Evidence map›Paper›PMID 24586190›Full record

ArticlePLoS genetics2014

Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.

Hsin-Hung Chou, Nigel F Delaney, Jeremy A Draghi, Christopher J Marx

Abstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
–field-weighted citation impact
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

50 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Evolution of pollutant biodegradation.Applied microbiology and biotechnology · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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.

Hsin-Hung ChouDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America ; Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Nigel F DelaneyDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.
Jeremy A DraghiDepartment of Zoology, University of British Columbia, Vancouver, Canada ; Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Christopher J MarxDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America ; Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.

Funding

Systems-level physiological basis of selection and epistasis in adaptationR01GM078209 · NIGMS · HARVARD UNIVERSITY · PI MARX, CHRISTOPHER J · 2007 to 2011
$1.7M
NIGMS NIH HHS GM078209NIGMS NIH HHS R01 GM078209
6 · The paper itself

Abstract

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.

Indexed as

Epistasis, GeneticEvolution, MolecularGenetic FitnessAdaptation, PhysiologicalGene Expression Regulation, EnzymologicMethylobacterium extorquensMutationPhenotypeSelection, Genetic

Identifiers

PMID24586190
PMCPMC3937219

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.