Measuring selection coefficients below 10(-3): method, questions, and prospects

Abstract

Measuring fitness with precision is a key issue in evolutionary biology, particularly in studying mutations of small effects. It is usually thought that sampling error and drift prevent precise measurement of very small fitness effects. We circumvented these limits by using a new combined approach to measuring and analyzing fitness. We estimated the mutational fitness effect (MFE) of three independent mini-Tn10 transposon insertion mutations by conducting competition experiments in large populations of Escherichia coli under controlled laboratory conditions. Using flow cytometry to assess genotype frequencies from very large samples alleviated the problem of sampling error, while the effect of drift was controlled by using large populations and massive replication of fitness measures. Furthermore, with a set of four competition experiments between ancestral and mutant genotypes, we were able to decompose fitness measures into four estimated parameters that account for fitness effects of our fluorescent marker (α), the mutation (β), epistasis between the mutation and the marker (γ), and departure from transitivity (τ). Our method allowed us to estimate mean selection coefficients to a precision of 2 × 10(-4). We also found small, but significant, epistatic interactions between the allelic effects of mutations and markers and confirmed that fitness effects were transitive in most cases. Unexpectedly, we also detected variation in measures of s that were significantly bigger than expected due to drift alone, indicating the existence of cryptic variation, even in fully controlled experiments. Overall our results indicate that selection coefficients are best understood as being distributed, representing a limit on the precision with which selection can be measured, even under controlled laboratory conditions.

Figure 1

Measuring genotype frequencies with flow cytometry. The fluorescence of each bacterium was measured in the FL1 (YFP) and FL10 (CFP) channels. Here we show a representative contour plot. Quadrants represent thresholds delimiting the YFP (C1), CFP (C4), doubled marked (C2), and unmarked (C3) populations. In this example, populations are composed of YFP, 110718 (51.03%); CFP, 103996 (47.93%); doubled-marked, 2110 (0.97%); Unmarked 151 (0.07%) individuals.

Figure 2

Selection coefficients (s) of the wild-type (REL4548) and mutant strains (REL4548 T63, T103, or T121) measured in the (a) wc/wy, (b) mc/my, (c) my/wc, and (d) mc/wy competitions. Each point represents an s measure estimated from a single competition experiment. s measures are grouped in lines to show the variance between experiments performed at different dates.

Figure 3

Variance in selection coefficients (σ_s estimate bold point ± support limits indicated by bars) of the wild-type (REL4548) and mutant strains (REL4548 T63, T103, or T121) measured in the (a) wc/wy, (b) mc/my, (c) my/wc, and (d) mc/wy competitions. The predicted variation expected by genetic drift alone is represented by the shaded line at the bottom of the figure.