Abstract
Quantitative models of cis-regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled, or heuristic approximations of the underlying regulatory mechanisms. We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Using this model on segmentation-related enhancers in Drosophila, we find that transcriptional synergy due to simultaneous action of multiple activators helps explain the data beyond what can be explained by cooperative DNA-binding alone. We find clear support for the phenomenon of short-range repression, where repressors do not directly interact with the basal transcriptional machinery. We also find that the binding sites contributing to an enhancer's function may not be conserved during evolution, and a noticeable fraction of these undergo lineage-specific changes. Our implementation of the model, called GEMSTAT, is the first publicly available program for simultaneously modeling the regulatory activities of a given set of sequences.
Highlights
Transcriptional gene regulation is largely achieved by binding of transcription factors (TFs) to their cognate sites in regulatory sequences, followed by interaction of the bound factors with the basal transcriptional machinery
We found that the transcriptional synergy arising from simultaneous contact of activators with the basal transcriptional machinery (BTM) contributes significantly to the accurate specification of expression patterns, and this contribution extends beyond the contribution from mutual interactions (DNA-binding cooperativity) between activators
We found evidence in favor of a short range repression mechanism for two of the TFs, consolidating experimental evidence that exists for this mechanism
Summary
Transcriptional gene regulation is largely achieved by binding of transcription factors (TFs) to their cognate sites in regulatory sequences (called binding sites), followed by interaction of the bound factors with the basal transcriptional machinery. Tools of genetics and molecular biology have been used through years of painstaking experimentation to reveal examples of CRMs and their regulatory interactions with TFs [1]. Despite the empirical knowledge of such examples, our understanding of the rules by which various TFs, some activators and others repressors, work together to drive the precise expression pattern of a gene remains rudimentary. Biochemical experiments [2] and genetic assays of synthetic CRMs [3,4] have been two successful paradigms for exploring the mechanisms of transcriptional regulation. There is widespread recognition [4] that such experimental paradigms need to be complemented with quantitative analyses, since the underlying rules of combinatorial regulation are themselves quantitative in nature. It may allow us to predict the function of an uncharacterized piece of DNA, and may be harnessed to discover novel CRMs in a genome, as well as to predict the expression pattern driven by a known CRM in conditions where aspects of the input information differ from those in wild type
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