The landscape genetics of infectious disease emergence and spread.
The landscape genetics of infectious disease emergence and spread.
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DOI：
10.1111/j.1365-294x.2010.04679.x
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发表时间：
2010-09
影响因子：
4.9
通讯作者：
Real LA
中科院分区：
文献类型：
--
作者：
Biek R;Real LA
寄生虫的传播本质上是一个空间过程，通常嵌入在物理复杂的景观中。因此，这并不奇怪，传染病研究人员越来越多地采取景观遗传学的角度来阐明基本生态过程驱动传染病动力学的机制，并了解空间依赖的人口过程和宿主和寄生虫内遗传变异的地理分布之间的联系。宿主和寄生虫的遗传信息越来越多的可用性时，再加上他们的生态相互作用，可以导致洞察预测模式的疾病出现，传播和控制。在这里，我们回顾了这一领域的研究进展，基于四个不同的动机应用景观遗传学方法：（1）评估寄生虫遗传变异的空间组织作为环境变异的函数，（2）使用宿主种群遗传结构作为参数化间接影响寄生虫种群的生态动态的手段，例如，跨异质景观的基因流动和运动途径以及传染因子的同时运输，（3）阐明疾病过程的时间和空间尺度，以及（4）重建和理解传染病入侵。在整个审查中，我们强调，景观遗传学的原则是相关的感染动态范围内的主机动态的全球地理格局的尺度，他们也可以应用到非常规的“景观”，如异质性接触网络的基础上传播的人类和牲畜疾病。最后，我们讨论了一些一般性的考虑和问题，从遗传数据推断流行病学的过程，并试图确定可能的未来方向和应用这个迅速扩大的领域。
The spread of parasites is inherently a spatial process often embedded in physically complex landscapes. It is therefore not surprising that infectious disease researchers are increasingly taking a landscape genetics perspective to elucidate mechanisms underlying basic ecological processes driving infectious disease dynamics and to understand the linkage between spatially-dependent population processes and the geographic distribution of genetic variation within both hosts and parasites. The increasing availability of genetic information on hosts and parasites when coupled to their ecological interactions can lead to insights for predicting patterns of disease emergence, spread, and control. Here, we review research progress in this area based on four different motivations for the application of landscape genetics approaches: (1) assessing the spatial organization of genetic variation in parasites as a function of environmental variability, (2) using host population genetic structure as a means to parameterize ecological dynamics that indirectly influence parasite populations, e.g. gene flow and movement pathways across heterogeneous landscapes and the concurrent transport of infectious agents, (3) elucidating the temporal and spatial scales of disease processes, and (4) reconstructing and understanding infectious disease invasion. Throughout this review, we emphasise that landscape genetic principles are relevant to infection dynamics across a range of scales from within host dynamics to global geographic patterns and that they can also be applied to unconventional “landscapes” such as heterogeneous contact networks underlying the spread of human and livestock diseases. We conclude by discussing some general considerations and problems for inferring epidemiological processes from genetic data and try to identify possible future directions and applications for this rapidly expanding field.