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

  • Curated by eLife

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    Evaluation Summary:

    The pleiotropic effects of beneficial mutations have been characterized in various settings, but it is less clear whether and how these pleiotropic patterns change over the course of evolution. Using a technically innovative and intensive experimental design with evolving yeast populations, the authors show that patterns of pleiotropy depend on the evolution environment and can change and vary substantially over relatively short timescales. They also find a surprising amount of variation among replicate populations that increases over time, so generalism or specialism is not deterministic. These technical and conceptual strengths were diminished by insufficient focus on the details of certain treatments that are demonstrative of these broader findings, making the take-home message somewhat unclear.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #3 agreed to share their names with the authors.)

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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.

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  1. Version published to 10.7554/elife.70918 on eLife
  2. eLife

    Author Response:

    Reviewer #1:

    Strengths

    This study is a technical and analytical tour de force. The evolution experiments with barcoded lineages involved an immense amount of work and clever design, and the scale of the data challenged the authors to develop new statistical summaries. The figures are clear and results easy to interpret, even outside the evolution-experiment bubble. While the essential findings are not especially surprising, the robustness enabled by this level of replication is appreciated.

    Weaknesses

    I'm not exactly sure what I learned. I'm biased to like this work and while I'm confident that if I studied these findings more I would learn more, it wasn't obvious. For example - I want to know more about the effects of ploidy on pleiotropy, and while there are some differences e.g in Figure 4A, I don't know what these PCs actually are saying. If particular phenotypes associate with PC's, it'd be helpful to "load" them on these axes.

    To more clearly show general trends and variation in pleiotropy, we have added a summary of the changes in fitness across all populations in Figure 2B and Figure 2– figure supplements 2–5. We have also expanded our consideration of these trends, including the effects of ploidy on pleiotropy. To supplement Figure 4, we have included the contribution of each assay environment to the principal components (Figure 4–figure supplement 5), as suggested.

    Also, do some treatments lead to faster or more complete diminishing returns than others, and does this influence pleiotropy?

    To compare changes in fitness across evolution environments and over time, we have computed the change in fitness for each population over the first 400 generations and the last 400 generations. This is plotted in Figure 2-figure supplement 6A. To assess the statistical significance of apparent diminishing returns, we compared the mean change in fitness over these time intervals using a t-test and provided the resulting p-values in Figure 2-figure supplement 6B. Overall, we see that different treatments lead to different extents of declining adaptability and note this in the Results. This declining adaptability may certainly influence pleiotropic outcomes, but unfortunately it is difficult to disentangle any potential such effects from other differences between environments (or assign any causality to correlations in the strengths of diminishing returns and differences in pleiotropy between replicates in the same environment), so we refrain from drawing any conclusions about this possibility.

    In total I think this manuscript can be improved by being presented / read by others, which is the job of peer review but here I think it's also to broaden its implications.

  3. eLife

    Evaluation Summary:

    The pleiotropic effects of beneficial mutations have been characterized in various settings, but it is less clear whether and how these pleiotropic patterns change over the course of evolution. Using a technically innovative and intensive experimental design with evolving yeast populations, the authors show that patterns of pleiotropy depend on the evolution environment and can change and vary substantially over relatively short timescales. They also find a surprising amount of variation among replicate populations that increases over time, so generalism or specialism is not deterministic. These technical and conceptual strengths were diminished by insufficient focus on the details of certain treatments that are demonstrative of these broader findings, making the take-home message somewhat unclear.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #3 agreed to share their names with the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    Strengths

    This study is a technical and analytical tour de force. The evolution experiments with barcoded lineages involved an immense amount of work and clever design, and the scale of the data challenged the authors to develop new statistical summaries. The figures are clear and results easy to interpret, even outside the evolution-experiment bubble. While the essential findings are not especially surprising, the robustness enabled by this level of replication is appreciated.

    Weaknesses

    I'm not exactly sure what I learned. I'm biased to like this work and while I'm confident that if I studied these findings more I would learn more, it wasn't obvious. For example - I want to know more about the effects of ploidy on pleiotropy, and while there are some differences e.g in Figure 4A, I don't know what these PCs actually are saying. If particular phenotypes associate with PC's, it'd be helpful to "load" them on these axes. Also, do some treatments lead to faster or more complete diminishing returns than others, and does this influence pleiotropy? In total I think this manuscript can be improved by being presented / read by others, which is the job of peer review but here I think it's also to broaden its implications.

  5. eLife

    Reviewer #2 (Public Review):

    The pleiotropic adaptive effects of mutations have been extensively characterized, with numerous examples of both specialist and generalist adaptations. However, it is less clear whether and how these pleiotropic patterns change over the course of evolution for a given evolving species. The authors attempt to answer this question by characterizing the pleiotropic fitness effects of ~150 adapted S. cerevisiae populations at 200-generation intervals over 1000 generations of evolution. The authors provide strong quantitative evidence that patterns of pleiotropy are highly dependent on the evolution environment, and changes substantially over relatively short evolutionary timescales (1000 generations). They further show that even with a fixed genotype and selective environment, replicate populations can substantially vary in their pleiotropic profiles (again, in an environment-dependent manner), and this variation tends to increase over evolutionary time. The authors thus provide substantial evidence that the evolution of "generalist" or "specialist" types is not deterministic but rather strongly dependent on both the specific evolving system and evolutionary stochasticity.

    The authors use DNA barcodes to uniquely tag each of their evolving populations, then use bulk fitness assays to measure the fitness of each population at 5 different timepoints across five different environments. These methods are well established, and appear to have been implemented correctly. The resulting data clearly answers the proposed question, and supports the major claims of the paper.

    Most previous studies of the pleiotropic effects of adaptation characterize a relatively small number of independently evolved lines, limiting our ability to draw quantitative conclusions (but see Kinser et al 2020 eLife). Furthermore, I am unaware of any large-scale study characterizing how the pleiotropic effects of mutations change over evolutionary time. While the specific experiments and data are not of use to the broader community, the major findings substantially advance our understanding of the evolutionary process and open up new avenues of both theoretical and empirical research.

  6. eLife

    Reviewer #3 (Public Review):

    Bakerlee, Phillips et al. investigated the dynamics of pleiotropic effects of laboratory adaptation in yeast. They do this by experimentally evolving 172 yeast populations in three different laboratory conditions. After which, they examine the dynamics of (environmental) pleiotropy by tracking the relative fitness change of each population in a focal and alternative environment (a total of five measurement environments).

    Even though various experimental evolution studies examined the same question (some of which testing it on the same environmental conditions and the same model organism), this manuscript stands out with a significant improvement in its experimental design, i.e., testing the pleiotropic effects of local adaptation on a large number of replicate populations across a series of evolutionary time points. As a result, they could observe that the pleiotropic effects show a considerable variation within treatment groups, and this variability is more pronounced in away than in home environments.

    The question of how adaptation to a stable environment affects the evolutionary fitness of populations in a different environment represents a crucial research topic. This work displays the presence of considerable variability in the evolution of pleiotropy, stressing the importance of chance and contingency. Overall, this is a nice study leveraging the recently developed microbial barcoding techniques, but there is still room for significant improvement to strengthen and clarify the results and conclusions.

  7. Version published to 10.1101/2021.06.24.449852v1 on bioRxiv