ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2014
Statistical mechanical model of coupled transcription from multiple promoters due to transcription factor titration.
Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 49 citations in OpenAlex.
- Tuning Ultrasensitivity in Genetic Logic Gates Using Antisense RNA Feedback.ACS synthetic biology · 2025Article
- A parameterized two-domain thermodynamic model explains diverse mutational effects on protein allostery.eLife · 2024Article
- A parametrized two-domain thermodynamic model explains diverse mutational effects on protein allostery.bioRxiv : the preprint server for biology · 2024Article
- Context-Aware Technology Mapping in Genetic Design Automation.ACS synthetic biology · 2023Article
- Multiple transcription auto regulatory loops can act as robust oscillators and decision-making motifs.Computational and structural biotechnology journal · 2022Article
- A balancing act in transcription regulation by response regulators: titration of transcription factor activity by decoy DNA binding sites.Nucleic acids research · 2021Article
- Emergent correlations in gene expression dynamics as footprints of resource competition.The European physical journal. E, Soft matter · 2021Article
- Anticipating response function in gene regulatory networks.Journal of the Royal Society, Interface · 2021Article
- Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage.Nature communications · 2020Article
- Deciphering the regulatory genome ofeLife · 2020Article
- Inherent regulatory asymmetry emanating from network architecture in a prevalent autoregulatory motif.eLife · 2020Article
- The Phenotype Paradox: Lessons From Natural Transcriptome Evolution on How to Engineer Plants.Frontiers in plant science · 2020Article
- AMPK Enhances Transcription of Selected Nrf2 Target Genes via Negative Regulation of Bach1.Frontiers in cell and developmental biology · 2020Article
- Building a minimal and generalizable model of transcription factor-based biosensors: Showcasing flavonoids.Biotechnology and bioengineering · 2018Article
- Coupling of DNA Replication and Negative Feedback Controls Gene Expression for Cell-Fate Decisions.iScience · 2018Article
- A Canonical Biophysical Model of the CsrA Global Regulator Suggests Flexible Regulator-Target Interactions.Scientific reports · 2018Article
- Distribution of Initiation Times Reveals Mechanisms of Transcriptional Regulation in Single Cells.Biophysical journal · 2018Article
- Tuning Transcriptional Regulation through Signaling: A Predictive Theory of Allosteric Induction.Cell systems · 2018Article
- Tailor-made transcriptional biosensors for optimizing microbial cell factories.Journal of industrial microbiology & biotechnology · 2017Review
- Effect of transcription factor resource sharing on gene expression noise.PLoS computational biology · 2017Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Transcription factors (TFs) with regulatory action at multiple promoter targets is the rule rather than the exception, with examples ranging from the cAMP receptor protein (CRP) in E. coli that regulates hundreds of different genes simultaneously to situations involving multiple copies of the same gene, such as plasmids, retrotransposons, or highly replicated viral DNA. When the number of TFs heavily exceeds the number of binding sites, TF binding to each promoter can be regarded as independent. However, when the number of TF molecules is comparable to the number of binding sites, TF titration will result in correlation ("promoter entanglement") between transcription of different genes. We develop a statistical mechanical model which takes the TF titration effect into account and use it to predict both the level of gene expression for a general set of promoters and the resulting correlation in transcription rates of different genes. Our results show that the TF titration effect could be important for understanding gene expression in many regulatory settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.