Figure 4.

Exploration of model parameters based on a comparison of fluorescence distributions and stochastic simulation algorithm (SSA) simulations. (A) Distribution of parameter set scores. The lowest scores correspond to the better fits. These fits were obtained using values of γ and α, the parameters contained within the joint α·γ value of 0.035 arbitrary unit/min/mRNA. The upper limit (0.107) of the single peak showing the best scores is specified (vertical line). (B) Distribution of chromatin dynamics ('mean burst size' and 'mean closed time'), obtained for the best parameter sets, after distribution comparisons for the six cellular clones. To compare with the possible chromatin dynamics presented in Figure 3B, this figure shows the chromatin dynamics obtained for the best parameter sets (black; score means between 0.07 and 0.107; see panel (A)) and the optimal parameter set for each clone (brown). (C) Illustration, for the six cellular clones, of the comparison between the mCherry fluorescence distributions measured by flow cytometry ('FACS'; solid line), and simulated fluorescence distributions ('Modeled'; dotted line) obtained with the best chromatin-dynamics parameter set. (D) One run of Gillespie SSA per clone showing the chromatin dynamics (opening and closing chromatin events are shown in black) for one virtual cell of the isogenic population distribution (see panel (C)). Consequences of chromatin open/closed dynamics on mRNA transcription and protein translation are shown in blue and in red respectively. Production (+) and degradation (-) evolutions of mRNAs and proteins are also indicated. (For illustration, Figure S2 (see Additional file 3) shows the same analysis as that presented in this figure, but for the parameter set with the highest (that is, worst) comparison score among the best ones).

Viñuelas et al. BMC Biology 2013 11:15   doi:10.1186/1741-7007-11-15
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