Delayed stochastic model of transcription at the single nucleotide level
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||Journal of Computational Biology|
|Publication status||Published - 2009|
|Publication type||A1 Journal article-refereed|
We present a delayed stochastic model of transcription at the single nucleotide level. The model accounts for the promoter open complex formation and includes alternative pathways to elongation, namely pausing, arrest, misincorporation and editing, pyrophosphorolysis, and premature termination. We confront the dynamics of this detailed model with a single-step multi-delayed stochastic model and with measurements of expression of a repressed gene at the single molecule level. At low expression rates both models match the experiments but, at higher rates the two models differ significantly, with consequences to cell-to-cell phenotypic variability. The alternative pathway reactions, due to, for example, causing polymerases to collide more often on the template, are the cause for the difference in dynamical behaviors. Next, we confront the model with measurements of the transcriptional dynamics at the single RNA level of an induced gene and show that RNA production, besides its bursting dynamics, also exhibits pulses (2 or more RNAs produced in intervals smaller than the smallest interval between initiations). The distribution of occurrences and amplitudes of pulses match the experimental measurements. This pulsing and the noise at the elongation stage are shown to play a role in the dynamics of a genetic switch.