Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types
AuthorFunk, Cory C.
Casella, Alex M.
Richards, Matthew A.
Golde, Todd E.
Van Horn, John D.
Price, Nathan D.
Ament, Seth A.
MetadataShow full item record
AbstractDNase-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
SponsorsNational Human Genome Research Institute
Identifier to cite or link to this itemhttp://hdl.handle.net/10713/13681