Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

Duveau, Fabien; Hodgins‐Davis, Andrea; Metzger, Brian P. H.; Yang, Bing; Tryban, Stephen; Walker, Elizabeth A.; Lybrook, Tricia; Wittkopp, Patricia J.

doi:10.7554/elife.37272

Cited by 62 publications

(77 citation statements)

References 64 publications

(127 reference statements)

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“…First, Cra expression noise only results in a fitness benefit when the increase in fitness during adaptive evolution. This pattern holds for nongenetic variation 428 in general, and is consistent with prior theoretical [15,16] and empirical work [17]. This 429 occurs because in populations remote from a fitness optimum, random variation in 430 phenotype is more likely to push some individuals closer to the optimum than in a 431 well-adapted population.…”

supporting

confidence: 74%

“…The fitness benefit of nongenetic variation in a trait often diminishes as populations 217 approach the optimum value for that trait [15][16][17]. We investigated whether this 218 reduction also occurs in our model.…”

Section: Cra Expression Noise Increases Fitness 202mentioning

confidence: 99%

“…Also, theory suggests that mean and 157 variance can evolve independently during adaptive evolution [58]. In addition, they can 158 be uncoupled experimentally [17].…”

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confidence: 99%

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Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Schmutzer

Wagner

2020

Preprint

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Nongenetic phenotypic variation can either speed up or slow down adaptive evolution. We show that it can speed up evolution in environments in which available carbon and energy sources change over time. To this end, we use an experimentally validated model of Escherichia coli growth on two alternative carbon sources, glucose and acetate. On the superior carbon source (glucose), all cells achieve high growth rates, while on the inferior carbon source (acetate) only a small fraction of the population manages to initiate growth. Consequently, populations experience a bottleneck when the environment changes from the superior to the inferior carbon source. Growth on the inferior carbon source depends on a circuit under the control of a transcription factor that is repressed in the presence of the superior carbon source. We show that noise in the expression of this transcription factor can increase the probability that cells start growing on the inferior carbon source. In doing so, it can decrease the severity of the bottleneck and increase mean population fitness whenever this fitness is low. A modest amount of noise can also enhance the fitness effects of a beneficial allele. It can accelerate the spreading of such an allele, increase its likelihood of going to fixation, and reduce its fixation time. Central to the adaptation-enhancing principle we identify is the ability of noise to mitigate population bottlenecks. Because such bottlenecks are frequent in fluctuating environments, and because fluctuating environments themselves are ubiquitous, this principle may apply to a broad range of environments and organisms.

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confidence: 74%

Section: Cra Expression Noise Increases Fitness 202mentioning

confidence: 99%

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Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Schmutzer

Wagner

2020

Preprint

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“…While these mutations are a subset of the types of changes that arise spontaneously, they are the most common type of point mutation observed in mutation accumulation lines (27,28) and the most common type of single nucleotide polymorphism segregating in natural populations of S. cerevisiae (29). Using a canvanine resistance assay (30,31), we estimated that the EMS conditions used introduced ~29 mutations per cell (95% percentiles: [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. Following mutagenesis, we isolated single cells from each of the mutagenized populations randomly with respect to the YFP fluorescence level using fluorescence activated cell sorting (FACS) ( Figure 1a).…”

Section: Introductionmentioning

confidence: 99%

“…YFP fluorescence levels were then estimated based on at least ~ 12 thousand events captured with flow cytometry from each replicate population (Supplementary Methods, Table S2a). These YFP fluorescence levels were used to estimate YFP mRNA expression levels as in (32) (Figure 1a). In parallel, for each promoter, populations of un-mutagenized cells were subjected to a sham treatment that was identical to the mutagenesis protocol except for exposure to EMS.…”

Section: Introductionmentioning

confidence: 99%

Empirical measures of mutational effects define neutral models of regulatory evolution inSaccharomyces cerevisiae

Hodgins‐Davis

Duveau

Walker

et al. 2019

Preprint

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Understanding how phenotypes evolve requires disentangling the effects of mutation generating new variation from the effects of selection filtering it. Evolutionary models frequently assume that mutation introduces phenotypic variation symmetrically around the population mean, yet few studies have tested this assumption by deeply sampling the distributions of mutational effects for particular traits. Here, we examine distributions of mutational effects for gene expression in the budding yeast Saccharomyces cerevisiae by measuring the effects of thousands of point mutations introduced randomly throughout the genome. We find that the distributions of mutational effects differ for the 10 genes surveyed and violate the assumption of normality. For example, all ten distributions of mutational effects included more mutations with large effects than expected for normally distributed phenotypes. In addition, some genes also showed asymmetries in their distribution of mutational effects, with new mutations more likely to increase than decrease the gene's expression or vice versa. Neutral models of regulatory evolution that take these empirically determined distributions into account suggest that neutral processes may explain more expression variation within natural populations than currently appreciated. Significance statementNew mutations tend to arise randomly throughout the genome, but their phenotypic effects are often not random. This disconnect results from interactions among genes that define the genotype-phenotype map. The structure of this map is poorly known and different for each trait, making it challenging to predict the distribution of mutational effects for specific phenotypes. Empirical measures of the distribution of mutational effects are thus necessary to understand how traits can change in the absence of natural selection. In this work, we define such distributions for expression of ten genes in S. cerevisiae and show that they predict greater neutral expression divergence than commonly used models of phenotypic evolution. \body Results and DiscussionPredicting neutral expression divergence using distributions of mutational effects

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Compensatorytrans-regulatory alleles minimizing variation inTDH3expression are common withinSaccharomyces cerevisiae

Metzger

Wittkopp

2019

Evolution Letters

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Heritable variation in gene expression is common within species. Much of this variation is due to genetic differences outside of the gene with altered expression and is trans‐acting. This trans‐regulatory variation is often polygenic, with individual variants typically having small effects, making the genetic architecture and evolution of trans‐regulatory variation challenging to study. Consequently, key questions about trans‐regulatory variation remain, including the variability of trans‐regulatory variation within a species, how selection affects trans‐regulatory variation, and how trans‐regulatory variants are distributed throughout the genome and within a species. To address these questions, we isolated and measured trans‐regulatory differences affecting TDH3 promoter activity among 56 strains of Saccharomyces cerevisiae, finding that trans‐regulatory backgrounds varied approximately twofold in their effects on TDH3 promoter activity. Comparing this variation to neutral models of trans‐regulatory evolution based on empirical measures of mutational effects revealed that despite this variability in the effects of trans‐regulatory backgrounds, stabilizing selection has constrained trans‐regulatory differences within this species. Using a powerful quantitative trait locus mapping method, we identified ∼100 trans‐acting expression quantitative trait locus in each of three crosses to a common reference strain, indicating that regulatory variation is more polygenic than previous studies have suggested. Loci altering expression were located throughout the genome, and many loci were strain specific. This distribution and prevalence of alleles is consistent with recent theories about the genetic architecture of complex traits. In all mapping experiments, the nonreference strain alleles increased and decreased TDH3 promoter activity with similar frequencies, suggesting that stabilizing selection maintained many trans‐acting variants with opposing effects. This variation may provide the raw material for compensatory evolution and larger scale regulatory rewiring observed in developmental systems drift among species.

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Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

Cited by 62 publications

References 64 publications

Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Empirical measures of mutational effects define neutral models of regulatory evolution inSaccharomyces cerevisiae

Compensatorytrans-regulatory alleles minimizing variation inTDH3expression are common withinSaccharomyces cerevisiae

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