Reciprocal sign epistasis between frequently experimentally evolved adaptive mutations causes a rugged fitness landscape

Abstract

The fitness landscape captures the relationship between genotype and evolutionary fitness and is a pervasive metaphor used to describe the possible evolutionary trajectories of adaptation. However, little is known about the actual shape of fitness landscapes, including whether valleys of low fitness create local fitness optima, acting as barriers to adaptive change. Here we provide evidence of a rugged molecular fitness landscape arising during an evolution experiment in an asexual population of Saccharomyces cerevisiae. We identify the mutations that arose during the evolution using whole-genome sequencing and use competitive fitness assays to describe the mutations individually responsible for adaptation. In addition, we find that a fitness valley between two adaptive mutations in the genes MTH1 and HXT6/HXT7 is caused by reciprocal sign epistasis, where the fitness cost of the double mutant prohibits the two mutations from being selected in the same genetic background. The constraint enforced by reciprocal sign epistasis causes the mutations to remain mutually exclusive during the experiment, even though adaptive mutations in these two genes occur several times in independent lineages during the experiment. Our results show that epistasis plays a key role during adaptation and that inter-genic interactions can act as barriers between adaptive solutions. These results also provide a new interpretation on the classic Dobzhansky-Muller model of reproductive isolation and display some surprising parallels with mutations in genes often associated with tumors.

Figure 1. Mutations in adaptive clones M1–M5.

Clones are colored according to their colored subpopulation of origin. New mutations found by whole genome sequencing are highlighted with gene names in red.

Figure 2. Relative fitness of individual mutations derived from competition experiments.

Mutations are ordered as in Figure 1, with M1–M5 going left to right, and bars are colored according to the color subpopulation of origin of each clone. Error bars are +/− standard error of the mean. Significance was determined by a separate two-sample, two-tailed t-test for each mutation versus the wild-type control. (*) indicates p<0.05, (**) indicates p<0.01.

Figure 3. Adaptive mutations recapitulate fitness of adaptive clones M1–M3 and M5.

For each adaptive clone, the fitness effects of each adaptive mutation from Figure 2 were added and compared to the relative fitness of the clone. The additive effects recapitulate the relative fitness of clones M1–M3 and M5, and there is evidence of negative epistasis between the two adaptive mutations in M4, since the additive fitness effect of the mutations is significantly larger than the relative fitness of the clone. Error bars are standard deviation. (*) indicates significance at α = 0.05. Relative fitness data of clones are from .

Figure 4. Allele frequencies of mth1-3 and HXT6/7 amplification in the yellow subpopulation.

Over the course of the experiment, mth1-3 transiently increases in frequency but gets outcompeted by clones carrying the HXT6/7 amplification by the end of the experiment. Error bars are +/− standard error of the mean of three biological replicate experiments. HXT6/7 data are from , plotted as a proportion of the yellow subpopulation.

Figure 5. Competition experiments to test for epistasis between singly adaptive mutations.

(A) Reciprocal sign epistasis between the mth1-2 and HXT6/7 amplification mutations from the red subpopulation, which results in a two-peaked fitness landscape (Figure S5); the mth1-3 and HXT6/7 amplification mutations from the yellow subpopulation give similar results (Figure S4). (B) Tests for epistasis between other singly adaptive mutations show pervasive negative epistasis between the pairs IRA1/(HXT6/7)_yellow, IRA1/RIM15, MTH1/GPB2, as well as sign epistasis between RIM15 and GPB2. Sign epistasis would constrain the fitness landscape but would not lead to two fitness peaks. Error bars are 95% confidence intervals.