PRJNA559526
Lineage tracking in experimentally evolved yeast populations
In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete simultaneously for dominance within the population. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. While earlier studies used whole-genome sequencing to follow molecular adaptation, these methods have very limited frequency resolution in microbial populations. Here, we introduce a novel renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, finding a “traveling wave” of adaptation that has been predicted by theory. We show that the dynamics of clonal competition create a dynamical rich-get-richer effect: fitness advantages acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Our results demonstrate that this combination of factors, which is not accounted for in any existing model of evolutionary dynamics, is critical in determining the rate, predictability, and molecular basis of adaptation.