title: Evolutionary dynamics, epistatic interactions, and biological information.
abstract: We investigate a definition of biological information that connects population genetics with the tools of information theory by focusing on the distribution of genotypes found in a population. Previous research has treated loci as non-interacting by making specific approximations in the calculation of information-theoretic quantities. We expand earlier mathematical forms to include epistasis, or interactions between mutations at all pairs of loci. Application of our improved measure of biological information to evolution on two-locus, two-allele fitness landscapes demonstrates that mutual information between loci reflects epistatic interaction of mutations. Finally, we consider four-locus, two-allele fitness landscapes with modular structure. As modular interactions are inherently epistatic, we demonstrate that our refined approximation provides insight into the underlying structure of these non-trivial fitness landscapes.
authors.affiliation: Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA. streliof@msu.edu
authors.forename: Christopher C
authors.initials: CC
authors.lastname: Strelioff
authors.forename: Richard E
authors.initials: RE
authors.lastname: Lenski
authors.forename: Charles
authors.initials: C
authors.lastname: Ofria
mesh_terms: D000483:Alleles; D005075:Biological Evolution; D004843:Epistasis, Genetic; D056084:Genetic Fitness; D056426:Genetic Loci / Q000235:genetics; D005828:Genetics, Population; D006801:Humans; D007257:Information Theory; D008957:Models, Genetic; D011157:Population Dynamics; D013997:Time Factors