...
首页> 外文期刊>BMC Evolutionary Biology >Patterns of genetic variation in populations of infectious agents
【24h】

Patterns of genetic variation in populations of infectious agents

机译:传染源人群遗传变异的模式

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Background The analysis of genetic variation in populations of infectious agents may help us understand their epidemiology and evolution. Here we study a model for assessing the levels and patterns of genetic diversity in populations of infectious agents. The population is structured into many small subpopulations, which correspond to their hosts, that are connected according to a specific type of contact network. We considered different types of networks, including fully connected networks and scale free networks, which have been considered as a model that captures some properties of real contact networks. Infectious agents transmit between hosts, through migration, where they grow and mutate until elimination by the host immune system. Results We show how our model is closely related to the classical SIS model in epidemiology and find that: depending on the relation between the rate at which infectious agents are eliminated by the immune system and the within host effective population size, genetic diversity increases with R0 or peaks at intermediate R0 levels; patterns of genetic diversity in this model are in general similar to those expected under the standard neutral model, but in a scale free network and for low values of R0 a distortion in the neutral mutation frequency spectrum can be observed; highly connected hosts (hubs in the network) show patterns of diversity different from poorly connected individuals, namely higher levels of genetic variation, lower levels of genetic differentiation and larger values of Tajima's D. Conclusion We have found that levels of genetic variability in the population of infectious agents can be predicted by simple analytical approximations, and exhibit two distinct scenarios which are met according to the relation between the rate of drift and the rate at which infectious agents are eliminated. In one scenario the diversity is an increasing function of the level of transmission and in a second scenario it is peaked around intermediate levels of transmission. This is independent of the type of host contact structure. Furthermore for low values of R0, very heterogeneous host contact structures lead to lower levels of diversity.
机译:背景分析传染原种群的遗传变异可能有助于我们了解其流行病学和进化。在这里,我们研究了一种模型,用于评估传染原群体中遗传多样性的水平和模式。人口分为许多小亚群,它们与它们的主机相对应,并根据特定类型的联系网络进行连接。我们考虑了不同类型的网络,包括完全连接的网络和无标度网络,这些网络已被视为捕获实际联系网络某些属性的模型。传染原通过迁移在宿主之间传播,在宿主中生长和突变直至被宿主免疫系统消除。结果我们展示了我们的模型与流行病学中的经典SIS模型如何紧密相关,并发现:根据免疫系统消除传染原的速率与宿主有效种群内部大小之间的关系,遗传多样性随着R的增加而增加 0 或处于中间R 0 级别的峰值;此模型中的遗传多样性模式通常与标准中性模型下预期的模式相似,但是在无标度网络中,并且对于R 0 的低值,中性突变频谱可能会失真。观测到的;高度连接的主机(网络中的集线器)显示出与连接不良的个体不同的多样性模式,即较高水平的遗传变异,较低水平的遗传分化和较大的田岛D值。结论我们发现种群中的遗传变异水平可以通过简单的分析近似来预测感染因子的数量,并根据漂移速率和消除感染因子的速率之间的关系展示两种截然不同的情况。在一种情况下,分集是传输级别的增加函数,而在第二种情况下,它在中间传输级别附近达到峰值。这与主机触点结构的类型无关。此外,对于R 0 的低值,非常异质的宿主接触结构会导致较低的多样性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号