Emergent L\'evy behavior in single-cell stochastic gene expression

TL;DR

This paper investigates the stochastic behavior of single-cell gene expression, establishing macroscopic limits that connect microscopic models to classical kinetics and empirical observations, with analytical results for protein distributions.

Contribution

It introduces the Le9vy limit as a new theoretical foundation for observed gene expression distributions, complementing the classical Kurtz limit.

Findings

Le9vy limit explains empirical gene expression data

Analytic expression for protein distribution in autoregulatory networks

Clarifies applicability of different macroscopic limits

Abstract

Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the L\'{e}vy limit provides a theoretical foundation for an empirical equation proposed in [Phys. Rev. Lett. 97:168302, 2006]. Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.