title: A General Approximation for the Dynamics of Quantitative Traits.
abstract: Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly.
authors.affiliation: Institute of Science and Technology Austria (IST Austria), Klosterneuburg A-3400, Austria kbodova@ist.ac.at.
authors.forename: Katarína
authors.initials: K
authors.lastname: Bod'ová
authors.affiliation: Institute of Science and Technology Austria (IST Austria), Klosterneuburg A-3400, Austria.
authors.forename: Gašper
authors.initials: G
authors.lastname: Tkačik
authors.affiliation: Institute of Science and Technology Austria (IST Austria), Klosterneuburg A-3400, Austria.
authors.forename: Nicholas H
authors.initials: NH
authors.lastname: Barton
mesh_terms: D000465:Algorithms; D000483:Alleles; D005787:Gene Frequency; D040961:Genetic Drift; D006801:Humans; D008957:Models, Genetic; D009154:Mutation; D040641:Quantitative Trait Loci; D019655:Quantitative Trait, Heritable; D012641:Selection, Genetic
keywords: diffusion approximation, quasi-stationarity; maximum entropy; quantitative genetics