Project description:One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increases the predictability of adaptive evolution. mRNA from each evolved clone or from the ancestral strain growing in the specificied nitrogen-limited condition was co-hybridized with mRNA from the ancestral strain grown in ammonium limited media
Project description:One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increases the predictability of adaptive evolution. DNA from each evolved clone or population is hybridized vs DNA from the ancestral strain
Project description:One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increases the predictability of adaptive evolution.
Project description:One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increases the predictability of adaptive evolution.
Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Escherichia coli. The transcriptome, resistance, and genomic profiles for the evolved strains in 48 environments were quantitatively analyzed. By analyzing the quantitative datasets through interpretable machine learning techniques, the emergence of low dimensional phenotypic states within the 192 strains was observed. Further analysis revealed the underlying biological processes responsible for the distinct states. We also report a novel constraint which leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space, and lead to a comprehensive understanding of constraints for antibiotic resistance.
Project description:Purpose: High-altitude adaptive evolution of transcription, and the convergence and divergence of transcriptional alteration across species in response to high-altitude environments, is an important topic of broad interest to the general biology community. Our study aims to answer this important biological question. Methods: We generated deep transcriptome data of high- and low- altitude populations across four species: chicken, pig, goat and sheep, as well as high-altitude yak and low-altitude cattle, from six tissues (heart, kidney, liver, lung, skeletal muscle and spleen). Results: Here we provide a comprehensive comparative transcriptome landscape of expression and alternative splicing variation between low- and high-altitude populations across multiple species for distinct tissues. Conclusions: Our data serves a valuable resource for further study on adaptive transcription evolution and identification of candidate adaptive genes.
Project description:The RpoS sigma factor protein of Escherichia coli is the master transcriptional regulator of physiological responses to a variety of stresses. This stress response comes at the expense of scavenging for scarce resources, causing a trade-off between stress tolerance and nutrient acquisition. This trade-off favors non-functional rpoS alleles in nutrient-poor environments. We used experimental evolution to explore how natural selection modifies the regulatory network of strains lacking RpoS when they are evolved in an osmotically stressful environment. We found that strains lacking RpoS adapt less variably, in terms of both fitness increase and changes in patterns of transcription, than strains with functional RpoS. This phenotypic uniformity was caused by the same adaptive mutation in every independent population: the insertion of IS10 into the promoter of otsBA. OtsA and OtsB are required to synthesize the osmoprotectant trehalose, and transcription of otsBA requires RpoS in the wild-type genetic background. The evolved IS10 insertion rewires expression of otsBA from RpoS-dependent to RpoS-independent, allowing for partial restoration of wild-type response to osmotic stress. Our results show that the regulatory networks of bacteria Keywords: evolution; expression This study started with wild-type and rpoS- strains, and evolved five lines from each, for a total of 12 strains. Expression was measured for each strain with two separate biological replicates of RNA