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      Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin

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          Abstract

          The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among elementary components of biological systems define their relative positioning and are key determinants of spatial patterns. However, biological variability and the lack of appropriate spatial statistical methods and models limit our current ability to analyze these interactions. Here, we developed a framework to dissect spatial interactions and organization principles by combining unbiased statistical tests, multiple spatial descriptors and new spatial models. We used plant constitutive heterochromatin as a model system to demonstrate the potential of our framework. Our results challenge the common view of a peripheral organization of chromocenters, showing that chromocenters are arranged along both radial and lateral directions in the nuclear space and obey a multiscale organization with scale-dependent antagonistic effects. The proposed generic framework will be useful to identify determinants of spatial organizations and to question their interplay with biological functions.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Equation of State Calculations by Fast Computing Machines

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              Phase separation drives heterochromatin domain formation

              Constitutive heterochromatin is an important component of eukaryotic genomes that has essential roles in nuclear architecture, DNA repair and genome stability, and silencing of transposon and gene expression. Heterochromatin is highly enriched for repetitive sequences, and is defined epigenetically by methylation of histone H3 at lysine 9 and recruitment of its binding partner heterochromatin protein 1 (HP1). A prevalent view of heterochromatic silencing is that these and associated factors lead to chromatin compaction, resulting in steric exclusion of regulatory proteins such as RNA polymerase from the underlying DNA. However, compaction alone does not account for the formation of distinct, multi-chromosomal, membrane-less heterochromatin domains within the nucleus, fast diffusion of proteins inside the domain, and other dynamic features of heterochromatin. Here we present data that support an alternative hypothesis: that the formation of heterochromatin domains is mediated by phase separation, a phenomenon that gives rise to diverse non-membrane-bound nuclear, cytoplasmic and extracellular compartments. We show that Drosophila HP1a protein undergoes liquid–liquid demixing in vitro, and nucleates into foci that display liquid properties during the first stages of heterochromatin domain formation in early Drosophila embryos. Furthermore, in both Drosophila and mammalian cells, heterochromatin domains exhibit dynamics that are characteristic of liquid phase-separation, including sensitivity to the disruption of weak hydrophobic interactions, and reduced diffusion, increased coordinated movement and inert probe exclusion at the domain boundary. We conclude that heterochromatic domains form via phase separation, and mature into a structure that includes liquid and stable compartments. We propose that emergent biophysical properties associated with phase-separated systems are critical to understanding the unusual behaviours of heterochromatin, and how chromatin domains in general regulate essential nuclear functions.
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                Author and article information

                Contributors
                valerie.gaudin@inrae.fr
                philippe.andrey@inrae.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 January 2021
                11 January 2021
                2021
                : 11
                : 323
                Affiliations
                GRID grid.460789.4, ISNI 0000 0004 4910 6535, Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, , Université Paris-Saclay, ; 78000 Versailles, France
                Article
                79158
                10.1038/s41598-020-79158-5
                7801681
                33431919
                8c03312e-79f4-4f44-9b93-795b5cb9787b
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 September 2020
                : 1 December 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100011264, FP7 People: Marie-Curie Actions;
                Award ID: 316965
                Award Recipient :
                Funded by: LabEx Saclay Plant Sciences
                Award ID: ANR-10-LABX-0040-SPS
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                image processing,statistical methods,cellular imaging,nuclear organization
                Uncategorized
                image processing, statistical methods, cellular imaging, nuclear organization

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