Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments

Abstract

Understanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a strong positive genetic interaction between specific mutations in KEL1 (P344T) and HSL7 (A695fs) that arose in an experimentally evolved Saccharomyces cerevisiae population. Because this genetic interaction is not phenocopied by gene deletion, it was previously unknown. Using "evolutionary replay" experiments, we identified additional mutations that have positive genetic interactions with the kel1-P344T mutation. We replayed the evolution of this population 672 times from six timepoints. We identified 30 populations where the kel1-P344T mutation reached high frequency. We performed whole-genome sequencing on these populations to identify genes in which mutations arose specifically in the kel1-P344T background. We reconstructed mutations in the ancestral and kel1-P344T backgrounds to validate positive genetic interactions. We identify several genetic interactors with KEL1, we validate these interactions by reconstruction experiments, and we show these interactions are not recapitulated by loss-of-function mutations. Our results demonstrate the power of experimental evolution to identify genetic interactions that are positive, allele specific, and not readily detected by other methods, shedding light on an underexplored region of the yeast genetic interaction network.

Keywords: experimental evolution; genetic interactions; yeast.

Fig. 1.

Dynamics of adaptation of population BYS2-E01. (A) Frequency of mutations present in the original BYS2-E01 population as determined by whole genome sequencing (Lang et al. 2013). A lineage containing a beneficial ste12-Q151fs mutation was outcompeted when an hsl7-A695fs mutation arose on the low-frequency focal lineage. Replay experiments were initiated at the timepoints indicated above (Generations 140, 210, 270, 335, 375, and 415). The kel1-344T mutation was first detected by whole genome, whole population sequencing at Timepoint 4. (B) Average fitness effects and standard deviations of mutations that contribute to the fitness of the focal lineage (Buskirk et al. 2017). Expected double mutant fitness (open circle) was calculated by summing individual fitness effects and propagating uncertainty. Asterisk (*) indicates P < 0.001 (Welch’s modified t-test).

Fig. 2.

Fate of ste12 lineages in the replay populations and simulated populations. Frequency of sterile cells in the replay populations over the course of the replay experiments as measured by flow cytometry (left) and frequency of the ste12 lineage over time in simulated populations (right). Each line represents one population. Percentage of populations where the ste12 lineage wins (top value) or loses (bottom value) are shown for each graph. For the simulations we show the first 48 simulated trajectories as an unbiased representation. Initial frequencies of ste12 lineage in experimental populations were plotted from values reported in Lang et al. (2011).

Fig. 3.

Positive genetic interactions between evolved mutations. Average fitness effects and standard deviations of (A) evolved mutations when reconstructed in the ancestral background and (B) gene deletions in the ancestral background. Observed fitness effects were determined by competitive fitness assays against a fluorescently labeled version of the ancestor. Expected double mutant fitness (open circles) was calculated by summing individual fitness effects and propagating uncertainty. Asterisk (*) indicates P < 0.001 (Welch’s modified t-test).