Garcia-R Juan C, Hayman David T S
Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Private Bag, 11 222, Palmerston North, 4442, New Zealand.
Parasitol Res. 2017 Jul;116(7):1855-1861. doi: 10.1007/s00436-017-5459-1. Epub 2017 May 13.
Cryptosporidiosis is one of the most common human infectious diseases globally. The gp60 gene has been adopted as a key marker for molecular epidemiological investigations into this protozoan disease because of the capability to characterize genotypes and detect variants within Cryptosporidium species infecting humans. However, we know relatively little about the potential spatial and temporal variation in population demography that can be inferred from this gene beyond that it is recognized to be under selective pressure. Here, we analyzed the genetic variation in time and space within two putative populations of Cryptosporidium in New Zealand to infer the processes behind the patterns of sequence polymorphism. Analyses using Tajima's D, Fu, and Li's D* and F* tests show significant departures from neutrality in some populations and indicate the selective maintenance of alleles within some populations. Demographic analyses showed distortions in the pattern of the genetic variability caused by high recombination rates and population expansion, which was observed in case notification data. Our results showed that processes acting on populations that have similar effects can be distinguished from one another and multiple processes can be detected acting at the same time. These results are significant for prediction of the parasite dynamics and potential mechanisms of long-term changes in the risk of cryptosporidiosis in humans.
隐孢子虫病是全球最常见的人类传染病之一。由于gp60基因能够对感染人类的隐孢子虫物种的基因型进行特征描述并检测其变异体,因此该基因已被用作对这种原生动物疾病进行分子流行病学调查的关键标记。然而,除了已知其受到选择压力外,我们对从该基因推断出的种群统计学潜在时空变化了解相对较少。在此,我们分析了新西兰两个假定的隐孢子虫种群在时间和空间上的遗传变异,以推断序列多态性模式背后的过程。使用 Tajima's D、Fu 和 Li's D* 以及 F* 检验进行的分析表明,一些种群显著偏离中性,并表明某些种群中存在等位基因的选择性维持。人口统计学分析显示,在病例通报数据中观察到的高重组率和种群扩张导致了遗传变异性模式的扭曲。我们的结果表明,作用于具有相似效应的种群的过程可以相互区分,并且可以同时检测到多个过程在起作用。这些结果对于预测寄生虫动态以及人类隐孢子虫病风险长期变化的潜在机制具有重要意义。