Stochastic Population Genetic Models of Chronic Pathogens

相关的种群遗传过程(选择和人口随机性)发生在受感染宿主内部和之间，并在可比的时间尺度上运行，这使得理解导致慢性感染的寄生虫的进化变得复杂。虽然有时可以对急性感染进行建模，就好像它们在进化时间尺度上是瞬时的，但这种简化在建模依赖时间的特征的进化时是不合适的，例如那些由偶发基因控制的特征，或者在多阶段寄生虫生命周期过程中表达有限的特征。在这里，我们提出了一些利用测量值随机过程的模型，我们认为这些过程捕捉到了与慢性感染相关的一些生物学现象，但在数学上仍然是容易处理的。我们既考虑了流行病，也考虑了地方性传染病，我们建议使用分枝马尔可夫过程来建模，地方性传染病可以使用对Moran模型的一类测度值推广的各种严格和启发式近似来研究。然后，我们描述了这些模型如何被用来研究三个具体现象：(I)有限种群中毒力的进化；(Ii)宿主的异质性和对HIV-1的多样化选择；以及(Iii)假基因积累和非洲锥虫中VSG抗原库的进化。

Understanding the evolution of parasites which cause chronic infections is complicated by the fact that the relevant population genetic processes (selection and demographic stochasticity) occur both within and among infected hosts and operate on comparable time scales. Whereas it may sometimes be possible to model acute infections as though they were instantaneous over evolutionary time scales, such simplifications will be unsuitable when modeling the evolution of time-dependent traits such as those controlled by contingency loci or which have limited expression over the course of multi-stage parasite life cycles. Here we propose a number of models making use of measure-valued stochastic processes which we believe capture some of the biological phenomena relevant to chronic infections yet remain mathematically tractable. We consider both epidemics, which we propose to model using branching Markov processes, and endemic infections, which can be studied using various rigorous and heuristic approximations to a class of measure-valuedgeneralizations of the Moran model. We then describe how these models can be used to study three concrete phenomena: (i) the evolution of virulence in finite populations; (ii) host heterogeneity and diversifying selection on HIV-1; and (iii) pseudogene accumulation and the evolution of the VSG antigen repertoire in African trypanosomes.