What have we learned so far?

 

 

Gene expression evolution is consistent with a House-of-Cards model of stabilizing selection

Distribution of median selective variance calculated for gene expression phenotypes in three model species.

Divergence in gene regulation is hypothesized to underlie much of phenotypic evolution, but the role of natural selection in shaping the molecular phenotype of gene expression continues to be debated. To resolve the mode of gene expression, evolution requires accessible theoretical predictions for the effect of selection over long timescales. Evolutionary quantitative genetic models of phenotypic evolution can provide such predictions, yet those predictions depend on the underlying hypotheses about the distributions of mutational and selective effects that are notoriously difficult to disentangle. Here, we draw on diverse genomic data sets including expression profiles of natural genetic variation and mutation accumulation lines, empirical estimates of genomic mutation rates, and inferences of genetic architecture to differentiate contrasting hypotheses for the roles of stabilizing selection and mutation in shaping natural expression variation. Our analysis suggests that gene expression evolves in a domain of phenotype space well fit by the House-of-Cards (HC) model. Although the strength of selection inferred is sensitive to the number of loci controlling gene expression, the model is not. The consistency of these results across evolutionary time from budding yeast through fruit fly implies that this model is general and that mutational effects on gene expression are relatively large. Empirical estimates of the genetic architecture of gene expression traits imply that selection provides modest constraints on gene expression levels for most genes, but that the potential for regulatory evolution is high. Our prediction using data from laboratory environments should encourage the collection of additional data sets allowing for more nuanced parameterizations of HC models for gene expression.

> Read more

Budding yeast exhibit abundant gene-by-environment variation in transcriptional reaction norms to copper

Clustering of highly expressed genes visualizes similarities in expression among genes exhibiting genetic (a), copper (b), and  genotype-by-copper (c) effects. Functional enrichments for gene clusters are listed in the righthand margins.

Genetic variation for plastic phenotypes potentially contributes phenotypic variation to populations that can be selected during adaptation to novel ecological contexts.  However, the basis and extent of plastic variation that manifests in diverse environments remains elusive. In this work, we characterized copper reaction norms for mRNA abundance among five S. cerevisiae strains to a) describe population variation across the full range of ecologically relevant copper concentrations, from starvation to toxicity, and b) to test the hypothesis that plastic networks exhibit increased population variation for gene expression.

We found that the vast majority of the variation was small in magnitude (considerably less than two-fold), but most genes showed variable expression across environments, across genetic backgrounds, or both. Plastically expressed genes included both genes regulated directly by copper-binding transcription factors Mac1 and Ace1 and genes indirectly responding to the downstream metabolic consequences of the copper gradient, particularly genes involved in copper, iron, and sulfur homeostasis. Copper-regulated gene networks exhibited more similar behavior within the population in environments where those networks have a large impact on fitness.  Nevertheless, expression variation in genes like Cup1, important to surviving copper stress, was linked with variation in mitotic fitness and in the breadth of differential expression across the genome. By revealing a broader range of population variation, these results provided further evidence for the interconnectedness of genome-wide mRNA levels, their dependence on environmental context and genetic background, and the abundance of variation in gene expression that can contribute to future evolution.

> Read more.

Work in progress

Analysis of gene expression mutation accumulation lines of Saccharomyces cerevisiae across a copper gradient.