{"ID": "PMID:28358394", "lab": {"title": "Yijun Ruan, JAX", "uuid": "abd48785-b0e5-4453-be14-30d37a516bf3", "@type": ["Lab", "Item"], "display_title": "Yijun Ruan, JAX", "@id": "/labs/yijun-ruan-lab/", "correspondence": [{"contact_email": "eWlqdW4ucnVhbkBqYXgub3Jn", "@id": "/users/d8ac229e-ec08-4411-be38-dc779520ea62/", "display_title": "Yijun Ruan"}], "status": "current", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.lab_submitter", "submits_for.abd48785-b0e5-4453-be14-30d37a516bf3"]}, "pi": {"error": "no view permissions"}}, "url": "https://www.ncbi.nlm.nih.gov/pubmed/28358394", "award": {"status": "current", "display_title": "NUCLEOME POSITIONING SYSTEM FOR SPATIOTEMPORAL GENOME ORGANIZATION AND REGULATION", "description": "NOFIC: This proposal seeks to fulfill a community need for a comprehensive, high-resolution genome-mapping platform that will enable investigation of the structural, functional and spatiotemporal organization of the human genome. Our ultimate goal is to deliver complex chromatin interaction network maps in the context of 3D genome structures from which the dynamics of individual genomic elements can be monitored and referenced. Here, we propose to develop a Nucleome Positioning System (NPS)-comprised of 1) a robust genome- wide mapping technology platform, 2) advanced computational modeling algorithms and 3) state-of-the-art nuclear imaging methods-that will allow users community-wide to uncover the regulatory functions of 3D genome organization in human cells. NPS will be based upon the established ChIA-PET method (1,2), enhanced by process optimizations-i.e., microfluidic-based miniaturization and Tn5-transposase-based library preparation-to facilitate the study of chromatin interactions mediated by protein factors across a broader range of human cell types (Aim 1, see also Mapping Technology Development Component). We will also optimize RICh-PET for the comprehensive mapping of chromatin interactions mediated by non-coding RNAs (Aim 1). The high-quality mapping data generated through these optimization efforts will be analyzed by a new computational platform (Three-Dimensional Nucleome Modeling Engine, or 3D-NOME) that makes use of hierarchical multi-scaling to model 3D genome structures (Aim 2, Data Analysis and Modeling component). We will also complement the 3D modeling with transcriptome, epigenome and SNP data associated with genetic diseases (GWAS) to provide functional annotation to structural units (Aim 2). We will continue by developing strategies to validate the nucleome geometry predicted by 3D-NOME both structurally, using new nuclear imaging technologies, and functionally, using cutting-edge genome- and epigenome-editing approaches, in both human cell lines and mouse models (Aim 3, Biological Validation Component). Finally, we will implement NPS to generate pilot 3D genome maps from a wide range of human cell lines and primary immune cells sorted from whole blood, to elucidate the spatiotemporal dynamics of human genome organization over major developmental and hematopoietic cell lineages, as well as among differentiating lymphocytes involved in the immune response (Aim 4, Data Generation Component). Together, these efforts will yield a powerful set of sophisticated, high-quality tools and mapping data for the larger research community, and will help establish the standards for future 3D/4D nucleome studies. They will also provide insights into the broad mechanisms that organize the structure and regulate the function of the human genome, as well as the specific mechanisms by which immune responses are regulated at the nuclear level.", "center_title": "NOFIC - Ruan", "name": "1U54DK107967-01", "project": "4DN", "uuid": "029a2578-43dc-4343-8f41-694518cce304", "@type": ["Award", "Item"], "@id": "/awards/1U54DK107967-01/", "pi": {"error": "no view permissions"}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "title": "Long-read ChIA-PET for base-pair-resolution mapping of haplotype-specific chromatin interactions.", "status": "current", "aliases": ["4dn-dcic-lab:long-read-chia-pet-pub"], "authors": ["Li X", "Luo OJ", "Wang P", "Zheng M", "Wang D", "Piecuch E", "Zhu JJ", "Tian SZ", "Tang Z", "Li G", "Ruan Y"], "journal": "Nature protocols", "abstract": "Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is a robust method for capturing genome-wide chromatin interactions. Unlike other 3C-based methods, it includes a chromatin immunoprecipitation (ChIP) step that enriches for interactions mediated by specific target proteins. This unique feature allows ChIA-PET to provide the functional specificity and higher resolution needed to detect chromatin interactions, which chromosome conformation capture (3C)/Hi-C approaches have not achieved. The original ChIA-PET protocol generates short paired-end tags (2 x 20 base pairs (bp)) to detect two genomic loci that are far apart on linear chromosomes but are in spatial proximity in the folded genome. We have improved the original approach by developing long-read ChIA-PET, in which the length of the paired-end tags is increased (up to 2 x 250  bp). The longer PET reads not only improve the tag-mapping efficiency but also increase the probability of covering phased single-nucleotide polymorphisms (SNPs), which allows haplotype-specific chromatin interactions to be identified.  Here, we provide the detailed protocol for long-read ChIA-PET that includes cell  fixation and lysis, chromatin fragmentation by sonication, ChIP, proximity ligation with a bridge linker, Tn5 tagmentation, PCR amplification and high-throughput sequencing. For a well-trained molecular biologist, it typically  takes 6 d from cell harvesting to the completion of library construction, up to a further 36 h for DNA sequencing and <20 h for processing of raw sequencing reads.", "categories": ["methods paper"], "date_created": "2019-11-20T16:11:29.962031+00:00", "submitted_by": {"error": "no view permissions"}, "last_modified": {"modified_by": {"error": "no view permissions"}, "date_modified": "2019-11-20T16:14:10.753592+00:00"}, "date_published": "2017-05", "public_release": "2019-11-20", "schema_version": "2", "project_release": "2019-11-20", "@id": "/publications/fb5cd1c5-942e-4da0-a7c8-d559fa6d6b47/", "@type": ["Publication", "Item"], "uuid": "fb5cd1c5-942e-4da0-a7c8-d559fa6d6b47", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}, "display_title": "Li X et al. (2017) PMID:28358394", "external_references": [], "short_attribution": "Li X et al. (2017)", "@context": "/terms/", "aggregated-items": {}, "validation-errors": []}