Biochemical Complexity Drives Log - Normal Variation in Genetic Expression

Cells exhibit a high degree of variation in levels of gene expression, even within otherwise homogeneous populations. The standard model to describe this variation centers on a gamma distribution driven by stochastic bursts of translation. Stochastic bursting, however, cannot account for the well-established behavior of strong transcriptional repressors. Instead, it can be shown the very complexity of the biochemical processes involved in gene expression drives an emergent log-normal distribution of expression levels. Emergent log-normal distributions can account for the observed behavior of transcriptional repressors, are still compatible with stochastically constrained distributions, and have important implications for both analysis of gene expression data and the engineering of biological organisms.