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      Condensed but liquid-like domain organization of active chromatin regions in living human cells

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          Abstract

          In eukaryotes, higher-order chromatin organization is spatiotemporally regulated as domains, for various cellular functions. However, their physical nature in living cells remains unclear (e.g., condensed domains or extended fiber loops; liquid-like or solid-like). Using novel approaches combining genomics, single-nucleosome imaging, and computational modeling, we investigated the physical organization and behavior of early DNA replicated regions in human cells, which correspond to Hi-C contact domains with active chromatin marks. Motion correlation analysis of two neighbor nucleosomes shows that nucleosomes form physically condensed domains with ~150-nm diameters, even in active chromatin regions. The mean-square displacement analysis between two neighbor nucleosomes demonstrates that nucleosomes behave like a liquid in the condensed domain on the ~150 nm/~0.5 s spatiotemporal scale, which facilitates chromatin accessibility. Beyond the micrometers/minutes scale, chromatin seems solid-like, which may contribute to maintaining genome integrity. Our study reveals the viscoelastic principle of the chromatin polymer; chromatin is locally dynamic and reactive but globally stable.

          Abstract

          Active chromatin in human cells is rather condensed, but locally dynamic and reactive, and globally stable.

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          Most cited references96

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Contributors
                Journal
                Science Advances
                Sci. Adv.
                American Association for the Advancement of Science (AAAS)
                2375-2548
                April 05 2023
                April 05 2023
                : 9
                : 14
                Affiliations
                [1 ]Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.
                [2 ]Laboratory for Developmental Dynamics, Center for Biosystems Dynamics Research (BDR), RIKEN, Kobe, Hyogo 650-0047, Japan.
                [3 ]Department of Genetics, School of Life Science, SOKENDAI (Graduate University for Advanced Studies), Mishima, Shizuoka 411-8540, Japan.
                [4 ]Genome Evolution Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.
                [5 ]Department of Computer Science and Engineering, Fukuoka Institute of Technology, Fukuoka, Fukuoka 811-0295, Japan.
                [6 ]Department of Computational Biology and Medical Sciences, University of Tokyo, 5-1-5 Kashiwanoha Kashiwa, Chiba 277-8562, Japan.
                [7 ]Laboratory for Cell Polarity Regulation, Center for Biosystems Dynamics Research (BDR), RIKEN, Suita, Osaka 565-0874, Japan.
                [8 ]Department of Complex Systems Science, Nagoya University, Nagoya 464-8601, Japan.
                [9 ]Fukui Institute for Fundamental Chemistry, Kyoto University, Kyoto 606-8103, Japan.
                Article
                10.1126/sciadv.adf1488
                3bf8c9e7-499c-4b84-8c71-d5ed870d3f95
                © 2023
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