1. Local fitness landscapes predict yeast evolutionary dynamics in directionally changing environments
- Author
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Mark G. M. Aarts, Bas J. Zwaan, Florien A. Gorter, and J. Arjan G. M. de Visser
- Subjects
0106 biological sciences ,0301 basic medicine ,Genotype-environment interaction ,Environmental change ,Fitness landscape ,Population ,Genetic Fitness ,Saccharomyces cerevisiae ,Investigations ,Environment ,Biology ,Laboratorium voor Erfelijkheidsleer ,010603 evolutionary biology ,01 natural sciences ,Evolution, Molecular ,03 medical and health sciences ,Yeasts ,Genetics ,Predicting evolution ,Groep Koornneef ,Fitness landscapes ,Evolutionary dynamics ,education ,skin and connective tissue diseases ,Experimental evolution ,education.field_of_study ,Ecology ,High-Throughput Nucleotide Sequencing ,Replicate ,PE&RC ,030104 developmental biology ,Metals ,Mutation ,Gene-Environment Interaction ,Laboratory of Genetics ,sense organs ,Genome, Fungal ,Adaptation ,EPS - 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.
- Published
- 2018