid.org/0000-0001-5174-8092
                http://orcid.org/0000-0001-8474-6587
                http://orcid.org/0000-0002-3346-6590
                http://orcid.org/0000-0002-3413-6841
                http://orcid.org/0000-0003-4953-7637
                Article
                aaz4012
                10.1126/sciadv.aaz4012
                7334000
                3de5ea0f-c9fd-49ab-9a42-73a403a73ec3
                Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 September 2019
                : 19 May 2020
                Funding
                Funded by: doi http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;
                Award ID: 172936
                Funded by: doi http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;
                Award ID: 179065
                Funded by: doi http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;
                Award ID: 150712
                Funded by: doi http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;
                Award ID: 179063
                Funded by: doi http://dx.doi.org/10.13039/501100012390, SystemsX.ch;
                Funded by: doi http://dx.doi.org/10.13039/501100012390, SystemsX.ch;
                Funded by: UK DRI;
                Funded by: NCCR in RNA and Disease;
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Cellular Neuroscience
                Genetics
                Cellular Neuroscience
                Custom metadata
                Karla Peñamante

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