Kaylee A. Byers, Tom R. Booker, Matthew Combs, Chelsea G. Himsworth, Jason Munshi‐South, David M. Patrick, and Michael C. Whitlock. 2020. Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens. Evolutionary Applications.
doi-org.ezproxy.library.ubc.ca/10.1111/eva.13049
Abstract
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.