{"lab": {"uuid": "53f8d746-0c48-4151-92a0-2d24ad28cb5a", "@id": "/labs/christine-disteche-lab/", "@type": ["Lab", "Item"], "correspondence": [{"contact_email": "Y2Rpc3RlY2hAdS53YXNoaW5ndG9uLmVkdQ==", "@id": "/users/d89fb49f-f068-43c3-8e3c-6b1c68757a53/", "display_title": "Christine Disteche"}], "title": "Christine Disteche, UW", "display_title": "Christine Disteche, UW", "status": "current", "pi": {"error": "no view permissions"}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.lab_submitter", "submits_for.53f8d746-0c48-4151-92a0-2d24ad28cb5a"]}}, "award": {"@id": "/awards/1U54DK107979-01/", "description": "NOFIC: A current grand challenge in genomics involves accurately assaying, at all relevant scales, the 3D conformation of DNA in vivo and then linking conformational changes to dynamic processes such as the cell cycle, differentiation and disease. Here we propose to create the University of Washington Center for Nuclear Organization and Function, bringing together an interdisciplinary team of investigators whose diverse areas of expertise - technology development, computational modeling, and mouse and human biology - make them ideally suited to this challenge. Our overall hypothesis is that characterizing and understanding changes in genome architecture over time (the 4D nucleome) will lead to fundamental insights into human biology and disease. We will address this hypothesis by developing a combination of experimental and computational methods development, coupled with their systematic biological validation and application to development- and disease-relevant systems. On the experimental side, we will further optimize our recently developed DNase Hi- C assay, including combinatorial methods for single cells, ultimately aiming to concurrently assay nuclear architecture and gene expression within each of many single cells. On the computational side, we will extend our existing 3D modeling algorithms to account for diploidy, cell-to-cell variabilit, the hierarchical nature of genome architecture, and to explicitly model architectural changes over cell cycle and cell differentiation time scales. We will then employ several complementary computational methods to link our 4D nucleome models to existing, 1D genomics data sets. The outputs of these new experimental and computational technologies will be subjected to orthogonal validation in several well-understood model systems: human cell lines, in vivo tissues from interspecific F1 hybrid mice, mouse embryonic stem cells (ESCs) and skeletal myoblasts. We will also test specific predictions of the models in response to targeted (genome editing) or large-scale (chromosome silencing) perturbations. After initial validation and in parallel with further methods development, we will apply our new tools to the analysis of three biological systems: we will characterize the dynamics of nuclear architecture during the directed differentiation of na\u00efve human ESCs into cardiomyocytes and endothelial cells; we will test the hypothesis that cardiomyopathy-inducing mutations in the nuclear scaffolding protein, lamin A, are associated with derangements in cardiomyocyte nuclear architecture; and we will determine the changes in human cardiomyocyte nuclear architecture induced by trisomy 21. The proposed center will produce new experimental protocols for ascertaining 4D nucleome architecture, two new software toolkits for modeling the 4D nucleome and linking features of the nucleome to other types of genomic data, a variety of publicly available, large-scale 4D nucleome data sets in mouse and human systems, and fundamental insights into human biology and disease. In all of this work, we will work closely and openly with NOFIC and the 4DN Network to maximize the impact of our center and the overall program.", "name": "1U54DK107979-01", "display_title": "UNIVERSITY OF WASHINGTON CENTER FOR NUCLEAR ORGANIZATION AND FUNCTION", "uuid": "fcc7f634-9252-499f-b79c-380795af2ddd", "@type": ["Award", "Item"], "status": "current", "center_title": "NOFIC - Shendure", "project": "4DN", "pi": {"error": "no view permissions"}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "badges": [{"badge": {"badge_icon": "/static/img/badges/replicates-orange-circle.svg", "@id": "/badges/replicate-numbers/", "badge_classification": "Warning", "display_title": "Replicate Numbers", "description": "Issues with replicate numbers", "warning": "Replicate Numbers", "status": "released", "uuid": "24a64a84-3c33-4d76-aaf2-e5ef45eff347", "@type": ["Badge", "Item"], "title": "Replicate Numbers", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "messages": ["Replicate set contains only a single biological replicate"]}], "status": "released", "aliases": ["disteche_lab:F123_EB_differentiation_day7_scihic_experiment_C_repset"], "accession": "4DNESWTC3W7N", "condition": "Embryoid body day 7", "description": "Replicate Set of sciHi-C on F123 cells Timecourse #2 - day 7 of embryoid body differentiation - this Replicate Set is derived from experiments performed on pooled mixtures of F123 cells undergoing differentiation to embryoid bodies. Cells are harvested on specific days over the time course of differentiation. The raw files linked to the experiments in this set will contain reads from multiple time points and barcode information needs to used to obtain cell specific reads - see details in the experiment descriptions. Processed files for this set will be specific to day 7 of differentiation.", "date_created": "2020-11-07T02:30:39.555443+00:00", "submitted_by": {"error": "no view permissions"}, "dataset_label": "sciHi-C on F123 cells", "last_modified": {"modified_by": {"error": "no view permissions"}, "date_modified": "2020-11-25T18:45:14.573820+00:00"}, "public_release": "2020-11-25", "replicate_exps": [{"bio_rep_no": 1, "tec_rep_no": 1, "replicate_exp": {"display_title": "sci-Hi-C on F123-CASTx129 differentiated to embryoid body with DpnII - 4DNEX1BY7H2C", "@type": ["ExperimentHiC", "Experiment", "Item"], "accession": "4DNEX1BY7H2C", "@id": "/experiments-hi-c/4DNEX1BY7H2C/", "uuid": "4744c5fc-b81a-4a34-9376-e9a7cd8b3d3b", "status": "released", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}}], "schema_version": "2", "static_headers": [{"lab": {"display_title": "4DN DCIC, HMS", "@id": "/labs/4dn-dcic-lab/", "@type": ["Lab", "Item"], "uuid": "828cd4fe-ebb0-4b36-a94a-d2e3a36cc989", "status": "current", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.lab_submitter", "submits_for.828cd4fe-ebb0-4b36-a94a-d2e3a36cc989"]}}, "body": "**Sci-Hi-C**\n\n\nSci-Hi-C is a method to detect and quantify chromatin interactions in large numbers of single cells. This massively multiplexed method was developed in 2017 and it enables characterization of 3D genome architecture in thousands of single cells in parallel without requiring compartmentalization of each cell or microfluidic manipulation.\n\nThis protocol involves cross-linking the cells with formaldehyde. The cells are then permeabilized with their nuclei intact. A 4-cutter restriction enzyme DpnII is used to fragment the chromatin. Nuclei are then distributed to 96 wells, wherein the first barcode is introduced through ligation of barcoded biotinylated double-stranded bridge adaptors. Intact nuclei are then pooled and subjected to proximity ligation, followed by dilution and redistribution to a second 96-well plate. Importantly, this dilution is carried out such that each well in this second plate contains at most 25 nuclei. Following lysis, a second barcode is introduced through ligation of barcoded Y-adaptors. As the number of barcode combinations (96 \u00d7 96) exceeds the number of nuclei (96 \u00d7 25), the vast majority of single nuclei are tagged by a unique combination of barcodes. All material is once again pooled, and biotinylated junctions are purified with streptavidin beads, restriction digested, and further processed to Illumina sequencing libraries. Sequencing these molecules with relatively long paired-end reads (i.e., 2 \u00d7 250 base pairs) allows one to identify not only the genome-derived fragments of conventional Hi-C, but also external and internal barcodes, which enable decomposition of the Hi-C data into single-cell contact probability maps.\n\n\nSee [Ramani et al 2017](https://www.nature.com/articles/nmeth.4155) for more details on in sci-Hi-C.\n\n
Sci-Hi-C
\nSci-Hi-C is a method to detect and quantify chromatin interactions in large numbers of single cells. This massively multiplexed method was developed in 2017 and it enables characterization of 3D genome architecture in thousands of single cells in parallel without requiring compartmentalization of each cell or microfluidic manipulation.
\nThis protocol involves cross-linking the cells with formaldehyde. The cells are then permeabilized with their nuclei intact. A 4-cutter restriction enzyme DpnII is used to fragment the chromatin. Nuclei are then distributed to 96 wells, wherein the first barcode is introduced through ligation of barcoded biotinylated double-stranded bridge adaptors. Intact nuclei are then pooled and subjected to proximity ligation, followed by dilution and redistribution to a second 96-well plate. Importantly, this dilution is carried out such that each well in this second plate contains at most 25 nuclei. Following lysis, a second barcode is introduced through ligation of barcoded Y-adaptors. As the number of barcode combinations (96 \u00d7 96) exceeds the number of nuclei (96 \u00d7 25), the vast majority of single nuclei are tagged by a unique combination of barcodes. All material is once again pooled, and biotinylated junctions are purified with streptavidin beads, restriction digested, and further processed to Illumina sequencing libraries. Sequencing these molecules with relatively long paired-end reads (i.e., 2 \u00d7 250 base pairs) allows one to identify not only the genome-derived fragments of conventional Hi-C, but also external and internal barcodes, which enable decomposition of the Hi-C data into single-cell contact probability maps.
\nSee Ramani et al 2017 for more details on in sci-Hi-C.
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