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

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.

doi:10.1016/j.celrep.2020.108029

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

Journal Article · Tue Aug 18 00:00:00 EDT 2020 · Cell Reports

DOI:https://doi.org/10.1016/j.celrep.2020.108029· OSTI ID:1774294

Funk, Cory C. ^[1]; ^[2]; Jung, Segun ^[3]; Richards, Matthew A. ^[1]; Rodriguez, Alex ^[3]; Shannon, Paul ^[1]; Donovan-Maiye, Rory ^[1]; ^[1]; Chard, Kyle ^[3]; Xiao, Yukai ^[3]; ^[1]; Ertekin-Taner, Nilufer ^[4]; ^[4]; Toga, Arthur ^[5]; Hood, Leroy ^[1]; Van Horn, John D. ^[5]; Kesselman, Carl ^[5]; ^[6]; ^[6]; Price, Nathan D. ^[1] more »

Institute for Systems Biology, Seattle, WA (United States)
Univ. of Maryland School of Medicine, Baltimore, MD (United States)
Univ. of Chicago, IL (United States)
Mayo Clinic, Jacksonville, FL (United States)
Univ. of Southern California, Los Angeles, CA (United States)
Univ. of Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)

Characterizing 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.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: National Human Genome Research Institute (NHGRI); National Institute of General Medical Sciences (NIGMS); National Institute of Mental Health (NIMH); National Institute on Aging (NIA); National Institutes of Health (NIH); USDOE

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1774294

Journal Information:: Cell Reports, Journal Name: Cell Reports Journal Issue: 7 Vol. 32; ISSN 2211-1247

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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59 BASIC BIOLOGICAL SCIENCES
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psychiatric genetics
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Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types

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References (53)

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