The Context-Dependence of Mutations: A Linkage of Formalisms

Контекстная зависимость мутаций: взаимосвязь формализмов
Frank J. Poelwijk, Vinod Krishna, Rama Ranganathan
2016-06-23

background-averaged epistasisepistasisepistatic structuregenotype-phenotype-fitness relationshipweighted Walsh-Hadamard transform
OverviewDefining the extent of epistasis-the nonindependence of the effects of mutations-is essential for understanding the relationship of genotype, phenotype, and fitness in biological systems.The applications cover many areas of biological research, including biochemistry, genomics, protein and systems engineering, medicine, and evolutionary biology.However, the quantitative definitions of epistasis vary among fields, and its analysis beyond just pairwise effects remains problematic in general.Here, we bring together a number of previous results that show that different definitions of epistasis are versions of a single mathematical formalismthe weighted Walsh-Hadamard transform.We demonstrate that one of the definitions, the background-averaged epistasis, may be the most informative for describing the epistatic structure of a biological system.Key issues are the choice of effective ensembles for averaging and to practically contend with the vast combinatorial complexity of mutations.In this regard, we discuss strategies for optimally learning the epistatic structure of biological systems.
1
Background-averaged epistasis may be the most informative measure for characterizing a biological system’s epistatic structure.
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Different quantitative definitions of epistasis across biological fields can be unified as forms of the weighted Walsh–Hadamard transform.
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Meaningful background-averaged epistasis depends critically on selecting appropriate effective ensembles for averaging.
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The formalism provides a common framework for analyzing mutation effects beyond pairwise interactions.
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The paper discusses strategies for learning epistatic structure despite the combinatorial complexity of mutation spaces.

biological systems with mutational genotype–phenotype–fitness relationships

the mathematical formalization and characterization of epistasis, including background-averaged epistasis and strategies for learning epistatic structure

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2016-06-23
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Frank J. Poelwijk
Vinod Krishna
Rama Ranganathan
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