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ZENODO
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Data sources: Datacite
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Data from: Avoiding dead ends: the experimental evolution of constraint as adaptation to environmental variation

Authors: Raghu, Shravan Ram; Smith, Myron; Simons, Andrew;

Data from: Avoiding dead ends: the experimental evolution of constraint as adaptation to environmental variation

Abstract

A bet-hedging strategy is suboptimal over short timescales, but optimal over long time scales because it buffers temporal variance in fitness. However, it is unclear how such strategies can persist when selection is expected to purge suboptimal traits in the short term. It has been proposed that the persistence of bet hedging is possible only if adaptive evolution is constrained in the short-term (Simons, 2002). To test the constraint-as-adaptation hypothesis, we take an experimental evolution approach using Saccharomyces cerevisiae and predict that evolution under reduced-frequency detrimental events results in an increase in evolution-resistant bet-hedging. Specifically, we evolve bet-hedging by imposing fluctuating selection through repeated heat shocks separated by intervening benign environments in which the frequency of extreme environments is reduced across two sequential evolution regimes (Regimes A and B). Then, to measure evolved constraints lines from both regimes are further evolved under extended benign conditions for ~150 generations and tested for the loss of heat shock tolerance. This dataset provides heat shock tolerance and competitive fitness data for replicate lines evolved in both regimes, and for the T1 ancestor. This dataset also provides these trait measurements after the replicate lines from both regimes are further evolved under extended benign conditions.

Data was collected from trait assays that were run simultaneously for all strains. Lines from the end of Regime A (EoR-A) and from the end of Regime B (EoR-B) were originally evolved from the T1 Ancestor which has an S288C background (MATα SUC2 gal2 mal2 mel flo1 flo8-1 hap1 ho bio1 bio6). The sequential experimental design implies that evolution proceeded along: T1 Ancestor --> Regime A (8 replicate lines) --> Regime B (8 replicate lines). Heat Shock Tolerance was measured as % Survival on exposure to a transient 54°C heat shock for 75 mins. Relative fitness was calculated using a competitive fitness assay with a reference strain, YIR044CΔ with a BY4741 background (MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0). This strain has the pseudogene YIR044C deleted and replaced with a gene conferring G418 resistance—used as a selectable marker for this assay. Proportions of focal strain/test population relative to the reference strain both before and after the competition were determined by plating on YPD agar with and without G418. Relative fitness was calculated as described in Wong et al. (2012), where the selection coefficient was determined using the following equation. Fitness w was calculated as 1+ s.

Experimental evolution and heat shock tolerance assays were performed in Synthetic Defined Media (SDM) containing 6.7 g of Yeast Nitrogen Base (without amino acids with ammonium sulfate) and 2% dextrose per liter. Competition experiments were performed in SDM+ Histidine (10 mg/L), Leucine (30 mg/L), Methionine (10 mg/L), Uracil (10 mg/L) to account for auxotrophies in the reference strain. Funding provided by: Natural Sciences and Engineering Research CouncilROR ID: https://ror.org/01h531d29Award Number:

Related Organizations
Keywords

rate of evolution, stasis, constraint, extinction, Adaptive tracking, Constraints, Macroevolution, Experimental Evolution, bet hedging, evolvability, Environmental stochasticity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average