Measuring the statistics of pleiotropic and epistatic fitness effects of beneficial mutations during microbial adaptation across environments
Measuring the statistics of pleiotropic and epistatic fitness effects of beneficial mutations during microbial adaptation across environments
批准号:
9396806
负责人:
Parris Humphrey
金额:
$5.71万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-07-01 至 2019-06-30
关键词:
AffectArchitectureBiologicalBiological AssayCase StudyDNADependenceDrug resistanceEnvironmentEvolutionExperimental ModelsFrequenciesFutureGenesGeneticGenetic EnhancementGenetic EpistasisGenetic RecombinationGenomeGenotypeGoalsLinkMeasurementMeasuresModelingMutationOrganismOutcomeParasitesPatternPhenotypePopulationPopulation GeneticsProcessRecombinantsResearchRoleSaccharomyces cerevisiaeSaccharomycetalesShapesSourceSpeedSystemTestingTheoretical StudiesUncertaintyVariantWorkYeastsasexualbasecombinatorialfitnessgene environment interactiongene interactioninnovationmicrobialnoveloffspringpathogenpleiotropismpreventsexstatisticstraittumor progression
中文摘要
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英文摘要
Project Summary.
Two main sources of uncertainty can combine to make the outcome of adaptive evolution unpredictable: how
the effects of mutations on evolutionary fitness depend on either the environment (i.e. pleiotropy) or genotype
(i.e. epistasis) of the organism. By conferring substantial context dependence to the fitness effects of mutations,
epistasis and pleiotropy independently and jointly impact the repeatability—and thus predictability—of evolution
at phenotypic and genotypic levels. Yet we lack an empirical and conceptual basis for predicting their general
importance in evolution, leaving a fundamental question unanswered: how much of the future depends on the
past? The answers may be as pertinent to the causes of biological diversification and speciation as they are to
predicting cancer progression, parasite host switches, and the emergence of drug resistant pathogens—
adaptive processes for which predictability is greatly needed.
When studied in detail, pleiotropy and epistasis reveal important facets of how the genetic architecture of
organismal traits interacts with the environment to affect the outcomes of adaptation. This work moves beyond
case-studies by proposing to systematically measure the distribution of fitness effects of beneficial mutations
across environments, as well as how these effects change when paired with other mutations in the genome.
Progress on these fronts has been impeded by practical combinatorial limits to the gene–gene and gene–
environment interactions that can be assayed at once, as well as by the limited availability of study systems
allowing controlled manipulation of recombination to isolate its effect on the evolution of such interactions.
Using budding yeast as a model for microbial adaptation, the proposed work removes the combinatorial upper
limit that has for so long prevented estimation of the statistics of epistatic and pleiotropic mutational effects,
and permits an analysis of how recombination affects their role in evolution. This work uses innovative
sequencing-based approaches to track the fitness of thousands of genotypes via DNA barcodes in bulk across
a wide range of environments, and will reveal the statistical context in which important forms of pleiotropy (e.g.
trade-offs) actually tend to arise. Additionally, this work tests how the effects, and genetic basis, of epistasis
and pleiotropy evolve differently in sexual versus asexual populations, by using DNA barcode fitness tracking
of thousands of recombinant offspring across multiple environments. Together, this work will provide a
comprehensive study of classic but poorly measured evolutionary quantities that impact the genetic and
phenotypic dynamics of adaptation and its predictability.
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