Modelling the Evolutionary Dynamics of Viruses within Their Hosts: A Case Study Using High-Throughput Sequencing

Uncovering how natural selection and genetic drift shape the evolutionary dynamics of virus populations within their hosts can pave the way to a better understanding of virus emergence. Mathematical models already play a leading role in these studies and are intended to predict future emergences. Here, using high-throughput sequencing, we analyzed the within-host population dynamics of four Potato virus Y (PVY) variants differing at most by two substitutions involved in pathogenicity properties. Model selection procedures were used to compare experimental results to six hypotheses regarding competitiveness and intensity of genetic drift experienced by viruses during host plant colonization. Results indicated that the frequencies of variants were well described using Lotka-Volterra models where the competition coefficients βij exerted by variant j on variant i are equal to their fitness ratio, rj/ri. Statistical inference allowed the estimation of the effect of each mutation on fitness, revealing slight (s = −0.45%) and high (s = −13.2%) fitness costs and a negative epistasis between them. Results also indicated that only 1 to 4 infectious units initiated the population of one apical leaf. The between-host variances of the variant frequencies were described using Dirichlet-multinomial distributions whose scale parameters, closely related to the fixation index FST, were shown to vary with time. The genetic differentiation of virus populations among plants increased from 0 to 10 days post-inoculation and then decreased until 35 days. Overall, this study showed that mathematical models can accurately describe both selection and genetic drift processes shaping the evolutionary dynamics of viruses within their hosts.

阐明自然选择与遗传漂变如何塑造宿主内病毒种群的进化动态，可为更深入理解病毒出现事件奠定基础。数学模型在这类研究中已发挥核心作用，且旨在预测未来的病毒出现事件。本研究借助高通量测序（high-throughput sequencing）技术，分析了4株差异最多仅涉及2个与致病性特征相关的氨基酸替换的马铃薯Y病毒（Potato virus Y, PVY）毒株的宿主内种群动态。研究采用模型选择程序，将实验结果与6种关于病毒在宿主植物定殖过程中竞争力与遗传漂变强度的假说进行对比。结果显示，洛特卡-沃尔泰拉（Lotka-Volterra）模型可很好地拟合毒株频率变化：当毒株j对毒株i的竞争系数β_ij等于二者的适合度比值r_j/r_i时，模型拟合效果最优。通过统计推断，我们估算了每个突变对适合度的影响，结果揭示了两种程度不一的适合度代价：轻度（s = −0.45%）与重度（s = −13.2%），且二者之间存在负上位性。研究同时发现，单株顶叶的病毒种群仅由1~4个感染起始单位奠基建立。毒株频率的宿主间方差可通过狄利克雷-多项分布（Dirichlet-multinomial distribution）进行拟合，该分布的尺度参数与固定指数F_ST（fixation index）紧密相关，且随时间动态变化。不同宿主植物间病毒种群的遗传分化在接种后0至10天逐渐升高，随后至接种后35天逐步降低。综上，本研究证实，数学模型可精准描述塑造宿主内病毒进化动态的自然选择与遗传漂变过程。