Abstract
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.
Highlights
A major challenge in the analysis of genomic sequences is the annotation of cis-regulatory elements
Chromatin Immunoprecipitation (ChIP)-based genomewide assays of transcription factor (TF) occupancy have emerged as a powerful, high throughput method to understand transcriptional regulation, especially on a global scale
Our findings provide robust statistical evidence of the role played by TF-TF interactions in shaping genome-wide TFDNA binding profiles, and in directing gene regulation
Summary
A major challenge in the analysis of genomic sequences is the annotation of cis-regulatory elements. A number of genome-wide ChIP data sets, corresponding to diverse TFs and cellular conditions, have been generated through the efforts of various laboratories and consortia [1,3]. Such data sets offer the opportunity to apply computational and statistical methods to understand the determinants of TFDNA binding at a quantitative level [5,6,7]. Given the central role of the TF-DNA binding process in the regulatory activity of a TF, such an understanding can provide a holistic view of transcriptional regulation and set the stage for future computational methods for predicting cell type-specific TF-binding profiles
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