Université de Picardie Jules Verne, UMR « Ecologie et Dynamique des Systèmes Anthropisés » (EDYSAN, UMR 7058 CNRS), 33 Rue Saint Leu, 80000 Amiens CEDEX 1, France.
Université de Picardie Jules Verne, UMR « Ecologie et Dynamique des Systèmes Anthropisés » (EDYSAN, UMR 7058 CNRS), 33 Rue Saint Leu, 80000 Amiens CEDEX 1, France.
Ticks Tick Borne Dis. 2020 Nov;11(6):101509. doi: 10.1016/j.ttbdis.2020.101509. Epub 2020 Jul 7.
Ixodes ricinus is the most common and widely distributed tick species in Europe, responsible for several zoonotic diseases, including Lyme borreliosis. Population genetics of disease vectors is a useful tool for understanding the spread of pathogens and infection risks. Despite the threat to the public health due to the climate-driven distribution changes of I. ricinus, the genetic structure of tick populations, though essential for understanding epidemiology, remains unclear. Previous studies have demonstrated weak to no apparent spatial pattern of genetic differentiation between European populations. Here, we analysed the population genetic structure of 497 individuals from 28 tick populations sampled from 20 countries across Europe, the Middle-East, and northern Africa. We analysed 125 SNPs loci after quality control. We ran Bayesian and multivariate hierarchical clustering analyses to identify and describe clusters of genetically related individuals. Both clustering methods support the identification of three spatially-structured clusters. Individuals from the south and north-western parts of Eurasia form a separated cluster from northern European populations, while central European populations are a mix between the two groups. Our findings have important implications for understanding the dispersal processes that shape the spread of zoonotic diseases under anthropogenic global changes.
硬蜱属中的蓖子硬蜱是在欧洲分布最广、最常见的蜱种,可传播多种人畜共患病,包括莱姆病。疾病媒介的种群遗传学是了解病原体传播和感染风险的有用工具。尽管由于气候驱动的蓖子硬蜱分布变化对公共卫生造成了威胁,但对于理解流行病学至关重要的蜱种群的遗传结构仍不清楚。先前的研究表明,欧洲种群之间的遗传分化存在弱至无明显的空间模式。在这里,我们分析了来自欧洲、中东和北非 20 个国家的 28 个蜱种群中 497 个个体的种群遗传结构。在质量控制后,我们分析了 125 个 SNP 基因座。我们运行了贝叶斯和多变量层次聚类分析,以识别和描述遗传上相关个体的聚类。这两种聚类方法都支持识别出三个具有空间结构的聚类。来自欧亚大陆南部和西北部的个体与北欧种群形成一个单独的聚类,而中欧种群则是这两个群体的混合体。我们的研究结果对于理解在人为的全球变化下塑造人畜共患病传播的扩散过程具有重要意义。