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      Chromatin loops associated with active genes and heterochromatin shape rice genome architecture for transcriptional regulation

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          Abstract

          Insight into high-resolution three-dimensional genome organization and its effect on transcription remains largely elusive in plants. Here, using a long-read ChIA-PET approach, we map H3K4me3- and RNA polymerase II (RNAPII)-associated promoter–promoter interactions and H3K9me2-marked heterochromatin interactions at nucleotide/gene resolution in rice. The chromatin architecture is separated into different independent spatial interacting modules with distinct transcriptional potential and covers approximately 82% of the genome. Compared to inactive modules, active modules possess the majority of active loop genes with higher density and contribute to most of the transcriptional activity in rice. In addition, promoter–promoter interacting genes tend to be transcribed cooperatively. In contrast, the heterochromatin-mediated loops form relative stable structure domains in chromatin configuration. Furthermore, we examine the impact of genetic variation on chromatin interactions and transcription and identify a spatial correlation between the genetic regulation of eQTLs and e-traits. Thus, our results reveal hierarchical and modular 3D genome architecture for transcriptional regulation in rice.

          Abstract

          Three-dimensional genome organization and its effect on transcription remain elusive in rice. Here, the authors map promoter–promoter interactions and heterochromatin interactions using ChIA-PET and reveal spatial correlation between the genetic regulation of eQTLs and e-traits.

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          Most cited references23

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          Architectural protein subclasses shape 3D organization of genomes during lineage commitment.

          Understanding the topological configurations of chromatin may reveal valuable insights into how the genome and epigenome act in concert to control cell fate during development. Here, we generate high-resolution architecture maps across seven genomic loci in embryonic stem cells and neural progenitor cells. We observe a hierarchy of 3D interactions that undergo marked reorganization at the submegabase scale during differentiation. Distinct combinations of CCCTC-binding factor (CTCF), Mediator, and cohesin show widespread enrichment in chromatin interactions at different length scales. CTCF/cohesin anchor long-range constitutive interactions that might form the topological basis for invariant subdomains. Conversely, Mediator/cohesin bridge short-range enhancer-promoter interactions within and between larger subdomains. Knockdown of Smc1 or Med12 in embryonic stem cells results in disruption of spatial architecture and downregulation of genes found in cohesin-mediated interactions. We conclude that cell-type-specific chromatin organization occurs at the submegabase scale and that architectural proteins shape the genome in hierarchical length scales. Copyright © 2013 Elsevier Inc. All rights reserved.
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            The Energetics and Physiological Impact of Cohesin Extrusion

            Cohesin extrusion is thought to play a central role in establishing the architecture of mammalian genomes. However, extrusion has not been visualized in vivo, and thus, its functional impact and energetics are unknown. Using ultra-deep Hi-C, we show that loop domains form by a process that requires cohesin ATPases. Once formed, however, loops and compartments are maintained for hours without energy input. Strikingly, without ATP, we observe the emergence of hundreds of CTCF-independent loops that link regulatory DNA. We also identify architectural "stripes," where a loop anchor interacts with entire domains at high frequency. Stripes often tether super-enhancers to cognate promoters, and in B cells, they facilitate Igh transcription and recombination. Stripe anchors represent major hotspots for topoisomerase-mediated lesions, which promote chromosomal translocations and cancer. In plasmacytomas, stripes can deregulate Igh-translocated oncogenes. We propose that higher organisms have coopted cohesin extrusion to enhance transcription and recombination, with implications for tumor development.
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              Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation.

              A key finding of the ENCODE project is that the enhancer landscape of mammalian cells undergoes marked alterations during ontogeny. However, the nature and extent of these changes are unclear. As part of the NIH Mouse Regulome Project, we here combined DNaseI hypersensitivity, ChIP-seq, and ChIA-PET technologies to map the promoter-enhancer interactomes of pluripotent ES cells and differentiated B lymphocytes. We confirm that enhancer usage varies widely across tissues. Unexpectedly, we find that this feature extends to broadly transcribed genes, including Myc and Pim1 cell-cycle regulators, which associate with an entirely different set of enhancers in ES and B cells. By means of high-resolution CpG methylomes, genome editing, and digital footprinting, we show that these enhancers recruit lineage-determining factors. Furthermore, we demonstrate that the turning on and off of enhancers during development correlates with promoter activity. We propose that organisms rely on a dynamic enhancer landscape to control basic cellular functions in a tissue-specific manner. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                guoliang.li@mail.hzau.edu.cn
                xingwangli@mail.hzau.edu.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                13 August 2019
                13 August 2019
                2019
                : 10
                : 3640
                Affiliations
                [1 ]ISNI 0000 0004 1790 4137, GRID grid.35155.37, National Key Laboratory of Crop Genetic Improvement, , Huazhong Agricultural University, ; 1 Shizishan Street, Hongshan District, Wuhan, 430070 Hubei China
                [2 ]GRID grid.494634.8, Department of Resources and Environment, , Henan University of Engineering, ; 1 Xianghe Road, Longhu Town, Zhengzhou, 451191 Henan China
                [3 ]ISNI 0000 0004 1790 4137, GRID grid.35155.37, State Key Laboratory of Agricultural Microbiology, , Huazhong Agricultural University, ; 1 Shizishan Street, Hongshan District, Wuhan, 430070 Hubei China
                [4 ]ISNI 0000 0001 2180 6431, GRID grid.4280.e, Department of Computer Science, , National University of Singapore, ; 13 Computing Drive, Singapore, 117417 Singapore
                [5 ]ISNI 0000 0004 0620 715X, GRID grid.418377.e, Genome Institute of Singapore, ; 60 Biopolis Street, Genome, Singapore, 138672 Singapore
                [6 ]ISNI 0000 0004 1790 4137, GRID grid.35155.37, Hubei Key Laboratory of Agricultural Bioinformatics and Hubei Engineering Technology Research Center of Agricultural Big Data, , Huazhong Agricultural University, ; 1 Shizishan Street, Hongshan District, Wuhan, 430070 Hubei China
                Author information
                http://orcid.org/0000-0002-8065-9707
                http://orcid.org/0000-0001-7806-7086
                http://orcid.org/0000-0003-1601-6640
                http://orcid.org/0000-0003-3985-2545
                Article
                11535
                10.1038/s41467-019-11535-9
                6692402
                31409785
                582205e0-a297-483e-8a95-c8cd34c602d4
                © 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
                : 9 November 2018
                : 19 July 2019
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                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                agricultural genetics,plant genetics,epigenomics
                Uncategorized
                agricultural genetics, plant genetics, epigenomics

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