Abstract：
We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.
摘要：
我们在这里提出了一个分析管道，用于从患者采样或实验进化的病毒种群中推断健身效应（DFE）的分布。这明确解释了病原体固有的非赖特-费雪和非平衡种群动态。我们通过广泛的功能和性能分析来检验这种方法的性能，并强调了两个说明性的应用——一个来自实验传代的RNA病毒，另一个来自临床采样的DNA病毒。最后,我们讨论了这种DFE推断如何揭示病毒进化中的主要研究问题，从控制基因组大小的群体遗传过程的量化，希尔-罗伯逊干涉在决定适应性结果中的作用，通过诱导的突变融化根除患者体内病毒群体的新型治疗方法的潜在设计。
