Quantifying fitness distributions and phenotypic relationships in recombinant yeast populations

Abstract

Studies of the role of sex in evolution typically involve a longitudinal comparison of a single ancestor to several intermediate descendants and to one terminally evolved descendant after many generations of adaptation under a given selective regime. Here we take a complementary, statistical approach to sex in evolution, by describing the distribution of phenotypic similarity in a population of yeast F1 meiotic recombinants. By applying graph theory to fitness measurements of thousands of Saccharomyces cerevisiae recombinants treated with 10 mechanistically distinct, growth-inhibitory small-molecule perturbagens (SMPs), we show that the network of phenotypic similarity among F1 recombinants exhibits a scale-free degree distribution. F1 recombinants are often phenotypically unique and sometimes exceptional, and their fitness strengths are unevenly distributed across the 10 compound treatments. By contrast, highly phenotypically similar F1 recombinants constitute failing hubs that display below-average fitness across all compound treatments and are candidate substrates for purifying selection. Comparison of the F1 generation with the parental strains reveals that (i) there is a specialist more fit in any given single condition than any of the parents but (ii) only rarely are there generalists that exhibit greater fitness than both parental strains across a majority of conditions. This analysis allows us to evaluate and to gain better theoretical understanding of the costs and benefits of sex in the F1 generation.

Fig. 1.

Schematic depicting the generation of a network of phenotypic similarity. All XHS123 F₁ recombinants are replica-pinned from stock plates (not shown) into a control plate that contains DMSO (white) and into daughter plates, each of which contains a given SMP (red, green, and blue). The growth (i.e., fitness) of each recombinant is measured as described in the text. These growth values are normalized by the average growth of the entire plate, producing a vector of normalized growth values. The distance between the growth vectors of two recombinants is used to define the edges in the graph; similar recombinants are connected by edges, whereas dissimilar recombinants are not. Completely unconnected recombinants are “orphans,” whereas highly connected recombinants are “hubs” (not shown).

Fig. 2.

Scale-free degree distribution of a representative network of phenotypic similarity composed of 3,107 F₁ recombinants. (A) Empirical degree distribution fit by power law with exponent 1.64. (B) Direct comparison of results observed in experimental network and results generated by recombination model.

Fig. 3.

Representative bimodal fitness distribution revealing phenotypically failing hubs. (A) Fitness distribution of 3,107 F₁ recombinants grown in dimethyl sulfoxide (DMSO). The bracketed orange line depicts the range of high k nodes. Vertical colored lines denote the fitness of parental strains, as shown in the inset key. (B) Fitness distribution of 3,107 F₁ recombinants grown in the small-molecule perturbagen (SMP) calcimycin. (C) Plot of average growth across all 11 conditions (10 SMPs + DMSO) versus standard deviation in growth between all 11 conditions. Each black point corresponds to an F₁ recombinant, blue points correspond to high k nodes, and the red line depicts a linear regression. The correlation coefficient is 0.8.

Fig. 4.

Calculation of the true-benefit ratio enables a cost-benefit analysis of sex in the F₁ generation. (A) Average TBR of a spore (calculated across all 10 conditions) vs. connectivity of that spore in the network with degree distribution shown in Fig. 2. (B) Plot similar to that in A but displaying the number of conditions in which a given spore exhibits a TBR >1 vs. the connectivity of the spore. (C) Number of model conditions to which a recombinant is resistant vs. the connectivity of that recombinant in our simple model of recombination.