Quantitative analyses of empirical fitness landscapes

By I. Szendro, Martijn F. Schenk, J. Franke, Joachim Krug, J. Visser. 2012

236 citations recorded by the source corpus.

The concept of a fitness landscape is a powerful metaphor that offers insight into various aspects of evolutionary processes and guidance for the study of evolution. Until recently, empirical evidence on the ruggedness of these landscapes was lacking, but since it became feasible to construct all possible genotypes containing combinations of a limited set of mutations, the number of studies has grown to a point where a classification of landscapes becomes possible. The aim of this review is to identify measures of epistasis that allow a meaningful comparison of fitness landscapes and then apply them to the empirical landscapes in order to discern factors that affect ruggedness. The various measures of epistasis that have been proposed in the literature appear to be equivalent. Our comparison shows that the ruggedness of the empirical landscape is affected by whether the included mutations are beneficial or deleterious and by whether intragenic or intergenic epistasis is involved. Finally, the empirical landscapes are compared to landscapes generated with the rough Mt Fuji model. Despite the simplicity of this model, it captures the features of the experimental landscapes remarkably well.

Subfields: Genetics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/4191288d82a7b8fdeee884bad7e54445379b4e1a

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Citations in the corpus

Adaptation in protein fitness landscapes is facilitated by indirect paths (2016, methodology): “By coupling state-of-the-art experimental techniques with novel quantitative analysis of fitness landscapes, this work takes the optimistic view that we can push the boundary further and discover new mechanisms underlying evolution (Fisher et al., 2013; Desai, 2013; Szendro et al., 2013] ).”
Patterns of Epistasis between Beneficial Mutations in an Antibiotic Resistance Gene (2013, methodology): “following the procedure described in Tokuriki et al. (2007). The TEM-1 structure (PDB: 1XPB) was used to calculate the”
Inferring the shape of global epistasis (2018, background): “Nonepistatic models often explain much of the variance in genotype-phenotype maps, but there is usually a significant portion of unexplained variance that cannot be accounted for, given the known magnitudes of measurement errors [34].”