Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1223397 | ENA |
REPOSITORIES: ENA
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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:Lung adenocarcinoma, the most common subtype of lung cancer, is genomically complex, with tumors containing tens to hundreds of non-synonymous mutations. However, little is understood about how genes interact with each other to enable the evolution of cancer in vivo, largely due to a lack of methods for investigating genetic interactions in a high-throughput and quantitative manner. Here, we employed a novel platform to generate tumors with all pairwise inactivation of ten diverse tumor suppressor genes within an autochthonous mouse model of oncogenic KRAS-driven lung cancer. By quantifying the fitness of tumors with every single and double mutant genotype, we show that most tumor suppressor genetic interactions exhibited negative epistasis, with diminishing returns on tumor fitness. In contrast, Apc inactivation showed positive epistasis with the inactivation of several other genes, including synergistic effects on tumor fitness in combination with Lkb1 or Nf1 inactivation. Sign epistasis was extremely rare, suggesting a surprisingly accessible fitness landscape during lung tumorigenesis. These findings greatly expand our understanding the evolutionary interactions that drive tumorigenesis in vivo.
2025-01-01 | GSE281604 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE24770: Heterochronic Evolution Reveals Modular Timing Changes in Budding Yeast Transcriptomes (Mutation Accumulation Lines) GSE24771: Heterochronic Evolution Reveals Modular Timing Changes in Budding Yeast Transcriptomes (Natural Strain Timecourse) Refer to individual Series
2010-10-19 | E-GEOD-24772 | biostudies-arrayexpress
Project description:Extreme positive epistasis for fitness in monosomic yeast strains - part 2
| PRJNA1159774 | ENA
Project description:Extreme positive epistasis for fitness in monosomic yeast strains - part 1
| PRJNA901440 | ENA
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:Interpreting variants in recessive diseases is difficult because clinical severity depends on the combined function of both alleles. Deep mutational scanning (DMS) experiments can provide functional measurements at scale, but their scores often relate nonlinearly to true biochemical activity. We developed a general method to infer enzymatic activities for thousands of variants by running two fitness assays at different expression levels and modelling the nonlinear activity–fitness relationship. These inferred activities allow computation of a biallelic pathogenicity score that captures the joint effect of two alleles. We applied this to adenylosuccinate lyase (ADSL), quantifying the effects of >8,000 coding variants in a yeast-based assay. The inferred activities separated pathogenic from benign alleles, and the biallelic score correlated strongly with biochemical measurements from patient-derived cells, outperforming existing predictors. This framework provides a broadly applicable strategy for mechanistic interpretation of variants in recessive enzymes.
2026-02-01 | GSE313314 | GEO
Project description:The extent to which carbon flux is directed towards fermentation vs. respiration differs between cell types and environmental conditions. Understanding the basic cellular processes governing carbon flux is challenged by the complexity of the metabolic and regulatory networks. To reveal the genetic basis for natural diversity in channeling carbon flux, we applied Quantitative Trait Loci analysis by phenotyping and genotyping hundreds of individual F2 segregants of budding yeast that differ in their capacity to ferment the pentose sugar xylulose. Causal alleles were mapped to the RXT3 and PHO23 genes, two components of the large Rpd3 histone deacetylation complex. We show that these allelic variants modulate the expression of SNF1/AMPK-dependent respiratory genes. Our results suggest that over close evolutionary distances, diversification of carbon flow is driven by changes in global regulators, rather than adaptation of specific metabolic nodes. Such regulators may improve the ability to direct metabolic fluxes for biotechnological applications. mRNA profiles of S. cerevisiae strain BY4741 with either the RXT3 or PHO23 genes either deleted, replaced by S. cerevisiae T73 allele or replaced by S. cerevisiae PHO23 allele
2015-12-04 | E-GEOD-75673 | biostudies-arrayexpress
Project description:SSD1 is a polymorphic locus in budding yeast with many pleiotropic effects. Our lab had previously done transcript microarray of W303a in an ssd1-d background, and here we have carried out another transcript microarray across the cell cycle in an isogenic SSD1-V background. We find that a large fraction of budding yeast transcripts is differentially expressed in these cells. Ssd1 has recently been shown to bind mRNAs in vivo, but very few of these mRNAs show significant changes in levels in the SSD1-V versus ssd1-d comparison. About 20% of cell cycle-regulated transcripts are affected by SSD1-V and most of these transcripts show sharper amplitudes of oscillation in SSD1-V cells. Many transcripts whose gene products influence longevity are also affected, the largest class of which are involved in translation. Ribosomal protein mRNAs are globally down-regulated by SSD1-V.
2009-09-01 | GSE16911 | GEO