School of Biological Sciences, Washington State University, Pullman, WA, USA.
Department of Integrative Biology, University of California, Berkeley, CA, USA.
Mol Ecol. 2020 Sep;29(17):3217-3233. doi: 10.1111/mec.15558. Epub 2020 Aug 2.
Genetic structure in host species is often used to predict disease spread. However, host and pathogen genetic variation may be incongruent. Understanding landscape factors that have either concordant or divergent influence on host and pathogen genetic structure is crucial for wildlife disease management. Devil facial tumour disease (DFTD) was first observed in 1996 and has spread throughout almost the entire Tasmanian devil geographic range, causing dramatic population declines. Whereas DFTD is predominantly spread via biting among adults, devils typically disperse as juveniles, which experience low DFTD prevalence. Thus, we predicted little association between devil and tumour population structure and that environmental factors influencing gene flow differ between devils and tumours. We employed a comparative landscape genetics framework to test the influence of environmental factors on patterns of isolation by resistance (IBR) and isolation by environment (IBE) in devils and DFTD. Although we found evidence for broad-scale costructuring between devils and tumours, we found no relationship between host and tumour individual genetic distances. Further, the factors driving the spatial distribution of genetic variation differed for each. Devils exhibited a strong IBR pattern driven by major roads, with no evidence of IBE. By contrast, tumours showed little evidence for IBR and a weak IBE pattern with respect to elevation in one of two tumour clusters we identify herein. Our results warrant caution when inferring pathogen spread using host population genetic structure and suggest that reliance on environmental barriers to host connectivity may be ineffective for managing the spread of wildlife diseases. Our findings demonstrate the utility of comparative landscape genetics for identifying differential factors driving host dispersal and pathogen transmission.
宿主物种的遗传结构通常被用来预测疾病的传播。然而,宿主和病原体的遗传变异可能不一致。了解对宿主和病原体遗传结构具有一致或不同影响的景观因素,对于野生动物疾病管理至关重要。恶魔面部肿瘤病(DFTD)于 1996 年首次发现,现已传播到塔斯马尼亚恶魔的几乎整个地理范围,导致其数量急剧下降。虽然 DFTD 主要通过成年恶魔之间的咬伤传播,但恶魔通常在幼年时分散,其 DFTD 患病率较低。因此,我们预测恶魔和肿瘤种群结构之间的关联很小,并且影响基因流动的环境因素在恶魔和肿瘤之间存在差异。我们采用比较景观遗传学框架来检验环境因素对恶魔和 DFTD 中隔离抵抗(IBR)和隔离环境(IBE)模式的影响。尽管我们发现恶魔和肿瘤之间存在广泛的结构成本构,但我们没有发现宿主和肿瘤个体遗传距离之间存在关系。此外,驱动遗传变异空间分布的因素也各不相同。恶魔表现出强烈的 IBR 模式,由主要道路驱动,没有 IBE 的证据。相比之下,肿瘤在两个肿瘤群中的一个中,其 IBR 模式几乎没有证据,IBE 模式较弱,与海拔高度有关。我们的结果表明,在使用宿主种群遗传结构推断病原体传播时需要谨慎,并且表明依赖于宿主连通性的环境障碍可能对管理野生动物疾病的传播无效。我们的研究结果表明,比较景观遗传学在确定驱动宿主扩散和病原体传播的差异因素方面具有实用性。