Christina Leslie, MSKCC

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    "fax": "(646)888-2762",
    "institute_label": "MSKCC",
    "address1": "",
    "state": "NY",
    "institute_name": "Memorial Sloan-Kettering Cancer Center",
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            "schema_version": "11",
            "title": "DECODING IN VIVO REGULATORY PROGRAMS OF CD4+ T LYMPHOCYTE POPULATIONS IN INFLAMMA",
            "name": "U01HG007893",
            "description": "In multicellular organisms, differentiated cells exhibit specialized functions that are specified by distinct transcriptional and epigenetic programs. Differential use of regulatory elements defines most previously studied lineage specific gene expression programs. However, challenges such as stress, injury, or infection can elicit adaptive or pathogenic responses in differentiated cells leading to a change in their functional state and transcriptional output. Cells of the immune system offer a powerful experimental model for dissection of genomic mechanisms underlying establishment of distinct differentiation and activation states. In this proposal, we study distinct CD4+ T cell populations as they transition from \"na¿ve\" (or resting) to activated states with opposing function: effector T cells that promote - and activated regulatory T cells (Treg) that suppress - immune response and associated inflammation. Resting Treg cells emerge during differentiation as a stable lineage of T lymphocytes distinct from na¿ve CD4+ T cells. We will use sophisticated genetic mouse models to generate a short-term inflammatory disorder and investigate genomic features of activated Treg and T effector cells and their resting counterparts in an inflammatory context in vivo. We will profile the enhancer and transcriptional landscapes of the four cell states using DNase-seq, TF and histone modification ChIP-seq, and bulk and single-cell RNA-seq profiles from ex vivo isolated cells. Using these comprehensive data sets, we will: (1) decode the changes in the enhancer landscape that govern the activation of distinct CD4+ T lymphocyte populations; (2) model the differential transcriptional output of genes in these cells as a function of the sequence and activity of their enhancers; and (3) model the expression distribution of individual genes over a population of cells as a function of the state space of their enhancers. Given the central role that Treg cells play in suppressing immune-mediated inflammation in diverse biological contexts ranging from autoimmunity, injury, and infection to pregnancy and metabolic disease as well as emerging understanding of their pivotal role in cancer, our study has broad relevance to human health and major practical significance.",
            "start_date": "2015-01-05",
            "end_date": "2017-11-30",
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            "rfa": "GGR",
            "project": "GGR",
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            "url": "https://projectreporter.nih.gov/project_info_description.cfm?aid=9247342&icde=32923373&ddparam=&ddvalue=&ddsub=&cr=1&csb=default&cs=ASC&pball=",
            "schema_version": "11",
            "title": "ENCODING GENOMIC ARCHITECTURE IN THE ENCYCLOPEDIA: LINKING DNA ELEMENTS, CHROMATIN STATE, AND GENE EXPRESSION IN 3D",
            "name": "U01HG009395",
            "description": "Most of the 1000s of sequencing experiments generated by ENCODE provide 1D readouts of the epigenetic landscape or transcriptional output of a 3D genome. New chromosome conformation capture (3C) technologies – in particular Hi-C and ChIA-PET – have begun to provide insight into the hierarchical 3D organization of the genome: the partition of chromosomes into open and closed compartments; the existence of structural subunits defined as topologically associated domains (TADs); and the presence of regulatory and structural DNA loops within TADs. New experimental evidence using CRISPR/Cas-mediated genome editing suggests that disruption of local 3D structure can alter regulation of neighboring genes, and there have been early efforts to use data on 3D DNA looping to predict the impact of non-coding SNPs from GWAS studies. The goal of this proposal is to develop new integrative computational methods to interpret large-scale ENCODE 1D epigenomic and transcriptomic resources in light of the underlying 3D architecture of the genome. Members of our team have pioneered powerful methods to infer local chromatin states from a 1D viewpoint through the Segway suite. We have also analyzed the 1D organization of chromatin accessible elements and their lineage dynamics to define the concept of regulatory complexity, and we presented a gene regulation model to predict gene expression changes in differentiation from the DNA content of active enhancers. Here we will build on these efforts to learn chromatin state and gene regulation models that incorporate information on hierarchical 3D genomic architecture, enabling us to predict how individual structural/regulatory elements contribute to 3D DNA looping and to gene expression. Mechanistic predictions will be experimentally validated in their native cell-type specific chromatin context using state-of-the-art genome editing, exploiting computational and experimental CRISPR/Cas tools developed by our team.",
            "start_date": "2017-02-01",
            "end_date": "2021-01-31",
            "pi": "/users/a9d259df-9fd8-4348-b446-f1893e64b72b/",
            "rfa": "ENCODE4",
            "project": "ENCODE",
            "viewing_group": "ENCODE4",
            "component": "computational analysis",
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    "title": "Christina Leslie, MSKCC",
    "phone1": "(646)888-2762",
    "phone2": "",
    "schema_version": "5",
    "pi": "/users/a9d259df-9fd8-4348-b446-f1893e64b72b/",
    "postal_code": "10065",
    "name": "christina-leslie",
    "city": "New York",
    "country": "USA",
    "status": "current",
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