1. Evolutionary Biology
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Dynamics and variability in the pleiotropic effects of adaptation in laboratory budding yeast populations

  1. Christopher W Bakerlee
  2. Angela M Phillips
  3. Alex N Nguyen Ba
  4. Michael M Desai  Is a corresponding author
  1. Harvard University, United States
Research Article
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Cite this article as: eLife 2021;10:e70918 doi: 10.7554/eLife.70918

Abstract

Evolutionary adaptation to a constant environment is driven by the accumulation of mutations which can have a range of unrealized pleiotropic effects in other environments. These pleiotropic consequences of adaptation can influence the emergence of specialists or generalists, and are critical for evolution in temporally or spatially fluctuating environments. While many experiments have examined the pleiotropic effects of adaptation at a snapshot in time, very few have observed the dynamics by which these effects emerge and evolve. Here, we propagated hundreds of diploid and haploid laboratory budding yeast populations in each of three environments, and then assayed their fitness in multiple environments over 1000 generations of evolution. We find that replicate populations evolved in the same condition share common patterns of pleiotropic effects across other environments, which emerge within the first several hundred generations of evolution. However, we also find dynamic and environment-specific variability within these trends: variability in pleiotropic effects tends to increase over time, with the extent of variability depending on the evolution environment. These results suggest shifting and overlapping contributions of chance and contingency to the pleiotropic effects of adaptation, which could influence evolutionary trajectories in complex environments that fluctuate across space and time.

Data availability

Raw amplicon sequencing reads have been deposited in the NCBI BioProject database with accession number PRJNA739738. Source data files are listed in appropriate figure legends. Analysis code is available at https://github.com/amphilli/pleiotropy-dynamics.

The following data sets were generated

Article and author information

Author details

  1. Christopher W Bakerlee

    Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Angela M Phillips

    Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9806-7574
  3. Alex N Nguyen Ba

    Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Michael M Desai

    Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
    For correspondence
    mdesai@oeb.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9581-1150

Funding

National Defense Science and Engineering Graduate

  • Christopher W Bakerlee

National Institutes of Health (GM007598)

  • Christopher W Bakerlee

Howard Hughes Medical Institute (Hanna H. Gray Postdoctoral Fellowship)

  • Angela M Phillips

National Science Foundation (PHY-1914916)

  • Michael M Desai

National Institutes of Health (GM104239)

  • Michael M Desai

Harvard University (FAS Division of Science Research Computing Group Cannon cluster)

  • Michael M Desai

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Vaughn S Cooper, University of Pittsburgh, United States

Publication history

  1. Received: June 2, 2021
  2. Accepted: September 29, 2021
  3. Accepted Manuscript published: October 1, 2021 (version 1)

Copyright

© 2021, Bakerlee et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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