Universal Poisson Statistics of mRNAs with Complex Decay Pathways

Mukund Thattai

doi:10.1016/j.bpj.2015.12.001

Abstract

Messenger RNA (mRNA) dynamics in single cells are often modeled as a memoryless birth-death process with a constant probability per unit time that an mRNA molecule is synthesized or degraded. This predicts a Poisson steady-state distribution of mRNA number, in close agreement with experiments. This is surprising, since mRNA decay is known to be a complex process. The paradox is resolved by realizing that the Poisson steady state generalizes to arbitrary mRNA lifetime distributions. A mapping between mRNA dynamics and queueing theory highlights an identifiability problem: a measured Poisson steady state is consistent with a large variety of microscopic models. Here, I provide a rigorous and intuitive explanation for the universality of the Poisson steady state. I show that the mRNA birth-death process and its complex decay variants all take the form of the familiar Poisson law of rare events, under a nonlinear rescaling of time. As a corollary, not only steady-states but also transients are Poisson distributed. Deviations from the Poisson form occur only under two conditions, promoter fluctuations leading to transcriptional bursts or nonindependent degradation of mRNA molecules. These results place severe limits on the power of single-cell experiments to probe microscopic mechanisms, and they highlight the need for single-molecule measurements.

Highlights

The small volume of living cells and the small number of many important biological molecules forces us to adopt a discrete description of biochemical reactions
Simple birth-death models of transcription and decay predict that steady-state messenger RNA (mRNA) numbers, m, should follow a Poisson distribution whose variance, s2m, is equal to its mean, mm [4]
A comprehensive analysis of mRNA numbers for over a thousand E. coli promoters found that variance scaled with the mean over two orders of magnitude, and that the median Fano factor, s2m=mm, was ~1.6 [6], close to the Poisson expectation

Summary

Introduction

The small volume of living cells and the small number of many important biological molecules forces us to adopt a discrete description of biochemical reactions. Simple birth-death models of transcription and decay predict that steady-state mRNA numbers, m, should follow a Poisson distribution whose variance, s2m, is equal to its mean, mm [4]. It is a surprising and powerful result that the transient mRNA distribution of the complex system in Eq 3 has precisely the Poisson form of Eq 2, where hmi is the (possibly time-dependent) mean mRNA number [19,20].

Results

Conclusion