Spatial epidemiology in sub-Saharan African wildlife: schistosomes of Cape Buffalo

包括病媒和寄生虫在内的动物分布受到环境特征的影响，这些特征可能促进或限制它们在景观中的移动。局部适应、扩散行为和成功繁殖留下了基因组足迹，使生物体能够在空间和时间上被追踪。这些数据使我们能够确定疾病出现和传播的驱动因素，从而转化为更有效的预防和/或控制措施，以减轻疫情。血吸虫病是一种被忽视的热带病，由一种寄生吸虫引起，具有重要的医学和兽医意义。寄生虫有一个复杂的传播周期，涉及特定的水生淡水蜗牛和哺乳动物宿主。该项目将重点研究对稀树草原生态系统健康至关重要的关键物种——开普敦水牛（Syncerus caffer caffer），包括实地考察、物种鉴定（蜗牛和寄生虫）和景观基因组学，以确定南非克鲁格国家公园（KNP）血吸虫病动态的驱动因素。您将：在克鲁格国家公园（WP1）内收集、鉴定和确定布法罗血吸虫寄生虫的分布；圆螺中间寄主（WP2）多样性鉴定与评价；Cape buffalo （WP3）的遗传健康和种群结构评估；关联景观变量与遗传多样性（WP4）。为了实现这些目标，WP1-2将涉及形态鉴定和分子元条形码。对于WP3，您将使用双酶切限制性位点相关DNA测序来获得全基因组SNP位点，以解决水牛精细规模的种群结构。WP4将采用景观基因组学方法，结合每个环境变量的GIS抗性图。利用R统计软件包，抗性距离将与水牛遗传距离相关，以确定与基因流呈正相关或负相关的变量。最后，将在CIRCUITSCAPE中生成当前地图，以确定高连通性和低连通性范围内的区域，从而为疾病传播和疫情预测提供信息。该项目将为未来人畜共患病媒介的景观基因组学提供一个模型，对分子流行病学领域做出重大贡献。

Animal distributions, including disease vectors and parasites, are influenced by environmental features, which can either facilitate or restrict their movement across the landscape. Local adaptation, dispersal behaviour and successful reproduction leaves a genomic footprint, allowing organisms to be tracked through space and time.Such data allow us to determine the drivers of disease emergence and spread, which can translate into more effective preventative and/or control measures to mitigate outbreaks. Schistosomiasis is a neglected tropical disease of great medical and veterinary importance caused by a parasitic trematode. The parasites have a complex transmission cycle involving specific aquatic freshwater snails and a mammalian host.Focusing on the Cape buffalo (Syncerus caffer caffer), a keystone species critical to the health of savannah grassland ecosystems, this studentship will involve fieldwork, species identification (snail and parasites) and landscape genomics to identify the drivers of schistosomiasis dynamics in the iconic Kruger National Park (KNP), South Africa.You will:collect, identify and determine the distribution of Buffalo schistosome parasites within the Kruger National Park (WP1);identify and assess diversity of Bulinus snail intermediate hosts (WP2);assess the "genetic health and population structure of Cape buffalos (WP3);correlate landscape variables with genetic diversity (WP4).To achieve these aims, WP1-2 will involve morphological identification and molecular metabarcoding. For WP3, you will apply double-digest restriction-site associated DNA sequencing to obtain genome-wide SNP loci to resolve fine scale population structure in buffalo.WP4 will deploy a landscape genomics approach incorporating GIS resistance maps for each environmental variable. Using R statistical packages, resistance distance will be correlated with buffalo genetic distance in order to identify variables that are either positivity or negatively correlated with gene flow. Lastly, current maps will be generated in CIRCUITSCAPE to identify areas within the landscape of high and low connectivity that can inform disease spread and predictions of outbreaks.This project will provide a model for future landscape genomics of zoonotic disease vectors making a significant contribution to the field of molecular epidemiology.