Active compensation for changes in TDH3 expression mediated by direct regulators of TDH3 in Saccharomyces cerevisiae.

Genetic networks are surprisingly robust to perturbations caused by new mutations. This robustness is conferred in part by compensation for loss of a gene's activity by genes with overlapping functions, such as paralogs. Compensation occurs passively when the normal activity of one paralog can compensate for the loss of the other, or actively when a change in one paralog's expression, localization, or activity is required to compensate for loss of the other. The mechanisms of active compensation remain poorly understood in most cases. Here we investigate active compensation for the loss or reduction in expression of the Saccharomyces cerevisiae gene TDH3 by its paralog TDH2. TDH2 is upregulated in a dose-dependent manner in response to reductions in TDH3 by a mechanism requiring the shared transcriptional regulators Gcr1p and Rap1p. TDH1, a second and more distantly related paralog of TDH3, has diverged in its regulation and is upregulated by another mechanism. Other glycolytic genes regulated by Rap1p and Gcr1p show changes in expression similar to TDH2, suggesting that the active compensation by TDH3 paralogs is part of a broader homeostatic response mediated by shared transcriptional regulators.

Candida albicans selection for human commensalism results in substantial within-host diversity without decreasing fitness for invasive disease.

Candida albicans is a frequent colonizer of human mucosal surfaces as well as an opportunistic pathogen. C. albicans is remarkably versatile in its ability to colonize diverse host sites with differences in oxygen and nutrient availability, pH, immune responses, and resident microbes, among other cues. It is unclear how the genetic background of a commensal colonizing population can influence the shift to pathogenicity. Therefore, we examined 910 commensal isolates from 35 healthy donors to identify host niche-specific adaptations. We demonstrate that healthy people are reservoirs for genotypically and phenotypically diverse C. albicans strains. Using limited diversity exploitation, we identified a single nucleotide change in the uncharacterized ZMS1 transcription factor that was sufficient to drive hyper invasion into agar. We found that SC5314 was significantly different from the majority of both commensal and bloodstream isolates in its ability to induce host cell death. However, our commensal strains retained the capacity to cause disease in the Galleria model of systemic infection, including outcompeting the SC5314 reference strain during systemic competition assays. This study provides a global view of commensal strain variation and within-host strain diversity of C. albicans and suggests that selection for commensalism in humans does not result in a fitness cost for invasive disease.

Systems biology of host-Candida interactions: understanding how we shape each other.

Candida albicans is both a member of the human mucosal microbiota and a common agent of invasive fungal disease. Systems biology approaches allow for analysis of the interactions between this fungus and its mammalian host. Framing these studies by considering how C. albicans and its host construct the niche the other occupies provides insight into how these interactions shape the ecosystems, behavior, and evolution of each organism. Here, we discuss recent work on multiscale systems biology approaches for examining C. albicans in relation to the host ecosystem to identify the emergent properties of the interactions and new variables that can be targeted for development of therapeutic strategies.

Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae.

Understanding how phenotypes evolve requires disentangling the effects of mutation generating new variation from the effects of selection filtering it. Tests for selection 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 are inconsistent with normality. For example, all 10 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.

Fitness effects of altering gene expression noise in Saccharomyces cerevisiae.

Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

Effects of mutation and selection on plasticity of a promoter activity in Saccharomyces cerevisiae.

Phenotypic plasticity is an evolvable property of biological systems that can arise from environment-specific regulation of gene expression. To better understand the evolutionary and molecular mechanisms that give rise to plasticity in gene expression, we quantified the effects of 235 single-nucleotide mutations in the Saccharomyces cerevisiae TDH3 promoter (PTDH3 ) on the activity of this promoter in media containing glucose, galactose, or glycerol as a carbon source. We found that the distributions of mutational effects differed among environments because many mutations altered the plastic response exhibited by the wild-type allele. Comparing the effects of these mutations with the effects of 30 PTDH3 polymorphisms on expression plasticity in the same environments provided evidence of natural selection acting to prevent the plastic response in PTDH3 activity between glucose and galactose from becoming larger. The largest changes in expression plasticity were observed between fermentable (glucose or galactose) and nonfermentable (glycerol) carbon sources and were caused by mutations located in the RAP1 and GCR1 transcription factor binding sites. Mutations altered expression plasticity most frequently between the two fermentable environments, with mutations causing significant changes in plasticity between glucose and galactose distributed throughout the promoter, suggesting they might affect chromatin structure. Taken together, these results provide insight into the molecular mechanisms underlying gene-by-environment interactions affecting gene expression as well as the evolutionary dynamics affecting natural variation in plasticity of gene expression.

Gene Expression Evolves under a House-of-Cards Model of Stabilizing Selection.

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.

Abundant gene-by-environment interactions in gene expression reaction norms to copper within Saccharomyces cerevisiae.

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. Here, we characterize copper reaction norms for mRNA abundance among five Saccharomyces cerevisiae strains to 1) describe population variation across the full range of ecologically relevant copper concentrations, from starvation to toxicity, and 2) to test the hypothesis that plastic networks exhibit increased population variation for gene expression. We find that although the vast majority of the variation is small in magnitude (considerably <2-fold), not just some, but most genes demonstrate 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 and deeper range of population variation, our results provide 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.

Biased learning affects mate choice in a butterfly.

Early acquisition of mate preferences or mate-preference learning is associated with signal diversity and speciation in a wide variety of animal species. However, the diversity of mechanisms of mate-preference learning across taxa remains poorly understood. Using the butterfly Bicyclus anynana we uncover a mechanism that can lead to directional sexual selection via mate-preference learning: a bias in learning enhanced ornamentation, which is independent of preexisting mating biases. Naïve females mated preferentially with wild-type males over males with enhanced wing ornamentation, but females briefly exposed to enhanced males mated significantly more often with enhanced males. In contrast, females exposed to males with reduced wing ornamentation did not learn to prefer drab males. Thus, we observe both a learned change of a preexisting mating bias, and a bias in ability to learn enhanced male ornaments over reduced ornaments. Our findings demonstrate that females are able to change their preferences in response to a single social event, and suggest a role for biased learning in the evolution of visual sexual ornamentation.

Evolving gene expression: from G to E to GxE.

Analyses of gene expression data sets for multiple individuals and species promise to shed light on the mode of evolution of gene expression. However, complementary complexities challenge this goal. Characterization of the genetic variation underlying gene expression can easily be compromised by lack of environmental control. Conversely, the breadth of conclusions from studies of environmental effects has been limited by the use of single strains. Controlled studies have hinted at extensive genexenvironment interaction. Thus, both genetics and environment are key components in models of the evolution of gene expression. We review the literature on the evolution of gene expression in terms of genetics (G), environmental response (E) and GxE interactions to make this conceptual point.

Kin recognition in zebrafish: a 24-hour window for olfactory imprinting.

Distinguishing kin from non-kin profoundly impacts the evolution of social behaviour. Individuals able to assess the genetic relatedness of conspecifics can preferentially allocate resources towards related individuals and avoid inbreeding. We have addressed the question of how animals acquire the ability to recognize kin by studying the development of olfactory kin preference in zebrafish (Danio rerio). Previously, we showed that zebrafish use an olfactory template to recognize even unfamiliar kin through phenotype matching. Here, we show for the first time that this phenotype matching is based on a learned olfactory imprinting process in which exposure to kin individuals on day 6 post fertilization (pf) is necessary and sufficient for imprinting. Larvae that were exposed to kin before or after but not on day 6 pf did not recognize kin. Larvae isolated from all contact with conspecifics did not imprint on their own chemical cues; therefore, we see no evidence for kin recognition through self-matching in this species. Surprisingly, exposure to non-kin odour during the sensitive phase of development did not result in imprinting on the odour cues of unrelated individuals, suggesting a genetic predisposition to kin odour. Urine-born peptides expressed by genes of the immune system (MHC) are important messengers carrying information about 'self' and 'other'. We suggest that phenotype matching is acquired through a time-sensitive learning process that, in zebrafish, includes a genetic predisposition potentially involving MHC genes expressed in the olfactory receptor neurons.

Classification of vocalizations of killer whales using dynamic time warping.

A large number of killer whale sounds have recently been classified perceptually into Call Types. [A. Hodgins-Davis, thesis, Wellesley College (2004)]. The repetition rate of the pulsed component of five or more examples of each call type has been calculated using a modified form of the FFT based comb-filter method. A dissimilarity or distance matrix for these sounds was calculated using dynamic time warping to compare their melodic contours. These distances were transformed into a component space using multidimensional scaling and the resulting points were clustered with a kmeans algorithm. In grouping 57 sounds into 9 call types, a single discrepancy between the perceptual and the automated methods occurred.