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Multi-taxa integrated landscape genetics for zoonotic infectious diseases: deciphering variables influencing disease emergence

机译：人畜共患传染病的多分类群综合景观遗传学：破译影响疾病出现的变量

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摘要

Zoonotic disease transmission systems involve sets of species interacting with each other and their environment. This complexity impedes development of disease monitoring and control programs that require reliable identification of spatial and biotic variables and mechanisms facilitating disease emergence. To overcome this difficulty, we propose a framework that simultaneously examines all species involved in disease emergence by integrating concepts and methods from population genetics, landscape ecology, and spatial statistics. Multi-taxa integrated landscape genetics (MTILG) can reveal how interspecific interactions and landscape variables influence disease emergence patterns. We test the potential of our MTILG-based framework by modelling the emergence of a disease system across multiple species dispersal, interspecific interaction, and landscape scenarios. Our simulations showed that both interspecific-dependent dispersal patterns and landscape characteristics significantly influenced disease spread. Using our framework, we were able to detect statistically similar inter-population genetic differences and highly correlated spatial genetic patterns that imply species-dependent dispersal. Additionally, species that were assigned coupled-dispersal patterns were affected to the same degree by similar landscape variables. This study underlines the importance of an integrated approach to investigating emergence of disease systems. MTILG is a robust approach for such studies and can identify potential avenues for targeted disease management strategies.
机译：人畜共患疾病的传播系统涉及相互影响的物种集及其环境。这种复杂性阻碍了疾病监测和控制程序的发展，这些程序需要可靠地识别空间和生物变量以及促进疾病出现的机制。为了克服这一困难，我们提出了一个框架，该框架通过整合来自种群遗传学，景观生态学和空间统计的概念和方法，来同时检查与疾病发生有关的所有物种。多分类群综合景观遗传学（MTILG）可以揭示种间相互作用和景观变量如何影响疾病的发生方式。通过对跨多种物种传播，种间相互作用和景观场景的疾病系统的出现进行建模，我们测试了基于MTILG的框架的潜力。我们的模拟结果表明，种间依赖的扩散模式和景观特征均显着影响疾病的传播。使用我们的框架，我们能够检测到统计上相似的种群间遗传差异和高度相关的空间遗传模式，这暗示了物种依赖性的扩散。另外，分配了耦合-分散模式的物种在相似程度上受到相似的景观变量的影响。这项研究强调了研究疾病系统出现的综合方法的重要性。 MTILG是进行此类研究的可靠方法，可以确定针对性疾病管理策略的潜在途径。

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