Multiplicative Levy noise-induced transitions in gene expression

Gene expression is intrinsically noisy. Experimental studies have shown that random fluctuations are large bursts and heavy-tailed distributions. Therefore, this study aims to consider transition dynamics in a gene transcriptional regulatory system via the mean first exit time (MFET) and first escape probability (FEP), when the degradation rate is under multiplicative non-Gaussian Levy fluctuations in the sense of Ito and Marcus forms. We find that, in the Marcus form case, the FEP corresponding to different stability index and noise intensity has an intersection point, whereas in the Ito form case, the turning point only occurs at stability index. Increasing the initial CI concentration is helpful for improving the likelihood of transcription in both cases. Our results also imply that larger jumps of Levy noise and smaller noise intensity can shorten the time of state transition to boost protein production.

Automated summary

Gene expression is inherently noisy and affected by random fluctuations. This study considers the transition dynamics in a gene regulatory system and finds that increasing the initial concentration can improve transcription. The results indicate that larger jumps in noise and smaller noise intensity can shorten the time for state transition and boost protein production.