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 …

Date

August 18, 2020

Authors

Cory C Funk, Alex M Casella, Segun Jung, Matthew A Richards, Alex Rodriguez, Paul Shannon, Rory Donovan-Maiye, Ben Heavner, Kyle Chard, Yukai Xiao, Gustavo Glusman, Nilufer Ertekin-Taner, Todd E Golde, Arthur Toga, Leroy Hood, John D Van Horn, Carl Kesselman, Ian Foster, Ravi Madduri, Nathan D Price, Seth A Ament

Journal

Cell reports

Volume

32

Issue

7

Publisher

Elsevier