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High-resolution lineage tracking reveals traveling wave of adaptation in laboratory yeast
In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population(1–5). These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. While earli...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6938260/ https://www.ncbi.nlm.nih.gov/pubmed/31723263 http://dx.doi.org/10.1038/s41586-019-1749-3 |
Sumario: | In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population(1–5). 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(6–10), these methods have limited 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(11–17). We show that clonal competition creates 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. |
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