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Computational Identification of Diverse Mechanisms Underlying Transcription Factor-DNA Occupancy

Journal Article · · PLoS Genetics
 [1];  [2];  [3];  [2];  [4];  [5];  [6];  [7]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Computer Science; DOE/OSTI
  2. Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Computer Science
  3. Univ. of Massachusetts, Worcester, MA (United States). Medical School. Program in Gene Function and Expression
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Berkeley Drosophila Genome Project. Dept. of Genome Dynamics
  5. Univ. of Massachusetts, Worcester, MA (United States). Medical School. Program in Gene Function and Expression; Univ. of Massachusetts, Worcester, MA (United States). Dept. of Biochemistry and Molecular Pharmacology
  6. Univ. of Massachusetts, Worcester, MA (United States). Medical School. Program in Gene Function and Expression; Univ. of Massachusetts, Worcester, MA (United States). Medical School. Dept. of Molecular Medicine
  7. Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Computer Science; Univ. of Illinois at Urbana-Champaign, IL (United States). Inst. of Genomic Biology
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ChIP-based genome-wide assays of transcription factor (TF) occupancy have emerged as a powerful, high-throughput method to understand transcriptional regulation, especially on a global scale. This has led to great interest in the underlying biochemical mechanisms that direct TF-DNA binding, with the ultimate goal of computationally predicting a TF’s occupancy profile in any cellular condition. In this study, we examined the influence of various potential determinants of TF-DNA binding on a much larger scale than previously undertaken. We used a thermodynamics-based model of TF-DNA binding, called ‘‘STAP,’’ to analyze 45 TF-ChIP data sets from Drosophila embryonic development. We built a cross-validation framework that compares a baseline model, based on the ChIP’ed (‘‘primary’’) TF’s motif, to more complex models where binding by secondary TFs is hypothesized to influence the primary TF’s occupancy. Candidates interacting TFs were chosen based on RNA-SEQ expression data from the time point of the ChIP experiment. We found widespread evidence of both cooperative and antagonistic effects by secondary TFs, and explicitly quantified these effects. We were able to identify multiple classes of interactions, including (1) long-range interactions between primary and secondary motifs (separated by #150 bp), suggestive of indirect effects such as chromatin remodeling, (2) short-range interactions with specific inter-site spacing biases, suggestive of direct physical interactions, and (3) overlapping binding sites suggesting competitive binding. Furthermore, by factoring out the previously reported strong correlation between TF occupancy and DNA accessibility, we were able to categorize the effects into those that are likely to be mediated by the secondary TF’s effect on local accessibility and those that utilize accessibility-independent mechanisms. Finally, we conducted in vitro pull-down assays to test model-based predictions of short-range cooperative interactions, and found that seven of the eight TF pairs tested physically interact and that some of these interactions mediate cooperative binding to DNA.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1627300
Journal Information:
PLoS Genetics, Journal Name: PLoS Genetics Journal Issue: 8 Vol. 9; ISSN 1553-7404
Publisher:
Public Library of ScienceCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (17)

The Role of Chromatin Accessibility in cis-Regulatory Evolution journal May 2019
Simulations of Enhancer Evolution Provide Mechanistic Insights into Gene Regulation journal October 2013
Optimization of transcription factor binding map accuracy utilizing knockout-mouse models journal November 2014
An improved predictive recognition model for Cys2-His2 zinc finger proteins journal February 2014
Quantitative modeling of gene expression using DNA shape features of binding sites journal June 2016
ChIPulate : A comprehensive ChIP-seq simulation pipeline posted_content February 2019
Inferring condition-specific targets of human TF-TF complexes using ChIP-seq data journal January 2017
Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response journal July 2019
Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast journal August 2015
Contextual Refinement of Regulatory Targets Reveals Effects on Breast Cancer Prognosis of the Regulome journal January 2017
Differential Nucleosome Occupancies across Oct4-Sox2 Binding Sites in Murine Embryonic Stem Cells journal May 2015
Integrative analysis of public ChIP-seq experiments reveals a complex multi-cell regulatory landscape journal December 2014
The role of chromatin accessibility in cis-regulatory evolution journal October 2018
Deep learning at base-resolution reveals motif syntax of the cis-regulatory code journal July 2020
The Role of Genome Accessibility in Transcription Factor Binding in Bacteria journal April 2016
ChIPulate: A comprehensive ChIP-seq simulation pipeline journal March 2019
The Role of Genome Accessibility in Transcription Factor Binding in Bacteria text January 2016

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