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      Principles of meiotic chromosome assembly revealed in S. cerevisiae

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          Abstract

          During meiotic prophase, chromosomes organise into a series of chromatin loops emanating from a proteinaceous axis, but the mechanisms of assembly remain unclear. Here we use Saccharomyces cerevisiae to explore how this elaborate three-dimensional chromosome organisation is linked to genomic sequence. As cells enter meiosis, we observe that strong cohesin-dependent grid-like Hi-C interaction patterns emerge, reminiscent of mammalian interphase organisation, but with distinct regulation. Meiotic patterns agree with simulations of loop extrusion with growth limited by barriers, in which a heterogeneous population of expanding loops develop along the chromosome. Importantly, CTCF, the factor that imposes similar features in mammalian interphase, is absent in S. cerevisiae, suggesting alternative mechanisms of barrier formation. While grid-like interactions emerge independently of meiotic chromosome synapsis, synapsis itself generates additional compaction that matures differentially according to telomere proximity and chromosome size. Collectively, our results elucidate fundamental principles of chromosome assembly and demonstrate the essential role of cohesin within this evolutionarily conserved process.

          Abstract

          During meiotic prophase chromosomes organise into a series of chromatin loops, but the mechanisms of assembly remain unclear. Here the authors use Saccharomyces cerevisiae to elucidate how this elaborate three-dimensional chromosome organisation is linked to genomic sequence, and demonstrate an essential role for cohesin during this process.

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          Most cited references54

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          HiGlass: web-based visual exploration and analysis of genome interaction maps

          We present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others. We demonstrate its utility in exploring different experimental conditions, comparing the results of analyses, and creating interactive snapshots to share with collaborators and the broader public. HiGlass is accessible online at http://higlass.io and is also available as a containerized application that can be run on any platform. Electronic supplementary material The online version of this article (10.1186/s13059-018-1486-1) contains supplementary material, which is available to authorized users.
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            Organization of the mitotic chromosome.

            Mitotic chromosomes are among the most recognizable structures in the cell, yet for over a century their internal organization remains largely unsolved. We applied chromosome conformation capture methods, 5C and Hi-C, across the cell cycle and revealed two distinct three-dimensional folding states of the human genome. We show that the highly compartmentalized and cell type-specific organization described previously for nonsynchronous cells is restricted to interphase. In metaphase, we identified a homogenous folding state that is locus-independent, common to all chromosomes, and consistent among cell types, suggesting a general principle of metaphase chromosome organization. Using polymer simulations, we found that metaphase Hi-C data are inconsistent with classic hierarchical models and are instead best described by a linearly organized longitudinally compressed array of consecutive chromatin loops.
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              Cooler: scalable storage for Hi-C data and other genomically labeled arrays

              Most existing coverage-based (epi)genomic datasets are one-dimensional, but newer technologies probing interactions (physical, genetic, etc.) produce quantitative maps with two-dimensional genomic coordinate systems. Storage and computational costs mount sharply with data resolution when such maps are stored in dense form. Hence, there is a pressing need to develop data storage strategies that handle the full range of useful resolutions in multidimensional genomic datasets by taking advantage of their sparse nature, while supporting efficient compression and providing fast random access to facilitate development of scalable algorithms for data analysis. We developed a file format called cooler, based on a sparse data model, that can support genomically labeled matrices at any resolution. It has the flexibility to accommodate various descriptions of the data axes (genomic coordinates, tracks and bin annotations), resolutions, data density patterns and metadata. Cooler is based on HDF5 and is supported by a Python library and command line suite to create, read, inspect and manipulate cooler data collections. The format has been adopted as a standard by the NIH 4D Nucleome Consortium. Cooler is cross-platform, BSD-licensed and can be installed from the Python package index or the bioconda repository. The source code is maintained on Github at https://github.com/mirnylab/cooler. Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                S.Schalbetter@sussex.ac.uk
                geoff.fudenberg@gladstone.ucsf.edu
                katherine.pollard@gladstone.ucsf.edu
                M.Neale@sussex.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                22 October 2019
                22 October 2019
                2019
                : 10
                : 4795
                Affiliations
                [1 ]ISNI 0000 0004 1936 7590, GRID grid.12082.39, Genome Damage and Stability Centre, School of Life Sciences, , University of Sussex, ; Brighton, UK
                [2 ]ISNI 0000 0004 0572 7110, GRID grid.249878.8, Gladstone Institutes for Data Science and Biotechnology, ; San Francisco, USA
                [3 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Epidemiology & Biostatistics, Institute for Human Genetics, Quantitative Biology Institute, and Institute for Computational Health Sciences, , University of California, ; San Francisco, CA USA
                [4 ]Chan-Zuckerberg Biohub, San Francisco, CA USA
                Author information
                http://orcid.org/0000-0001-7563-169X
                http://orcid.org/0000-0001-5905-6517
                http://orcid.org/0000-0002-4455-9717
                http://orcid.org/0000-0002-9870-6196
                http://orcid.org/0000-0002-6453-1877
                Article
                12629
                10.1038/s41467-019-12629-0
                6805904
                30602773
                4f19f453-d36a-4786-a577-1b86c4ecab71
                © The Author(s) 2019

                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
                : 11 February 2019
                : 20 September 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100004440, Wellcome Trust (Wellcome);
                Award ID: 200843/Z/16/Z
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100011199, EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013));
                Award ID: 311336
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/M010279/1, BB/S001425/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: MH109907, HL098179
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                chromosomes,computational models,genome,chromatin structure
                Uncategorized
                chromosomes, computational models, genome, chromatin structure

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