Quantitative evolutionary dynamics using high-resolution lineage tracking

Evolution of large asexual cell populations underlies ∼30% of deaths worldwide, including those caused by bacteria, fungi, parasites, and cancer. However, the dynamics underlying these evolutionary processes remain poorly understood because they involve many competing beneficial lineages, most of which never rise above extremely low frequencies in the population. To observe these normally hidden evolutionary dynamics, we constructed a sequencing-based ultra high-resolution lineage tracking system in Saccharomyces cerevisiae that allowed us to monitor the relative frequencies of ∼500,000 lineages simultaneously. In contrast to some expectations, we found that the spectrum of fitness effects of beneficial mutations is neither exponential nor monotonic. Early adaptation is a predictable consequence of this spectrum and is strikingly reproducible, but the initial small-effect mutations are soon outcompeted by rarer large-effect mutations that result in variability between replicates. These results suggest that early evolutionary dynamics may be deterministic for a period of time before stochastic effects become important. Random DNA barcodes were used to simultaneously track hundreds of thousands of lineages in large cell populations, revealing deterministic dynamics early in their evolution. Evolutionary dynamics of large cell populations The dynamics underlying the evolution of large asexual cell populations such as bacteria, fungi, parasites and cancers remain poorly understood because they involve many competing lineages. To study these dynamics, Sasha Levy et al . have constructed a sequencing-based ultra high-resolution lineage tracking system in the yeast Saccharomyces cerevisiae and use it to monitor the relative frequencies of approximately 500,000 lineages simultaneously. They find that although individual mutations occur at random, the early dynamics of the population as a whole is a predictable outcome of the population size and the distribution of mutation rates to each fitness effect, and is strikingly reproducible.