Chance and necessity in the pleiotropic consequences of adaptation for budding yeast

Abstract

Mutations that a population accumulates during evolution in one 'home' environment may cause fitness gains or losses in other environments. Such pleiotropic fitness effects determine the evolutionary fate of the population in variable environments and can lead to ecological specialization. It is unclear how the pleiotropic outcomes of evolution are shaped by the intrinsic randomness of the evolutionary process and by the deterministic variation in selection pressures across environments. Here, to address this question, we evolved 20 replicate populations of the yeast Saccharomyces cerevisiae in 11 laboratory environments and measured their fitness across multiple conditions. We found that evolution led to diverse pleiotropic fitness gains and losses, driven by multiple types of mutations. Approximately 60% of this variation is explained by the home environment of a clone and the most common parallel genetic changes, whereas about 40% is attributed to the stochastic accumulation of mutations whose pleiotropic effects are unpredictable. Although populations are typically specialized to their home environment, generalists also evolved in almost all of the conditions. Our results suggest that the mutations that accumulate during evolution incur a variety of pleiotropic costs and benefits with different probabilities. Thus, whether a population evolves towards a specialist or a generalist phenotype is heavily influenced by chance.

Extended Data Fig. 1. Median fitness gains and losses, restricted to V⁺ clones.

Median fitness gains and losses among groups of clones from the same home environment, excluding V⁻ clones. Notations as in Figure 1.

Extended Data Fig. 2. Frequency-dependence of competition between V⁺ and V⁻.

Fitness of a V⁻ clone relative to the ancestor at Low Temp, initiated at different initial frequencies. The frequency dependence of the relative fitness suggests that the fitness defect might be caused by a direct interaction between the competitors. Error bars show ± 1 SE.

Extended Data Fig. 3. Variance in fitness across environmental panels.

As in Figure 5a-c, but variance in fitness across groups of clones rather than means. Error bars represent ± 1 standard error of the variance.

Extended Data Fig. 4. Correlations between clone fitness in different salt conditions.

Each panel below the diagonal shows clone fitness in a particular pair of environments. (Error bars: ± 1 SE on clone fitness.) The diagonal shows the correlation between technical replicates in the fitness assay in each condition. Panels above the diagonal are colored by and display the Pearson correlation coefficient between clone fitness in the corresponding pair of environments.

Extended Data Fig. 5. Correlations between clone fitness in different pH conditions.

Each panel below the diagonal shows clone fitness in a particular pair of environments. (Error bars: ± 1 SE on clone fitness.) The diagonal shows the correlation between technical replicates in the fitness assay in each condition. Panels above the diagonal are colored by and display the Pearson correlation coefficient between clone fitness in the corresponding pair of environments.

Extended Data Fig. 6. Correlations between clone fitness in different temperature conditions.

Each panel below the diagonal shows clone fitness in a particular pair of environments. (Error bars: ± 1 SE on clone fitness.) The diagonal shows the correlation between technical replicates in the fitness assay in each condition. Panels above the diagonal are colored by and display the Pearson correlation coefficient between clone fitness in the corresponding pair of environments.

Fig 1.. Fitness gains and losses in diagnostic conditions after evolution in each condition.

Each square shows the median fitness gain or loss in a measurement environment (columns) across all populations evolved in a given home environment (rows) for ~ 700 generations. The left bar graph shows the average degree of specialization after evolution in each home environment. The degree of specialization is defined as the average proportion of measurement environments where clones lost fitness relative to the ancestor. The bar graph on the bottom shows the competitiveness of a “resident” clone in its home environment against invasions from other environments. The competitiveness is defined as the average proportion of evolved clones from other environments that are less fit than a randomly chosen resident clone. Error bars represent 95% confidence intervals on a bootstrap over clones in each evolution condition.

Fig 2.. Environmental and stochastic determinants of pleiotropic profiles.

a, t-SNE dimensional reduction of the pleiotropic profiles. Each point represents a clone; the eight-dimensional vector of clone fitness across the eight conditions was projected into two dimensions using t-SNE. Clones are colored according to home environment. b, t-SNE projection as in panel a. Colors are assigned based on the t-SNE coordinates to establish visual correspondence between this projection and the full pleiotropic profiles shown in panel d. c, Proportion of the variance in clone fitness in each environment that is attributable to (in this order) home environment, V⁺/V⁻ phenotype, other pleiotropy (unexplained variance), measurement noise. Clones are excluded from their own home environment. d, The pleiotropic profiles of clones from each home environment. Profiles are colored as in panel b. Error bars represent ±1 SE on clone fitness.

Fig 3.. V⁻ phenotype is caused by the loss of yeast killer virus.

a, Gel electrophoresis of total DNA and dsRNA extracted from 15 clones. Anc is the common ancestor of the experiment; evolved clones 1 through 7 are from the V⁺ cluster (Fig. 2b), i.e., without a fitness defect at 21°C; evolved clones 8 through 14 are from the V⁻ cluster, i.e., with a fitness defect at 21°C. The upper (~ 4 kb) band is consistent with the helper virus, and the lower (~ 2 kb) band is consistent with the killer virus. b, Fitness of all evolved clones relative to the ancestor and to the ancestor cured of the killer virus. Classification of clones into V⁺(blue) and V⁻(red) is based on the t-SNE plot in Fig. 2b.

Fig 4.. Mutations across evolution conditions and genetic determinants of pleiotropy.

a, Genes with four or more nonsynonymous mutations across the experiment, or two or more within one home environment, organized into the Ras pathway and thereafter by GO slim process. Number in the parentheses next to each gene name indicates the total number of detected nonsynonymous mutations in that gene. Genes in bold are significantly associated with one home environment. b, Proportion of the variance in clone fitness in each environment attributable (in this order) to mutations in multi-hit genes; ploidy; V⁺ /V⁻ phenotype; home environment, beyond these previously listed factors; other pleiotropy (unexplained variance); measurement noise. Clones are excluded from their own home environment. Only clones evolved in diagnostic conditions are considered in this analysis, as in Fig. 2.

Fig 5.. Specialization across salt (a, d, g), pH (b, e, h) and temperature (c, f, i) panels of environments.

a-c, Average fitness of clones from each home environment (colors) across multiple test conditions (x-axis). Squares represent individual clone fitness. Note that in panel b, two measurements that fell below −10% are not displayed (one clone evolved at pH 6 and measured at pH 3.8, and one clone evolved at pH 7.3 and measured at pH 4.5). d-f, Fraction of clones from each home environment (colors) that gained fitness in each test condition (x-axis). Error bars represent ±1 SE. g-i, Fraction of clones from each home environment (x-axis) that gained fitness across all test conditions in the panel. Error bars represent ±1 SE.