Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 532087
Title Local fitness landscapes predict yeast evolutionary dynamics in directionally changing environments
Author(s) Gorter, Florien A.; Aarts, Mark G.M.; Zwaan, Bas J.; Visser, J.A.G.M. de
Source Genetics 208 (2018)1. - ISSN 0016-6731 - p. 307 - 322.
DOI http://dx.doi.org/10.1534/genetics.117.300519
Department(s) Laboratory of Genetics
EPS
Groep KoornneefGroep Koornneef
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2018
Keyword(s) Experimental evolution - Fitness landscapes - Genotype-environment interaction - Predicting evolution - Saccharomyces cerevisiae
Abstract The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change.
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