1. Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types.
- Author
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Funk CC, Casella AM, Jung S, Richards MA, Rodriguez A, Shannon P, Donovan-Maiye R, Heavner B, Chard K, Xiao Y, Glusman G, Ertekin-Taner N, Golde TE, Toga A, Hood L, Van Horn JD, Kesselman C, Foster I, Madduri R, Price ND, and Ament SA
- Subjects
- Humans, Binding Sites genetics, Deoxyribonucleases metabolism, Genomics methods, Transcription Factors metabolism
- Abstract
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., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2020
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