4.4 Article

The Impact of Macroscopic Epistasis on Long-Term Evolutionary Dynamics

期刊

GENETICS
卷 199, 期 1, 页码 177-U639

出版社

GENETICS SOCIETY AMERICA
DOI: 10.1534/genetics.114.172460

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资金

  1. National Science Foundation (NSF) Graduate Research Fellowship
  2. James S. McDonnell Foundation
  3. Alfred P. Sloan Foundation
  4. NSF [PHY 1313638]
  5. National Institutes of Health [GM104239]
  6. Research Computing Group at Harvard University
  7. Harvard Milton Fund
  8. Direct For Mathematical & Physical Scien
  9. Division Of Physics [1313638] Funding Source: National Science Foundation

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Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of epistasis over 50,000 generations in a well-studied laboratory evolution experiment in Escherichia coli. The extensive duration of this experiment provides a unique window into the effects of epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with a two-epoch model of adaptation, in which an initial burst of diminishing-returns epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of epistasis that are compatible with all of the experimental data.

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