Computational identification of diverse mechanisms underlying transcription factor-DNA occupancy.
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.
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Qiong
Q
Cheng
Majid
M
Kazemian
Hannah
H
Pham
Charles
C
Blatti
Susan E
SE
Celniker
Scot A
SA
Wolfe
Michael H
MH
Brodsky
Saurabh
S
Sinha
D000465:Algorithms; D000818:Animals; D001665:Binding Sites; D042002:Chromatin Assembly and Disassembly / Q000235:genetics; D019295:Computational Biology; D004247:DNA / Q000235:genetics*; D004268:DNA-Binding Proteins / Q000235:genetics*; D004330:Drosophila / Q000235:genetics* / Q000254:growth & development; D047108:Embryonic Development / Q000235:genetics*; D018507:Gene Expression Regulation, Developmental; D016678:Genome; D014157:Transcription Factors / Q000235:genetics*
D004268:DNA-Binding Proteins; D014157:Transcription Factors; D004247:DNA