威尼斯人

报告摘要：In single cells, message RNA molecules fluctuate heavily even within a homogeneous environment. Fluctuation in gene transcription is considered to be a main source of phenotypic heterogeneity. Highly variable mRNA distributions are primarily attributed to randomly switching between periods of active (ON) and inactive (OFF) gene transcription. In most studies, the waiting-time distributions for gene spending in its ON- or OFF-state are typically modeled as exponential distributions. However, increasing data indicate that a gene's lifetimes at ON- or OFF-state are non-exponential distributions. By combining the Kolmogorov forward equations with the alternating renewal processes, we present a novel method to compute the average transcription level and its noise. Taking the lifetimes of the OFF and the ON states having the Erlang distribution, for instance, we derive the mean transcription level and the noise in mRNA copy numbers at a steady state. The computation approach we constructed in this paper to calculate the mean and the noise of mRNA transcripts can be used to treat a series of transcription cycles that are non-lattice.