title: Populations adapt to fluctuating selection using derived and ancestral allelic diversity.
abstract: Populations can adapt to changing environments by using allelic diversity, yet whether diversity is recently derived or ancestral is often debated. Although evolution could productively use both types of diversity in a changing environment, their relative frequency has not been quantified. We address this question experimentally using budding yeast strains that harbor a tandem repeat containing URA3 gene, which we expose to cyclical selection and counterselection. We characterize and quantify the dynamics of frameshift events in the URA3 gene in eight populations over 12 cycles of selection and find that ancestral alleles account for 10-20% of all adaptive events. Using a general model of fluctuating selection, we determine how these results depend on mutation rates, population sizes, and fluctuation timescales. We quantify the contribution of derived alleles to the adaptation process using the de novo mutation rate along the population's ancestral lineage, a novel measure that is applicable in a wide range of settings. We find that the adaptive dynamics undergoes a sharp transition from selection on ancestral alleles to selection on derived alleles as fluctuation timescales increase. Our results demonstrate that fluctuations can select between different modes of adaptation over evolutionary timescales.
authors.affiliation: Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, 10003.
authors.forename: Wei-Hsiang
authors.initials: WH
authors.lastname: Lin
authors.affiliation: Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, 10003.
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Rocco
authors.affiliation: Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, 10003.
authors.forename: Amelia
authors.initials: A
authors.lastname: Bertozzi-Villa
authors.affiliation: Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, 10003.|Department of Physics, New York University, New York, New York, 10003.
authors.forename: Edo
authors.initials: E
authors.lastname: Kussell
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics; D000483:Alleles; D005075:Biological Evolution; D004777:Environment; D059645:Mutation Rate; D004718:Saccharomycetales / Q000235:genetics* / Q000502:physiology; D012641:Selection, Genetic; D013997:Time Factors
keywords: Adaptation; experimental; fitness; genetic variation; models/simulations; mutations; selection