Ontology highlight
ABSTRACT:
PROVIDER: PRJNA751388 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The hypothesis that increased fitness within a selective environment must be accompanied by a loss of fitness in other non-selective environments leads to the notion of evolutionary tradeoffs. Experimental evolution provides an approach to test the existence of evolutionary tradeoffs, characterize their general quality, and reveal their genetic origins. To examine the underlying mechanism for a fitness trade-off, we constructed the evolutionary trajectories of Escherichia coli K-12 at increasing temperatures up to 45.3°C, and found diverging mutational histories that led to adaptive phenotypes with and without fitness trade-offs at low temperatures. We identified genetic changes in cellular respiration, iron metabolism and methionine biosynthesis that regulated gene expression to achieve thermal adaptation and determined the presence and absence of a fitness trade-off. Our results suggested that evolutionary trade-off could be generated by a regulatory protein mutation that was beneficial in the selective conditions but forced suboptimal proteome allocation under non-selective environments.
2020-11-17 | GSE140478 | GEO
Project description:In Escherichia coli, the highly conserved enzymes MiaA and MiaB mediate the sequential prenylation and methylthiolation of adenosine-37 within tRNAs that decode UNN codons. We found that MiaA, but not MiaB, is critical to the fitness and virulence of extraintestinal pathogenic E. coli (ExPEC), a major cause of urinary tract and bloodstream infections. Deletion of miaA has pleiotropic effects, attenuating bacterial fitness and virulence within diverse host environments and rendering ExPEC especially sensitive to stressors like nitrogen and oxygen radicals and osmotic shock. We find that stress can stimulate striking changes in miaA expression. To assess how changing MiaA levels affect the pathogen proteome, we used MS to analyze the proteins express by the reference ExPEC isolate UTI89 and derivatives that either lack or overexpress MiaA.
2022-02-14 | PXD024782 | Pride
Project description:Protein synthesis is costly and the proteome size is constrained. Using a genome-scale computational model of proteome allocation together with absolute proteomics data sets from many growth environments, we determine how these fundamental limitations constrain growth and fitness in Escherichia coli. First, we show that the observed variation in growth rates across environments is largely determined by the expression of protein not utilized for growth in a given environment. We then elucidate the overall transcriptional regulatory logic that underlies the expression of unused protein. We systematically classify the unused proteome into segments devoted to environmental readiness and stress resistance functions. While expression of these proteome segments incurs a fitness cost of decreased growth in a fixed environment, they provide fitness benefits in a changing environment. Thus, the systems biology of the prokaryotic proteome can be quantitatively understood based on resource allocation to growth, environmental readiness, and stress resistance functions.
2018-08-01 | GSE72020 | GEO
Project description:A fitness landscape (FL) describes the genotype-fitness relationship in a given environment. To explain and predict evolution, it is imperative to measure the FL in multiple environments because the natural environment changes frequently. Using a high-throughput method that combines precise gene replacement with next-generation sequencing, we determine the in vivo FL of a yeast tRNA gene comprising over 23,000 genotypes in four environments. Although genotype-by-environment interaction (G×E) is abundantly detected, its pattern is so simple that we can transform an existing FL to that in a new environment with fitness measures of only a few genotypes in the new environment. Under each environment, we observe prevalent, negatively biased epistasis between mutations (G×G). Epistasis-by-environment interaction (G×G×E) is also prevalent, but trends in epistasis difference between environments are predictable. Our study thus reveals simple rules underlying seemingly complex FLs, opening the door to understanding and predicting FLs in general.
2018-03-23 | GSE111508 | GEO
Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation that were sexually selected Sexual selection is predicted to have widespread effects on the genetic variation generated by new mutations as a consequence of the genic capture of condition by male sexual traits. We manipulated the opportunity for sexual selection on males during 27 generations of mutation accumulation in inbred lines of Drosophila serrata, and used a microarray platform to investigate the effect of sexual selection on the expression of 2685 genes, representing a broad coverage of biological function. Sexual selection had little effect on mean gene expression levels, with only 4 genes diverging significantly at a false discovery rate of 5% . In contrast, sexual selection impacted on both the magnitude and nature of mutational variance accumulating in these genes. The magnitude of mutational variance increased under sexual selection by an average of 29%. Mutational variance was less commonly generated by extreme phenotypes less commonly under sexual selection. Furthermore, analysis of random sets of five genes revealed that the mutational variance that accumulated under sexual selection was less pleiotropic in nature than that found in the absence of sexual selection. The generation of greater mutational variance without a general concomitant change in mean expression under sexual selection suggested that gene expression traits were be under apparent rather than direct sexual selection. We discuss two main explanations for the broad-based increase in mutational variance under sexual selection that both require extensive pleiotropy between traits affecting male mating success, standard metric traits represented here by gene expression traits, and general fitness. We measured gene expression of male Drosophila serrata from 41 mutation accumulation lines (whole-body) that were sexually selected. Data from two replicates for each line are presented.
2014-03-01 | E-GEOD-54777 | biostudies-arrayexpress
Project description:In some of the earliest uses of genome-wide gene-expression microarrays and array-based Comparative Genomic Hybridization (aCGH), a set of diploid yeasts that had undergone experimental evolution under aerobic glucose limitation was used to explore how gene expression and genome structure had responded to this selection pressure. To more deeply understand how adaptation to one environment might constrain or enhance performance in another we have now identified the adaptive mutations in this set of clones using whole-genome sequencing, and have assessed whether the evolved clones had become generalists or specialists by assaying their fitness under three contrasting growth environments: aerobic and anaerobic glucose limitation and aerobic acetate limitation. Additionally, evolved clones and their common ancestor were assayed for gene expression, biomass estimates and residual substrate levels under the alternative growth conditions. Relative fitnesses were evaluated by competing each clone against a common reference strain in each environment. Unexpectedly, we found that the evolved clones also outperformed their ancestor under strictly fermentative and strictly oxidative growth conditions. We conclude that yeasts evolving under aerobic glucose limitation become generalists for carbon limitation, as the mutations selected for in one environment are advantageous in others. High-throughput sequencing of the evolved clones uncovered mutations in genes involved in glucose sensing, signaling, and transport that in part explain these physiological phenotypes, with different sets of mutations found in independently-evolved clones. Earlier gene expression data from aerobic glucose-limited cultures had revealed a shift from fermentation towards respiration in all evolved clones explaining increased fitness in that condition. However, because the evolved clones also show higher fitness under strictly anaerobic conditions and under conditions requiring strictly respirative growth, this switch cannot be the sole source of adaptive benefit. Furthermore, because independently evolved clones are genetically distinct we conclude that there are multiple mutational paths leading to the generalist phenotype. Strain Name: Parental strain (CP1AB) or evolved clones (E1 - E5) Media: aerobic / anaerobic 36 hybridizations
2011-11-02 | E-GEOD-25081 | biostudies-arrayexpress
Project description:The high mutation rate of RNA viruses provides viral populations with the ability to adapt to new environments but also makes them vulnerable to extinction due to the deleterious effects of mutations, which is the conceptual basis for the antiviral activity of RNA mutagens. However, there are still gaps in the quantitative understanding of the dynamics between the mutations induced by an RNA mutagen and its effects on viral fitness. To address this, we used Venezuelan Equine Encephalitis Virus (VEEV) and the potent RNA mutagen β-d-N4-hydroxycytidine (NHC) as a model to analyze virus replication competency and mutation frequency following treatment in the total and replication-competent viral populations separately. We found that NHC induced transition mutations in a concentration dependent manner in the total population, while the replication-competent population maintained itself within an increased, yet narrow, mutation spectrum. The incorporation of NHC mainly happened during the positive sense RNA synthesis of VEEV. A growth kinetic analysis of VEEV population treated with NHC pointed to a lower but more diverse distribution in mutational fitness, demonstrating that NHC-induced mutations negatively and broadly affect the fitness of the virus. Together, our study provides mechanistic insight into how RNA mutagens affect viral population landscape and the potential of RNA mutagens as an antiviral strategy for alphaviruses.
2024-10-25 | GSE207136 | GEO
Project description:In Arabidopsis thaliana a high rate of spontaneous epigenetic variation can occur in the DNA methylome in the absence of genetic variation and selection. It has been of great interest, whether natural epigenetic variation is subject to selection and contributes to fitness and adaptation in selective environments. We compared the variation in selected phenotypic traits, genome-wide cytosine DNA methylation and gene expression in two Arabidopsis recombinant inbred lines, which had undergone five generations of selection in experimental landscapes relative to their genetically identical ancestors. Selected populations exerted significant differences in flowering time and the number of branches and fruits, differences that were maintained over two to three generations in the absence of selection. We identified 4,629 and 5,158 differentially methylated cytosines which were overrepresented in genes that regulate flowering time, epigenetic processes, development and morphogenesis. Differentially methylated genes were enriched in differentially expressed genes. Thus, epigenetic variation is subject to selection and may play an important role in the adaptive response of populations in rapidly changing natural environments. Genomic DNA was extracted from whole-plant above-ground tissue of individual 25-day-old plants with the Qiagen DNeasy kit (Qiagen). DNA from two randomly chosen CVL39 individuals from ancestral (A3) lines and from 7 selected (S3) lines that had experienced 5 generations of selection in the three replicated dynamic landscapes (2xD1, 3xD5,2xD6) was sequenced (paired-end, 100 bp) using the Illumina Highseq 2000 Instrument. Single nucleotide polymorphisms and TE insertions were mapped with respect to the recombinant reference genome and compared between selected and ancestral lines.
2014-09-01 | E-GEOD-47490 | biostudies-arrayexpress