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Taxonomy, diversity, temporal and geographical distribution of Cutaneous Leishmaniasis in Colombia: A retrospective study.哥伦比亚皮肤利什曼病的分类学、多样性、时间和地理分布:一项回顾性研究。
Sci Rep. 2016 Jun 22;6:28266. doi: 10.1038/srep28266.
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Multi-taxa integrated landscape genetics for zoonotic infectious diseases: deciphering variables influencing disease emergence.人畜共患传染病的多分类群综合景观遗传学:解读影响疾病出现的变量
Genome. 2016 May;59(5):349-61. doi: 10.1139/gen-2016-0039. Epub 2016 Mar 4.
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Explaining the geographic spread of emerging epidemics: a framework for comparing viral phylogenies and environmental landscape data.解释新发传染病的地理传播:一种比较病毒系统发育和环境景观数据的框架。
BMC Bioinformatics. 2016 Feb 11;17:82. doi: 10.1186/s12859-016-0924-x.
4
Coupled Heterogeneities and Their Impact on Parasite Transmission and Control.耦合异质性及其对寄生虫传播与控制的影响。
Trends Parasitol. 2016 May;32(5):356-367. doi: 10.1016/j.pt.2016.01.001. Epub 2016 Feb 2.
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Host dispersal as the driver of parasite genetic structure: a paradigm lost?宿主扩散作为寄生虫遗传结构的驱动因素:一种过时的范例?
Ecol Lett. 2016 Mar;19(3):336-47. doi: 10.1111/ele.12564. Epub 2016 Jan 5.
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Real-time, portable genome sequencing for Ebola surveillance.用于埃博拉监测的实时便携式基因组测序
Nature. 2016 Feb 11;530(7589):228-232. doi: 10.1038/nature16996. Epub 2016 Feb 3.
7
Navigating the pitfalls and promise of landscape genetics.应对景观遗传学的陷阱与前景
Mol Ecol. 2016 Feb;25(4):849-63. doi: 10.1111/mec.13527.
8
Environmental Correlation Analysis for Genes Associated with Protection against Malaria.与疟疾防护相关基因的环境关联分析
Mol Biol Evol. 2016 May;33(5):1188-204. doi: 10.1093/molbev/msw004. Epub 2016 Jan 6.
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Harnessing the power of RADseq for ecological and evolutionary genomics.利用RADseq技术助力生态与进化基因组学研究
Nat Rev Genet. 2016 Feb;17(2):81-92. doi: 10.1038/nrg.2015.28. Epub 2016 Jan 5.
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Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America, under Climate Change.生态位建模预测在气候变化下,南美利什曼原虫(亚马逊利什曼原虫)的传播媒介黄盾罗蛉(罗蛉属)(双翅目:毛蠓科:白蛉亚科)将向南扩张。
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利用景观基因组学框架预测和预防寄生虫病。

Prediction and Prevention of Parasitic Diseases Using a Landscape Genomics Framework.

机构信息

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK.

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK.

出版信息

Trends Parasitol. 2017 Apr;33(4):264-275. doi: 10.1016/j.pt.2016.10.008. Epub 2016 Nov 16.

DOI:10.1016/j.pt.2016.10.008
PMID:27863902
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5376512/
Abstract

Substantial heterogeneity exists in the dispersal, distribution and transmission of parasitic species. Understanding and predicting how such features are governed by the ecological variation of landscape they inhabit is the central goal of spatial epidemiology. Genetic data can further inform functional connectivity among parasite, host and vector populations in a landscape. Gene flow correlates with the spread of epidemiologically relevant phenotypes among parasite and vector populations (e.g., virulence, drug and pesticide resistance), as well as invasion and re-invasion risk where parasite transmission is absent due to current or past intervention measures. However, the formal integration of spatial and genetic data ('landscape genetics') is scarcely ever applied to parasites. Here, we discuss the specific challenges and practical prospects for the use of landscape genetics and genomics to understand the biology and control of parasitic disease and present a practical framework for doing so.

摘要

寄生虫的传播、分布和传播存在很大的异质性。了解和预测寄生虫在其栖息的景观生态变化下是如何受到这些特征的影响,是空间流行病学的核心目标。遗传数据可以进一步提供寄生虫、宿主和媒介种群在景观中的功能连接信息。基因流动与寄生虫和媒介种群中具有流行病学意义的表型(如毒力、药物和农药抗性)的传播以及由于当前或过去的干预措施导致寄生虫传播缺失时的入侵和再入侵风险相关。然而,很少有将空间和遗传数据(“景观遗传学”)正式整合到寄生虫中的情况。在这里,我们讨论了使用景观遗传学和基因组学来理解寄生虫病的生物学和控制的具体挑战和实际前景,并提出了一个实用的框架来实现这一目标。