The effect of phenotypic selection on stochastic gene expression

TL;DR

This paper investigates how phenotypic selection influences stochastic gene expression in genetically identical cells, revealing effects on population fitness, variability, and stability of expression states through quantitative modeling.

Contribution

It introduces a model linking phenotypic selection to gene expression variability, analyzing how selection shapes population distribution and stability of expression states.

Findings

Selection can increase or decrease gene expression variability

Heritability influences population fitness under selection

Selection impacts stability and switching between expression states

Abstract

Genetically identical cells in the same population can take on phenotypically variable states, leading to differentiated responses to external signals, such as nutrients and drug-induced stress. Many models and experiments have focused on a description based on discrete phenotypic states. Here we consider the effects of selection acting on a single trait, which we explicitly link to the variable number of proteins expressed by a gene. Considering different regulatory models for the gene under selection, we calculate the steady-state distribution of expression levels and show how the population adapts its expression to enhance its fitness. We quantitatively relate the overall fitness of the population to the heritability of expression levels, and their diversity within the population. We show how selection can increase or decrease the variability in the population, alter the stability of bimodal states, and impact the switching rates between metastable attractors.