High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast
High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast
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DOI：
10.1038/s41586-019-1749-3
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发表时间：
2019-11-21
期刊：
影响因子：
64.8
通讯作者：
Desai, Michael M.
中科院分区：
文献类型：
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作者：
Ba, Alex N. Nguyen;Cvijovic, Ivana;Desai, Michael M.
在快速适应的无性种群中，包括许多微生物病原体和病毒，许多突变谱系经常在种群中竞争优势（1-5）。这些复杂的进化动力决定了适应的结果，但很难直接观察到。以前的研究使用全基因组测序来跟踪分子适应（6-10）;然而，这些方法在微生物种群中的分辨率有限。在这里，我们介绍了一个可再生的条形码系统，以观察实验室芽殖酵母在高分辨率的进化动力学。我们发现即使在低频率下也有嵌套的干扰和搭便车模式。这些事件是由新突变的不断出现所驱动的，这些新突变在达到实质性频率之前改变了现有谱系的命运。我们观察了种群内适应度的分布如何随时间变化，并发现了理论（11-17）预测的适应行波。我们发现，克隆竞争创造了一个动态的“富-更富”的效果：在进化早期获得的健身优势驱动克隆扩张，这增加了获得未来突变的机会。然而，适应性较差的血统也经常超越适应性较高的品系。我们的研究结果表明，这种因素的组合，这是不占在现有的进化动力学模型，是至关重要的，在确定适应的速度，可预测性和分子基础。
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. Previous studies have used whole-genome sequencing to follow molecular adaptation(6-10); however, these methods have limited resolution in microbial populations. Here we introduce a 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, and find a travelling 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 that are 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 existing models of evolutionary dynamics, is critical in determining the rate, predictability and molecular basis of adaptation.