Evidence map›Paper›PMID 29141909›Full record

ArticleGenetics2018

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

Florien A Gorter, Mark G M Aarts, Bas J Zwaan, J Arjan G M de Visser

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Epistasis decreases with increasing antibiotic pressure but not temperature.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Recombination drives the evolution of mutational robustness.Current opinion in systems biology · 2019
    Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Florien A GorterLaboratory of Genetics, Wageningen University, 6708PB, The Netherlands floriengorter@gmail.com mark.aarts@wur.nl bas.zwaan@wur.nl arjan.devisser@wur.nl.ORCID http://orcid.org/0000-0002-5992-8538
Mark G M AartsLaboratory of Genetics, Wageningen University, 6708PB, The Netherlands.ORCID http://orcid.org/0000-0001-5257-0740
Bas J ZwaanLaboratory of Genetics, Wageningen University, 6708PB, The Netherlands.
J Arjan G M de VisserLaboratory of Genetics, Wageningen University, 6708PB, The Netherlands.
Wageningen University & Research · NLSwiss Federal Institute of Aquatic Science and Technology · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

EnvironmentEvolution, MolecularGenetic FitnessGene-Environment InteractionGenome, FungalHigh-Throughput Nucleotide SequencingMetalsMutationSaccharomyces cerevisiaeYeastsMetalsexperimental evolutionfitness landscapesgenotype-environment interactionpredicting evolutionSaccharomyces cerevisiae

Identifiers

PMID29141909
PMCPMC5753865
OpenAlexW2768474856

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.