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Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
Evolutionary Applications ( IF 3.5 ) Pub Date : 2020-06-28 , DOI: 10.1111/eva.13049
Kaylee A Byers 1, 2, 3 , Tom R Booker 2 , Matthew Combs 4 , Chelsea G Himsworth 3, 5, 6 , Jason Munshi-South 7 , David M Patrick 5, 8 , Michael C Whitlock 2
Affiliation  

Urban Norway rats (Rattus norvegicus) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape and to evaluate whether these patterns align with pathogen distributions. We genotyped 605 rats from a single neighborhood in Vancouver, Canada, and used 1,495 genome‐wide single nucleotide polymorphisms to identify parent–offspring and sibling relationships using pedigree analysis. We resolved 1,246 pairs of relatives, of which only 1% of pairs were captured in different city blocks. Relatives were primarily caught within 33 meters of each other leading to a highly leptokurtic distribution of dispersal distances. Using binomial generalized linear mixed models, we evaluated whether family relationships influenced rat pathogen status with the bacterial pathogens Leptospira interrogans, Bartonella tribocorum, and Clostridium difficile, and found that an individual's pathogen status was not predicted any better by including disease status of related rats. The spatial clustering of related rats and their pathogens lends support to the hypothesis that spatially restricted movement promotes the heterogeneous patterns of pathogen prevalence evidenced in this population. Our findings also highlight the utility of evolutionary tools to understand movement and rat‐associated health risks in urban landscapes.

中文翻译:


利用遗传相关性了解城市大鼠相关病原体的异质分布



挪威城市老鼠( Rattusnorvegicus )携带多种可传染给人类的病原体。然而,病原体流行率在不同的精细空间尺度(即按城市街区)之间可能有所不同。使用群体基因组学方法,我们试图描述老鼠在城市景观中的运动模式,并评估这些模式是否与病原体分布相符。我们对来自加拿大温哥华一个社区的 605 只老鼠进行了基因分型,并使用 1,495 个全基因组单核苷酸多态性通过谱系分析来识别亲子关系和兄弟姐妹关系。我们解决了 1,246 对亲属,其中只有 1% 的亲属是在不同的城市街区被抓获的。亲属间的距离主要在 33 米以内,导致扩散距离呈高度尖峰分布。使用二项式广义线性混合模型,我们评估了家庭关系是否影响细菌病原体问号钩端螺旋体摩擦巴尔通体艰难梭菌的大鼠病原体状态,并发现通过包括相关大鼠的疾病状态并不能更好地预测个体的病原体状态。相关大鼠及其病原体的空间聚集支持了这样的假设:空间受限的运动促进了该群体中病原体流行的异质模式。我们的研究结果还强调了进化工具在了解城市景观中的运动和与老鼠相关的健康风险方面的实用性。
更新日期:2020-06-28
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