Selection to minimise noise in living systems and its implications for the evolution of gene expression

Abstract

Gene expression, like many biological processes, is subject to noise. This noise has been measured on a global scale, but its general importance to the fitness of an organism is unclear. Here, I show that noise in gene expression in yeast has evolved to prevent harmful stochastic variation in the levels of genes that reduce fitness when their expression levels change. Therefore, there has probably been widespread selection to minimise noise in gene expression. Selection to minimise noise, because it results in gene expression that is stable to stochastic variation in cellular components, may also constrain the ability of gene expression to respond to non-stochastic variation. I present evidence that this has indeed been the case in yeast. I therefore conclude that gene expression noise is an important biological trait, and one that probably limits the evolvability of complex living systems.

Figure 1

Noise is minimised for dosage-sensitive genes. The relationship between gene expression and the proportion of genes that are (A) essential, (B) haploinsufficient, (C) inhibit growth when deleted or (D) inhibit growth when overexpressed. The result when considering all dosage-sensitive genes is shown in (E). The percentage of genes with each phenotype is shown for each of 10 equally sized bins of genes ranked according to an expression-level-adjusted measure of noise (DM). The range of each bin is shown, except for the maximum of the top bin, which extends to 61.0.

Figure 2

Proteins with more interactions have lower noise. The relationship between noise and dosage sensitivity is seen both for genes that are part of MIPS protein complexes and for other genes (A). It is also seen when controlling for the number of protein interactions (B). P-values for differences between dosage-sensitive and other genes: 2 × 10⁻⁴ (complex subunits), 9 × 10⁻⁹ (non-complex subunits), 4 × 10⁻⁷ (zero protein interactions), 0.05 (1–5 protein interactions), and 1 × 10⁻³ (>5 protein interactions) (Wilcoxon rank sum test). In addition, genes without protein interactions have a higher mean noise than genes with protein interactions for both dosage-sensitive and other genes (P=1 × 10⁻³ and P=5 × 10⁻⁸, respectively). The error bars represent measure±s.e.

Figure 3

Mutational variance (Vm) and expression divergence between species are restricted for dosage-sensitive genes with low noise. Both mutational variance, a measure of the change in a gene's expression in response to random mutagenesis (Landry et al, 2007) (A), and the divergence in expression between yeast species (Tirosh et al, 2006) (B), negatively correlate with noise (Spearman's Rank correlation coefficient, ρ=0.27, P=1.08 × 10⁻¹⁴, n=776, and ρ=0.30, P=2.2 × 10⁻¹⁶, n=1750, respectively). Error bars represent measure±s.e. (C) The relationship between mutational variance and the percentage of dosage-sensitive genes. The percentage of dosage-sensitive genes is shown for ten equally sized bins of genes arranged according to their mutational variance. (D) The same plot but comparing dosage-sensitivity to gene expression divergence between yeast species, again for ten equally sized bins of yeast genes. The ranges of each bin are shown, except for the maximum of the top bins, which extend to 4.05 and 9.02, respectively.