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    Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types

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    Author
    Funk, Cory C.
    Casella, Alex M.
    Jung, Segun
    Richards, Matthew A.
    Rodriguez, Alex
    Shannon, Paul
    Donovan-Maiye, Rory
    Heavner, Ben
    Chard, Kyle
    Xiao, Yukai
    Glusman, Gustavo
    Ertekin-Taner, Nilufer
    Golde, Todd E.
    Toga, Arthur
    Hood, Leroy
    Van Horn, John D.
    Kesselman, Carl
    Foster, Ian
    Madduri, Ravi
    Price, Nathan D.
    Ament, Seth A.
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    Date
    2020-08-18
    Journal
    Cell Reports
    Publisher
    Elsevier B.V.
    Type
    Article
    
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    See at
    https://doi.org/10.1016/j.celrep.2020.108029
    Abstract
    DNase-seq footprinting provides a means to predict genome-wide binding sites for hundreds of transcription factors (TFs) simultaneously. Funk et al. analyze data from the ENCODE consortium to create a resource of footprints in 27 human tissues, demonstrating associations of tissue-specific TF occupancy with gene regulation and disease risk. © 2020 The AuthorsCharacterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking. Here, we develop a scalable footprinting workflow using two state-of-the-art algorithms: Wellington and HINT. We apply our workflow to detect footprints in 192 ENCODE DNase-seq experiments and predict the genomic occupancy of 1,515 human TFs in 27 human tissues. We validate that these footprints overlap true-positive TF binding sites from ChIP-seq. We demonstrate that the locations, depth, and tissue specificity of footprints predict effects of genetic variants on gene expression and capture a substantial proportion of genetic risk for complex traits. © 2020 The Authors
    Sponsors
    National Human Genome Research Institute
    Keyword
    DNase-seq
    ENCODE
    footprinting
    gene regulation
    motifs
    psychiatric genetics
    transcription factors
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/13681
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.celrep.2020.108029
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