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(2020) PMID:32213324", "url": "https://www.ncbi.nlm.nih.gov/pubmed/32213324", "date_published": "2020-05-07", "@type": ["Publication", "Item"], "ID": "PMID:32213324", "short_attribution": "Krietenstein N et al. (2020)", "abstract": "Over the past decade, 3C-related methods have provided remarkable insights into chromosome folding in vivo. To overcome the limited resolution of prior studies,  we extend a recently developed Hi-C variant, Micro-C, to map chromosome architecture at nucleosome resolution in human ESCs and fibroblasts. Micro-C robustly captures known features of chromosome folding including compartment organization, topologically associating domains, and interactions between CTCF binding sites. In addition, Micro-C provides a detailed map of nucleosome positions and localizes contact domain boundaries with nucleosomal precision. Compared to Hi-C, Micro-C exhibits an order of magnitude greater dynamic range, allowing the identification of approximately 20,000 additional loops in each cell type. Many newly identified peaks are localized along extrusion stripes and form  transitive grids, consistent with their anchors being pause sites impeding cohesin-dependent loop extrusion. Our analyses comprise the highest-resolution maps of chromosome folding in human cells to date, providing a valuable resource  for studies of chromosome organization.", "authors": ["Krietenstein N", "Abraham S", "Venev SV", "Abdennur N", "Gibcus J", "Hsieh TS", "Parsi KM", "Yang L", "Maehr R", "Mirny LA", "Dekker J", "Rando OJ"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "pubs_using": [{"@id": "/publications/dfc530f1-82c0-4ddc-8f95-6f40417f87a0/", "display_title": "Akgol Oksuz B et al. (2021) PMID:34480151", "status": "current", "uuid": "dfc530f1-82c0-4ddc-8f95-6f40417f87a0", "@type": ["Publication", "Item"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, {"@id": "/publications/6bf7c532-961a-49e1-8fef-0f699d1708ac/", "display_title": "Wang J and Nakato R (2023) PMID:36162821", "status": "current", "uuid": "6bf7c532-961a-49e1-8fef-0f699d1708ac", "@type": ["Publication", "Item"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, {"@id": "/publications/9095d07f-54e7-439c-9e56-9b1487cf9489/", "display_title": "Zhou J (2022) PMID:35551308", "status": "current", "uuid": "9095d07f-54e7-439c-9e56-9b1487cf9489", "@type": ["Publication", "Item"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}], "publications_of_set": [{"@id": "/publications/dfc530f1-82c0-4ddc-8f95-6f40417f87a0/", "authors": ["Akgol Oksuz B", "Yang L", "Abraham S", "Venev SV", "Krietenstein N", "Parsi KM", "Ozadam H", "Oomen ME", "Nand A", "Mao H", "Genga RMJ", "Maehr R", "Rando OJ", "Mirny LA", "Gibcus JH", "Dekker J"], "ID": "PMID:34480151", "date_published": "2021-09", "abstract": "Chromosome conformation capture (3C) assays are used to map chromatin interactions genome-wide. Chromatin interaction maps provide insights into the spatial organization of chromosomes and the mechanisms by which they fold. Hi-C and Micro-C are widely used 3C protocols that differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a  systematic evaluation of 3C experimental parameters. We identified optimal protocol variants for either loop or compartment detection, optimizing fragment size and cross-linking chemistry. We used this knowledge to develop a greatly improved Hi-C protocol (Hi-C 3.0) that can detect both loops and compartments relatively effectively. In addition to providing benchmarked protocols, this work produced ultra-deep chromatin interaction maps using Micro-C, conventional Hi-C and Hi-C 3.0 for key cell lines used by the 4D Nucleome project.", "title": "Systematic evaluation of chromosome conformation capture assays.", "@type": ["Publication", "Item"], "journal": "Nature methods", "uuid": "dfc530f1-82c0-4ddc-8f95-6f40417f87a0", "status": "current", "display_title": "Akgol Oksuz B et al. (2021) PMID:34480151", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, {"@id": "/publications/6bf7c532-961a-49e1-8fef-0f699d1708ac/", "authors": ["Wang J", "Nakato R"], "ID": "PMID:36162821", "date_published": "2023-01-06", "abstract": "Cohesin is a multifunctional protein responsible for transcriptional regulation  and chromatin organization. Cohesin binds to chromatin at tens of thousands of  distinct sites in a conserved or tissue-specific manner, whereas the function of  cohesin varies greatly depending on the epigenetic properties of specific  chromatin loci. Cohesin also extensively mediates cis-regulatory modules (CRMs)  and chromatin loops. Even though next-generation sequencing technologies have  provided a wealth of information on different aspects of cohesin, the integration  and exploration of the resultant massive cohesin datasets are not  straightforward. Here, we present CohesinDB  (https://cohesindb.iqb.u-tokyo.ac.jp), a comprehensive multiomics cohesin  database in human cells. CohesinDB includes 2043 epigenomics, transcriptomics and  3D genomics datasets from 530 studies involving 176 cell types. By integrating  these large-scale data, CohesinDB summarizes three types of 'cohesin objects':  751 590 cohesin binding sites, 957 868 cohesin-related chromatin loops and 2 229  500 cohesin-related CRMs. Each cohesin object is annotated with locus, cell type,  classification, function, 3D genomics and cis-regulatory information. CohesinDB  features a user-friendly interface for browsing, searching, analyzing,  visualizing and downloading the desired information. CohesinDB contributes a  valuable resource for all researchers studying cohesin, epigenomics,  transcriptional regulation and chromatin organization.", "title": "CohesinDB: a comprehensive database for decoding cohesin-related epigenomes, 3D  genomes and transcriptomes in human cells.", "@type": ["Publication", "Item"], "journal": "Nucleic acids research", "uuid": "6bf7c532-961a-49e1-8fef-0f699d1708ac", "status": "current", "display_title": "Wang J and Nakato R (2023) PMID:36162821", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, {"@id": "/publications/a716e6b4-9cfa-4f8d-a2c7-cabf21d42b95/", "authors": ["Krietenstein N", "Abraham S", "Venev SV", "Abdennur N", "Gibcus J", "Hsieh TS", "Parsi KM", "Yang L", "Maehr R", "Mirny LA", "Dekker J", "Rando OJ"], "ID": "PMID:32213324", "date_published": "2020-05-07", "abstract": "Over the past decade, 3C-related methods have provided remarkable insights into chromosome folding in vivo. To overcome the limited resolution of prior studies,  we extend a recently developed Hi-C variant, Micro-C, to map chromosome architecture at nucleosome resolution in human ESCs and fibroblasts. Micro-C robustly captures known features of chromosome folding including compartment organization, topologically associating domains, and interactions between CTCF binding sites. In addition, Micro-C provides a detailed map of nucleosome positions and localizes contact domain boundaries with nucleosomal precision. Compared to Hi-C, Micro-C exhibits an order of magnitude greater dynamic range, allowing the identification of approximately 20,000 additional loops in each cell type. Many newly identified peaks are localized along extrusion stripes and form  transitive grids, consistent with their anchors being pause sites impeding cohesin-dependent loop extrusion. Our analyses comprise the highest-resolution maps of chromosome folding in human cells to date, providing a valuable resource  for studies of chromosome organization.", "title": "Ultrastructural Details of Mammalian Chromosome Architecture.", "@type": ["Publication", "Item"], "journal": "Molecular cell", "uuid": "a716e6b4-9cfa-4f8d-a2c7-cabf21d42b95", "status": "current", "display_title": "Krietenstein N et al. (2020) PMID:32213324", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, {"@id": "/publications/9095d07f-54e7-439c-9e56-9b1487cf9489/", "authors": ["Zhou J"], "ID": "PMID:35551308", "date_published": "2022-05", "abstract": "To learn how genomic sequence influences multiscale three-dimensional (3D) genome  architecture, this manuscript presents a sequence-based deep-learning approach,  Orca, that predicts directly from sequence the 3D genome architecture from  kilobase to whole-chromosome scale. Orca captures the sequence dependencies of  structures including chromatin compartments and topologically associating  domains, as well as diverse types of interactions from CTCF-mediated to  enhancer-promoter interactions and Polycomb-mediated interactions with cell-type  specificity. Orca enables various applications including predicting structural  variant effects on multiscale genome organization and it recapitulated effects of  experimentally studied variants at varying sizes (300 bp to 90 Mb). Moreover,  Orca enables in silico virtual screens to probe the sequence basis of 3D genome  organization at different scales. At the submegabase scale, it predicted specific  transcription factor motifs underlying cell-type-specific genome interactions. At  the compartment scale, virtual screens of sequence activities suggest a model for  the sequence basis of chromatin compartments with a prominent role of  transcription start sites.", "title": "Sequence-based modeling of three-dimensional genome architecture from kilobase to  chromosome scale.", "@type": ["Publication", "Item"], "journal": "Nature genetics", "uuid": "9095d07f-54e7-439c-9e56-9b1487cf9489", "status": "current", "display_title": "Zhou J (2022) PMID:35551308", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}], "number_of_experiments": 9, "@context": "/terms/", "aggregated-items": {"badges": [{"parent": "/biosamples/4DNBSC8TU4XY/", "embedded_path": "experiments_in_set.biosample.badges", "item": {"messages": ["Biosample missing doubling_number"], "badge": {"commendation": null, "warning": "Biosample Metadata Incomplete", "uuid": "2b2cc7ff-b7a8-4138-9a6c-22884fc71690", "@id": "/badges/biosample-metadata-incomplete/", "badge_icon": "/static/img/badges/biosample-icon.svg", "description": "Biosample is missing metadata information required as part of the standards implemented by the 4DN Samples working group."}}}, {"parent": "/biosamples/4DNBSTNNFD79/", "embedded_path": "experiments_in_set.biosample.badges", "item": {"messages": ["Biosample missing doubling_number", "Biosample is a stem cell line over 10 passages but missing karyotype"], "badge": {"commendation": null, "warning": "Biosample Metadata Incomplete", "uuid": "2b2cc7ff-b7a8-4138-9a6c-22884fc71690", "@id": "/badges/biosample-metadata-incomplete/", "badge_icon": "/static/img/badges/biosample-icon.svg", "description": "Biosample is missing metadata information required as part of the standards implemented by the 4DN Samples working group."}}}]}, "validation-errors": []}