Abstract
Abstract
Random variation in reproductive success—genetic drift—profoundly shapes genetic diversity and evolutionary trajectories. The strength of drift depends on the variance in descendant number, σd2, which governs key evolutionary outcomes: for instance, the establishment probability of a beneficial mutation scales inversely with σd2. However, whether σd2 itself evolves over long timescales has remained unclear, because allele-frequency fluctuations depend on drift only through the effective population size, Ne=N/σd2, which blends census population size with descendant-number variance. Here, we disentangle these components by using model-based Bayesian inference combined with joint tracking of (i) frequency fluctuations of neutrally barcoded lineages and (ii) census population sizes across growth cycles in the Escherichia coli long-term evolution experiment (LTEE). Analyzing 33 clones spanning the ancestor through 50,000 generations in two replicate populations (Ara-2 and Ara+2), we find that the strength of genetic drift evolved markedly—and divergently—between the two replicate populations. Both census size and σd2 changed substantially through time, with most variation in Ne driven by shifts in σd2 rather than census size. After approximately 2,000 generations, the σd2 of the two populations diverged sharply: Ara+2 generally remained close to a bottleneck-only null expectation, whereas Ara-2 exhibited 1.5–5× stronger drift, consistent with an evolved increase in stochasticity during growth. These results imply that mutations can alter both the mean and the variance of the descendant-number distribution, and we show that the joint distribution of mutational effects on fitness and on σd2 can substantially modulate the rate of adaptation. The key parameter governing genetic drift can therefore itself evolve in the LTEE, with direct consequences for adaptation.