Process_TranscriptionalRegulation – Transcriptional regulation

Name
WID Process_TranscriptionalRegulation
Name Transcriptional regulation
 
Implementation
Initialization order 9 View in model
 
Comments
Comments Introduction Transcription regulation is modeled as a two-state (free, bound) Markov chain. Following maturation, transcriptional regulators first enter the free state. Next free transcriptional regulators stably bind promoters according to experimentally observed transcript abundance fold changes. Finally, transcriptional regulators remain stably bound to promoters, and bias the RNA polymerase-promoter binding probabilities. Simulates Affinity – Binding of transcription factors to transcription unit promoters Activity – Effect of bound transcription factors on recruitment of RNA polymerase to each transcription unit promoter Using experimentally observed the experimentally observed fold change expression effect of each transcription factor on each promoter. Affinity Binds enzymes to promoters assuming: Transcription factors have high affinity for promoters Transcription factors bind promoters rapidly Transcription factors bind promoters stably over time Only 1 copy of a transcription factor can bind each promoter Consequently, at each time step we simulate that each free transcription factor binds randomly binds unoccupied promoters (no copy of that transcription factor is already bound to the promoter). Random transcription factor-promoter binding is weighted by the affinity of each transcription factor for each promoter. Because transcription factor-promoter affinities are generally not experimentally observed, we set the relative transcription factor-promoter affinities numerically equal to the absolute value of the log of the transcription factor fold change activities. Activity The effect of bound transcription factors on the recruitment of RNA polymerase and the expression of transcription units is simulated here and incorporated into the calculation of the RNA polymerase transcription unit promoter binding probabilities in the transcription module. Specifically, the wild-type average RNA polymerase transcription unit promoter binding probabilities are multiplied by the binding probability fold change effects simulated in this module. The RNA polymerase binding probability fold change is simulated for each promoter as the product of the observed expression fold change effects of each bound transcription factor. When a promoter is bound by a single transcription factor the net RNA polymerase binding probability fold change is the observed expression fold change of that transcription factor. When a promoter is bound by multiple transcription units the net RNA polymerase binding probability fold change is given by the product of the individual fold change effects of the bound transcription factors. References Lacramioara Bintu, Nicolas E Buchler, Hernan G Garcia, Ulrich Gerland, Terence Hwa, Jane Kondev and Rob Phillips (2005). Transcriptional regulation by the numbers: models. Curr Opin Genet Dev. 15:116-24. [PUB_0459] Lacramioara Bintu, Nicolas E Buchler, Hernan G Garcia, Ulrich Gerland, Terence Hwa, Jane Kondev and Rob Phillips (2005). Transcriptional regulation by the numbers: applications. Curr Opin Genet Dev. 15:125-35. [PUB_0460]
References
  1. Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Kuhlman T, Phillips R. Transcriptional regulation by the numbers: applications. Curr Opin Genet Dev 15, 125-35 (2005). WholeCell: PUB_0460, PubMed: 15797195

  2. Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Phillips R. Transcriptional regulation by the numbers: models. Curr Opin Genet Dev 15, 116-24 (2005). WholeCell: PUB_0459, PubMed: 15797194

 
Metadata
Created 2012-10-01 15:07:35
Last updated 2012-10-01 15:14:00