Abstract

Changes in gene expression can affect phenotypes and therefore both its level and stochastic variability are frequently under selection. It has recently been proposed that epistatic interactions influence gene expression evolution: gene pairs where simultaneous knockout is more deleterious than expected should evolve reduced expression noise to avoid concurrent low expression of both proteins. In apparent support, yeast genes with many epistatic partners have low expression variation both among isogenic individuals and between species. However, the specific predictions and basic assumptions of this verbal model remain untested. Using bioinformatics analysis, we first demonstrate that the model's predictions are unsupported by available large-scale data. Based on quantitative biochemical modeling, we then show that epistasis between expression reductions (epigenetic epistasis) is not expected to aggravate the fitness cost of stochastic expression, which is in sharp contrast to the verbal argument. This nonintuitive result can be readily explained by the typical diminishing return of fitness on gene activity and by the fact that expression noise not only decreases but also increases the abundance of proteins. Overall, we conclude that stochastic variation in epistatic partners is unlikely to drive noise minimization or constrain gene expression divergence on a genomic scale.

Highlights

  • Gene expression is the first step in translating genetic information into phenotypes, expression level is expected to be the subject of natural selection

  • We report that a set of 10 gene features can explain 19.5% of variation in gene expression noise when considered jointly

  • A recent verbal model proposed that epistasis shapes the evolution of gene expression noise and the conservation of gene expression between species (Park and Lehner 2013)

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Summary

Introduction

Gene expression is the first step in translating genetic information into phenotypes, expression level is expected to be the subject of natural selection. Both increased and decreased expression can impose a fitness burden (Papp et al 2003; Dekel and Alon 2005; Deutschbauer et al 2005; Sopko et al 2006) and comparative analyses revealed that transcript levels of most genes evolve under stabilizing selection (Lemos et al 2005; Gilad et al 2006). Noise in gene expression appears to be shaped by natural selection to minimize the deleterious consequences of fluctuations in important and dosage-sensitive proteins

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