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Antagonistic pleiotropy conceals molecular adaptations in changing environments
Piaopiao Chen1, Jianzhi Zhang2
1Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA.
Nature Ecology & Evolution
|February 12, 2020
Summary
Environmental changes in nature may cause molecular adaptations to appear less frequent than they are. Frequent environmental shifts can make beneficial mutations harmful, hindering their fixation and underestimating positive selection.
Area of Science:
- Molecular Evolution
- Evolutionary Biology
- Genomics
Background:
- The role of positive selection in molecular evolution is debated, with lab studies showing frequent adaptation while natural evolution suggests otherwise.
- This discrepancy may stem from environmental changes in nature, where mutations beneficial at one time can become deleterious due to antagonistic pleiotropy.
Purpose of the Study:
- To investigate the impact of changing environments on the rate of molecular adaptation.
- To test the hypothesis that environmental fluctuations hinder the fixation of beneficial mutations, leading to an underestimation of positive selection in natural populations.
Main Methods:
- Yeast evolution experiments were conducted in both changing and constant environments.
- Genome sequencing was used to analyze the evolving populations and quantify mutation rates.
- Population genetic simulations were performed to support the experimental findings.
Main Results:
- The ratio of nonsynonymous to synonymous nucleotide changes was lower in changing environments compared to constant ones.
- Population dynamics of mutations supported the hypothesis that environmental changes impede adaptation.
- Antagonistic fitness effects of mutations in dynamic environments were observed.
Conclusions:
- Environmental variability in nature can lead to an underestimation of molecular adaptation.
- Antagonistic pleiotropy in fluctuating environments significantly impacts the fixation of mutations.
- The true rate of positive selection in natural populations may be higher than currently inferred from genomic data.
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