Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data
- Kaixuan Luo1,2,3,4,
- Jianling Zhong1,2,3,
- Alexias Safi2,5,
- Linda K. Hong2,5,
- Alok K. Tewari6,
- Lingyun Song2,5,
- Timothy E. Reddy1,2,7,8,9,
- Li Ma1,10,
- Gregory E. Crawford1,2,5 and
- Alexander J. Hartemink1,2,3,11
- 1Computational Biology & Bioinformatics Graduate Program, Duke University, Durham, North Carolina 27708, USA;
- 2Center for Genomic and Computational Biology, Duke University, Durham, North Carolina 27708, USA;
- 3Department of Computer Science, Duke University, Durham, North Carolina 27708, USA;
- 4Department of Human Genetics, The University of Chicago, Chicago, Illinois 60637, USA;
- 5Department of Pediatrics, Duke University Medical Center, Durham, North Carolina 27710, USA;
- 6Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA;
- 7Department of Biostatistics and Bioinformatics, Durham, North Carolina 27710, USA;
- 8Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina 27710, USA;
- 9Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, USA;
- 10Department of Statistical Science, Duke University, Durham, North Carolina 27708, USA;
- 11Department of Biology, Duke University, Durham, North Carolina 27708, USA
Abstract
Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.272203.120.
- Received September 30, 2020.
- Accepted May 6, 2022.
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see https://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
