ArticlePLoS computational biology2010
Thermodynamics-based models of transcriptional regulation by enhancers: the roles of synergistic activation, cooperative binding and short-range repression.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
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Who cites it
107 citing papers in PubMed.
- Cooperativity enables widespread role of low-affinity motifs in chromatin accessibility and increases regulatory potential.Cell genomics · 2026Article
- Widespread low-affinity motifs enhance chromatin accessibility and regulatory potential in mESCs.bioRxiv : the preprint server for biology · 2025Article
- Characterizing the regulatory logic of transcriptional control at the DNA sequence level by ensembles of thermodynamic models.Bioinformatics (Oxford, England) · 2025Article
- The Hallmarks of Aneuploidy in Cancer and Congenital Syndromes.Annual review of genomics and human genetics · 2025Review
- Experimental approaches to investigate biophysical interactions between homeodomain transcription factors and DNA.Biochimica et biophysica acta. Gene regulatory mechanisms · 2025Review
- Two coacting shadow enhancers regulate twin of eyeless expression during early Drosophila development.Genetics · 2025Article
- An enhanced BERT model with improved local feature extraction and long-range dependency capture in promoter prediction for hearing loss.PeerJ. Computer science · 2025Article
- Deciphering regulatory architectures of bacterial promoters from synthetic expression patterns.PLoS computational biology · 2024Article
- Developmental and housekeeping transcriptional programs display distinct modes of enhancer-enhancer cooperativity in Drosophila.Nature communications · 2024Article
- Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases.Human molecular genetics · 2024Article
- AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors.Molecules (Basel, Switzerland) · 2024Review
- Mechanistic analysis of enhancer sequences in the estrogen receptor transcriptional program.Communications biology · 2024Article
- Regulatory properties of transcription factors with diverse mechanistic function.PLoS computational biology · 2024Article
- Cell-type-directed design of synthetic enhancers.Nature · 2024Article
- A transcriptomic atlas of acute stress response to low pH in multipleMicrobiology spectrum · 2024Article
- SEAMoD: A fully interpretable neural network for cis-regulatory analysis of differentially expressed genes.bioRxiv : the preprint server for biology · 2023Article
- Multinomial Convolutions for Joint Modeling of Regulatory Motifs and Sequence Activity Readouts.Genes · 2022Article
- Concentration-dependent transcriptional switching through a collective action of cis-elements.Science advances · 2022Article
- A synthetic synthesis to explore animal evolution and development.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Review
- Thermodynamics-based modeling reveals regulatory effects of indirect transcription factor-DNA binding.iScience · 2022Article
47 more citing papers are in PubMed but not listed here.
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4 authors.
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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.
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