The Adaptive Landscape of Genetic Interaction Network Has No Impact on Yeast Adaptive Evolution.
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ABSTRACT:
SUBMITTER: Klim J
PROVIDER: S-EPMC8013701 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:To study the evolution of the yeast protein interaction network, we first classified yeast proteins by their evolutionary histories into isotemporal categories, then analyzed the interaction tendencies within and between the categories, and finally reconstructed the main growth path. We found that two proteins tend to interact with each other if they are in the same or similar categories, but tended to avoid each other otherwise, and that network evolution mirrors the universal tree of life. These observations suggest synergistic selection during network evolution and provide insights into the hierarchical modularity of cellular networks.
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Project description:A Saccharomyces cerevisiae population was cultured for many generations under conditions to which it is not optimally adapted. These experiments were designed to investigate adaptive evolution under natural selection. This study is described in more detail in Ferea TL, et al. 1999. Proc Natl Acad Sci USA 96:9721-6
2002-02-11 | E-GEOD-29 | biostudies-arrayexpress
Project description:A Saccharomyces cerevisiae population was cultured for many generations under conditions to which it is not optimally adapted. These experiments were designed to investigate adaptive evolution under natural selection. This study is described in more detail in Ferea TL, et al. 1999. Proc Natl Acad Sci USA 96:9721-6 Keywords: other
2002-02-12 | GSE29 | GEO
Project description:Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution.
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Project description:Phenotypes associated with genetic variants can be altered by interactions with other genetic variants (GxG), with the environment (GxE), or both (GxGxE). Yeast genetic interactions have been mapped on a global scale, but the environmental influence on the plasticity of genetic networks has not been examined systematically. To assess environmental rewiring of genetic networks, we examined 14 diverse conditions and scored 30,000 functionally representative yeast gene pairs for dynamic, differential interactions. Different conditions revealed novel differential interactions, which often uncovered functional connections between distantly related gene pairs. However, the majority of observed genetic interactions remained unchanged in different conditions, suggesting that the global yeast genetic interaction network is robust to environmental perturbation and captures the fundamental functional architecture of a eukaryotic cell.
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Project description:Meiotic recombination comprises crossovers and noncrossovers. Recombination, crossover in particular, shuffles mutations and impacts both the level of genetic polymorphism and the speed of adaptation. In many species, the recombination rate varies across the genome with hot and cold spots. The hotspot paradox hypothesis asserts that recombination hotspots are evolutionarily unstable due to self-destruction. However, the genomic landscape of double-strand breaks (DSBs), which initiate recombination, is evolutionarily conserved among divergent yeast species, casting doubt on the hotspot paradox hypothesis. Nonetheless, because only a subset of DSBs are associated with crossovers, the evolutionary conservation of the crossover landscape could differ from that of DSBs. Here, we investigate this possibility by generating a high-resolution recombination map of the budding yeast Saccharomyces paradoxus through whole-genome sequencing of 50 meiotic tetrads and by comparing this recombination map with that of S. cerevisiae. We observe a 40% lower recombination rate in S. paradoxus than in S. cerevisiae. Compared with the DSB landscape, the crossover landscape is even more conserved. Further analyses indicate that the elevated conservation of the crossover landscape is explained by a near-subtelomeric crossover preference in both yeasts, which we find to be attributable at least in part to crossover interference. We conclude that the yeast crossover landscape is highly conserved and that the evolutionary conservation of this landscape can differ from that of the DSB landscape.
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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.
2021-02-25 | GSE167397 | GEO
Project description:BackgroundThe 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 interacting genes.ResultsUsing Saccharomyces cerevisiae haploid deletion mutants as a model, we investigated two modules lacking COG7 or NUP133, which are evolutionarily conserved genes with many interactions. We performed laboratory evolution experiments with these strains 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 in the experimental conditions used to determine the interaction network. Similarly, transcriptome changes during continuous culture mostly signified adaptation to growth conditions rather than compensation of the absence of the COG7, NUP133 or MSH2 genes. However, we noticed that for genes whose inactivation was deleterious an upregulation of transcription was more common than downregulation.ConclusionsOur findings demonstrate that the genetic interactions and the modular structure of the network described by others have very limited effects on the evolutionary trajectory following gene deletion of module elements in our experimental conditions and has no significant impact on short-term compensatory evolution. However, we observed likely compensatory evolution in functionally related (albeit non-interacting) genes.
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Project description:A common misconception is that evolution is a linear 'march of progress', where each organism along a line of descent is more fit than all those that came before it. Rejecting this misconception implies that evolution is nontransitive: a series of adaptive events will, on occasion, produce organisms that are less fit compared to a distant ancestor. Here we identify a nontransitive evolutionary sequence in a 1000-generation yeast evolution experiment. We show that nontransitivity arises due to adaptation in the yeast nuclear genome combined with the stepwise deterioration of an intracellular virus, which provides an advantage over viral competitors within host cells. Extending our analysis, we find that nearly half of our ~140 populations experience multilevel selection, fixing adaptive mutations in both the nuclear and viral genomes. Our results provide a mechanistic case-study for the adaptive evolution of nontransitivity due to multilevel selection in a 1000-generation host/virus evolution experiment.
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Project description:Histone acetylation and deacetylation are among the principal mechanisms by which chromatin is regulated during transcription, DNA silencing, and DNA repair. We analyzed patterns of genetic interactions uncovered during comprehensive genome-wide analyses in yeast to probe how histone acetyltransferase (HAT) and histone deacetylase (HDAC) protein complexes interact. The genetic interaction data unveil an underappreciated role of HDACs in maintaining cellular viability, and led us to show that deacetylation of the histone variant Htz1p at Lys 14 is mediated by Hda1p. Studies of the essential nucleosome acetyltransferase of H4 (NuA4) revealed acetylation-dependent protein stabilization of Yng2p, a potential nonhistone substrate of NuA4 and Rpd3C, and led to a new functional organization model for this critical complex. We also found that DNA double-stranded breaks (DSBs) result in local recruitment of the NuA4 complex, followed by an elaborate NuA4 remodeling process concomitant with Rpd3p recruitment and histone deacetylation. These new characterizations of the HDA and NuA4 complexes demonstrate how systematic analyses of genetic interactions may help illuminate the mechanisms of intricate cellular processes.
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