Ontology highlight
ABSTRACT:
PROVIDER: PRJNA815849 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Characterization of the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here, we reconstruct the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. We find that the His3 fitness landscape is dominated by synergistic epistasis, such that the cumulative effect of amino acid substitutions causes a dramatic decline in fitness. Furthermore, in 63% of sites substitutions were strongly positive in one genetic background and strongly negative in another, with 41% of sites showing reciprocal sign epistasis. This sign epistasis, present in proportionally few genotypes, was caused by simultaneous interaction of multiple sites with demonstrating a complex multidimensional nature of the His3 fitness landscape.
2017-07-02 | GSE99990 | GEO
Project description:Metabolic imbalances underlie a large spectrum of diseases, spanning congenital and chronic conditions and cancer. Our ability to explain and predict such imbalances remains severely limited by the diversity of underlying mutation effects and their dependence on the genetic background and environment, but it is unclear whether these complicating factors can be reduced to simple quantitative rules. To characterise their interplay in determining cell physiology and fitness, we systematically quantified almost 4,000 interactions between expression variants of two genes of a well-known sugar-utilisation pathway containing a toxic metabolite in the model bacterium, Escherichia coli, in different environments. We detect a remarkable variety of types and trends of intergenic interaction in this linear pathway, which cannot be reliably predicted from the effects of each variant in isolation, along with a dependence of this epistasis on the environment. Despite this apparent complexity, the fitness consequences of interactions between alleles and environment are explained by a mechanistic model accounting for catabolic flux and toxic metabolite concentration. Our findings reveal how, contrary to a common assumption, the nature of fitness interactions is governed by more than just the topology of the molecular network underlying a selected trait. Our prospects of predicting disease and evolution will therefore improve by expanding our knowledge of the links among proteome, metabolome and physiology.
2018-09-15 | GSE115725 | GEO
Project description:Antimicrobial resistance (AMR) poses a threat to global health and the economy. Rifampicin resistant Mycobacterium tuberculosis accounts for a third of the global AMR burden. Gaining the upper hand on AMR requires a deeper understanding of the physiology of resistance. AMR often results in the erosion of normal cell function: a fitness cost. Identifying intervention points in the mechanisms underpinning the cost of resistance in M. tuberculosis could play a pivotal role in strengthening future treatment regimens. We used a collection of M. tuberculosis strains providing an evolutionary and phylogenetic snapshot of rifampicin resistance and subjected them to genome-wide transcriptomic and proteomic profiling to identify key perturbations of normal physiology. We found that a rifampicin resistance-conferring mutation in RpoB imparts considerable gene expression changes, many of which are mitigated by a compensatory mutation in RpoC. However, our data also provide evidence for pervasive epistasis: the same resistance mutation imposed a different fitness cost and functionally unrelated changes to gene expression in clinical strains from unrelated genetic backgrounds. Rather than functional changes in specific pathways, our data suggest that the fitness cost of rifampicin resistance stems from a misallocation of resources: the greater the departure from the wild type baseline proteome investment, the greater the fitness cost of rifampicin resistance in a given strain. We summarize these observations in the “Burden of Expression” hypothesis of fitness cost and provide evidence that it can be used for suppressing the emergence of rifampicin resistance.
2021-03-12 | PXD011568 | Pride
Project description:Pazopanib is a drug with idiosyncratic hepatotoxicity risk. Analysis of gene expression changes after exposing hepatocytes can indicate effects on specific biological pathways and potential mechanisms of hepatotoxicity. HLCs derived from patient-specific iPSCs were treated with pazopanib to identify both drug-related global effects and patient-specific effects
2016-09-30 | GSE75888 | GEO
Project description:To unravel the underlying mechanisms of inflammation-related idiosyncratic drug toxicity
2017-07-29 | GSE102006 | GEO
Project description:Adaptive laboratory evolution is highly effective for improving desired traits through natural selection. However, its applicability is inherently constrained to growth-correlated traits precluding traits of interest that incur a fitness cost, such as metabolite secretion. Here, we introduce the concept of tacking trait enabling natural selection of fitness-costly metabolic traits. The concept is inspired from the tacking maneuver used in sailing for traversing upwind. We use first-principle metabolic models to design an evolution niche wherein the tacking trait and fitness become correlated. Adaptive evolution in this niche, when followed by the reversal to the original niche, manifests in the improvement of the desired trait due to biochemical coupling between the tacking and the desired trait. We experimentally demonstrated this strategy, termed EvolveX, by evolving wine yeasts for increased aroma production. RNA-sequencing was performed for parental and evolved strains in the respective evolution niche and in natural grape must.
2021-12-30 | E-MTAB-10019 | biostudies-arrayexpress
Project description:Gene expression profiles of in vitro selected highly metastatic MKN45-GFP sublines. The results were compared with MKN45-GFP control cell line to determine the metastasis associated genes. Four pairs compared experiment. Each pair was used MKN45-GFP cells as correlated control. Determining on the gene expression trends were by various metastatic ability of each subline.
2011-11-10 | E-GEOD-33570 | biostudies-arrayexpress
Project description:To obtain the global gene expression trends during ovule development, we collected samples of the gynoecium in developmental stages 9–10, 11, and 12 with three biological replicates to perform microarray assay.
2020-12-08 | GSE162759 | GEO