Project description:Background: The impact of genetic interaction networks on evolution is a fundamental issue. Previous studies have demonstrated that the topology of the network is determined by the properties of the cellular machinery. Functionally related genes frequently interact with one another, and they establish modules, e.g., modules of protein complexes and biochemical pathways. In this study, we experimentally tested the hypothesis that compensatory evolutionary modifications, such as mutations and transcriptional changes, occur frequently in genes from perturbed modules of genetically interacting genes. Results: Using haploid strains of Saccharomyces cerevisiae deletion mutants as a model, we investigated two modules lacking COG7 or NUP133, which are evolutionarily conserved genes with many compensatory interactions. We performed laboratory evolution experiments with strains bearing these mutations in two genetic backgrounds (with or without additional deletion of MSH2), subjecting them to continuous culture in a non-limiting minimal medium. Next, the evolved yeast populations were characterized through whole-genome sequencing and transcriptome analyses. No obvious compensatory changes resulting from inactivation of genes already included in modules were identified. The supposedly compensatory inactivation of genes in the evolved strains was only rarely observed to be in accordance with the established fitness effect of the genetic interaction network. In fact, a substantial majority of the gene inactivations were predicted to be neutral. Similarly, transcriptome changes during continuous culture mostly signified adaptation to growth conditions rather than compensation of the absence of COG7, NUP133 or MSH2 genes. Conclusions: Our findings demonstrate that the genetic interactions and modular structure of the network described in other studies have very limited effects on the evolutionary trajectory observed on the genomic and transcriptomic levels, following gene deletion of module elements and upon our experimental conditions. This observation indicates that the modular structure of the cellular machinery has no impact on compensatory evolution in the short term.

Project description:The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time.Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms.We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes, including point mutations, structural changes, and insertion variation, that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in glucose-, sulfate, or phosphate-limited chemostats for ~ 200 generations.We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation.Global mutation detection in 10 clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of continuous phase in the chemostat.We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5-50%. We found that the spectrum of available mutations in glucose or phosphate-limited environments combined with the batch phase population dynamics early in our experiments to allow several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes.Thus, the reproducibility of evolution varies with specific selective pressures reflecting the constraints inherent in the system-level organization of metabolic processes in the cell.We were able to relate some of the observed adaptive mutations (e.g. transporter gene amplifications) to known features of the relevant metabolic pathways, but many of the mutations pointed to genes not previously associated with the relevant physiology. Thus, in addition to answering basic mechanistic questions about evolutionary mechanisms our work suggests that experimental evolution can also shed light on the function and regulation of individual metabolic pathways. Keywords: gene expression, CGH, and TSE analysis

Project description:The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time.Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms.We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes, including point mutations, structural changes, and insertion variation, that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in glucose-, sulfate, or phosphate-limited chemostats for ~ 200 generations.We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation.Global mutation detection in 10 clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of continuous phase in the chemostat.We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5-50%. We found that the spectrum of available mutations in glucose or phosphate-limited environments combined with the batch phase population dynamics early in our experiments to allow several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes.Thus, the reproducibility of evolution varies with specific selective pressures reflecting the constraints inherent in the system-level organization of metabolic processes in the cell.We were able to relate some of the observed adaptive mutations (e.g. transporter gene amplifications) to known features of the relevant metabolic pathways, but many of the mutations pointed to genes not previously associated with the relevant physiology. Thus, in addition to answering basic mechanistic questions about evolutionary mechanisms our work suggests that experimental evolution can also shed light on the function and regulation of individual metabolic pathways. Keywords: gene expression, CGH, and TSE analysis consult individual records for details of analysis This Dataset consists of several experiments: Gene expression experiments found in Figure 1a of paper: Design: RNA from each evolved clone or population grown in chemostat culture is compared to RNA from matching ancestor strains grown in the same conditions. Samples: GSM339025-GSM339088 CGH experiments found in Figure 2A, Figure 3, and Table S2: Experiment design: DNA from each evolved clone or population is hybridized vs DNA from the matched ancestor strain Samples: GSM339089-GSM339146 CGH experiments found in Table S3: Experiment design: DNA from each segregant derived from an evolved strain is hybridized vs DNA from the matched ancestor strain Samples: GSM339147-GSM339158 Gel band CGH experiments found in Figure S1: Experiment design: Chromosomes from evolved strains were run on a gel and excised. DNA from the bands is hybridized vs matched ancestor genomic DNA Samples: GSM339159-GSM339184 TSE CGH experiments found in Table S4: Experiment design: DNA linked to Ty1/Ty2 sequences was extracted from evolved strains and ancestor strains, and compared to ancestral extracted or genomic DNA as indicated. Samples: GSM339185-GSM339212 CGH experiments for experiments in Figure S7: Experiment design: DNA from 2 strains transformed with a SUL1 plasmid hybridized vs DNA from the matched ancestor strain Samples: GSM339213 and GSM339214

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Genetic interaction network has a very limited impact on the evolutionary trajectories in continuous culture-grown populations of yeast

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