Inferring genetic interactions from comparative fitness data

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incomp...

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Bibliographic Details
Published in:eLife 2017-12, Vol.6
Main Authors: Crona, Kristina, Gavryushkin, Alex, Greene, Devin, Beerenwinkel, Niko
Format: Article
Language:English
Subjects:
Antibiotic resistance
Antibiotics
Aspergillus niger - genetics
Aspergillus niger - physiology
beta-Lactamases - genetics
Competition
Computational and Systems Biology
Drug resistance
Epistasis
Epistasis, Genetic
Experiments
fitness graph
fitness landscape
gene interactions
Genetic diversity
Genetic Fitness
Genotype
Genotypes
HIV-1 - genetics
HIV-1 - physiology
Malaria
Mutation
partial order
Plasmodium vivax - genetics
Plasmodium vivax - physiology
Population
rank order
Reproductive fitness
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Summary:Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite , the fungus , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.
ISSN:2050-084X
2050-084X
DOI:10.7554/eLife.28629