Ontology highlight
ABSTRACT:
PROVIDER: PRJNA781980 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16989301_1.fastq.gz | Fastqsanger.gz | |||
| SRR16989301_2.fastq.gz | Fastqsanger.gz | |||
| SRR16989302_1.fastq.gz | Fastqsanger.gz | |||
| SRR16989302_2.fastq.gz | Fastqsanger.gz | |||
| SRR16989303_1.fastq.gz | Fastqsanger.gz |
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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.
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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.
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Project description:Extreme positive epistasis for fitness in monosomic yeast strains - part 1
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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.
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