title: The spectrum of adaptive mutations in experimental evolution.
abstract: A primary goal of recent work in experimental evolution is to probe the molecular basis of adaptation. This requires an understanding of the individual mutations in evolving populations: their identity, their physiological and fitness effects, and the interactions between them. The combination of high-throughput methods for laboratory evolution and next-generation sequencing methods now makes it possible to identify and quantify mutations in hundreds of replicate populations over thousands of generations, and to directly measure fitness effects and epistatic interactions. Many laboratories are now leveraging these tools to study the molecular basis of adaptation and the reproducibility of evolutionary outcomes across a variety of model systems. Genetic analyses on evolved populations are shedding light on the statistics of epistasis between evolved mutations. Here we review the current understanding of the spectrum of mutations observed across these systems, with a focus on epistatic interactions between beneficial mutations and constraints on evolutionary outcomes. We emphasize evolution in asexual microbes, where next generation sequencing methods have been widely applied.
authors.affiliation: Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA. Electronic address: glang@lehigh.edu.
authors.forename: Gregory I
authors.initials: GI
authors.lastname: Lang
authors.affiliation: Department of Organismic and Evolutionary Biology, Department of Physics, FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA. Electronic address: mmdesai@fas.harvard.edu.
authors.forename: Michael M
authors.initials: MM
authors.lastname: Desai
mesh_terms: D000220:Adaptation, Biological; D019020:Directed Molecular Evolution / Q000379:methods*; D004843:Epistasis, Genetic; D019143:Evolution, Molecular; D056084:Genetic Fitness; D059014:High-Throughput Nucleotide Sequencing; D009154:Mutation
keywords: Adaptive mutations; Experimental evolution; Next-generation sequencing