A transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription
Fig 4
Transcriptional activation in the presence of PPRR positive feedback predominately alters activation of more permissive initial promoter states.
(A) Three representative fractional promoter-state probability pie charts with the addition of feedback of UP (blue), AP (teal) and BP (yellow) for BIR:BTR ratios of 0.1, 1, and 10 with PBR and PPRR held constant at 10 hr-1. Data presented as described in Fig 2A. (B) Representative simulated trajectories with feedback for BIR:BTR = 10 (pink), BIR:BTR = 1 (green), and BIR:BTR = 0.1 (cerulean) presented as described in (Fig 2B). Gray regions on the right represent the probability density of mRNA counts at 24 hours, with kernel smoothing, with feedback (black) and without feedback (red). (C-D) Fold-change in mRNA counts (C) and Fano factor (D) for the three BIR:BTR ratios at 0, 1, 2, 4 and 24 hours as compared to non-feedback simulations. Data were generated through stochastic simulation for 1,000 cells for each parameter combination. Error bars represent 95% bootstrapped confidence intervals. (E) Three representative pie charts of fractional promoter-state probability with the addition of feedback of UP (blue), AP (teal) and BP (yellow) for PPRR:PBR ratios of 0.1, 1, and 10 with BIR and BTR held constant at 0.1 hr-1. Fractional probabilities were calculated as described in (A). (F) Representative simulated trajectories with feedback for PPRR:PBR = 0.1 (yellow), PPRR:PBR = 1 (green), and PPRR:PBR = 10 (orange). Data presented as described in (B). (G-H) Fold-change mRNA counts (G) and Fano factor (H) for the three PPRR:PBR ratios for timepoints of 0, 1, 2, 4 and 24 hours as compared to non-feedback simulations. Data presented as described in (C-D).