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Data from: Using genetic relatedness to understand heterogeneous distributions of urban rat-associated pathogens Byers, Kaylee; Booker, Tom; Combs, Matthew; Himsworth, Chelsea; Munshi-South, Jason; Patrick, David; Whitlock, Michael
Description
<b>Abstract</b><br/>
Urban Norway rats (<i>Rattus norvegicus</i>) 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 <i>Leptospira interrogans</i>, <i>Bartonella tribocorum</i>, and <i>Clostridium difficile</i>, 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. <span lang="EN-US" style="background:white;">Our findings also highlight the utility of evolutionary tools to understand movement and rat-associated health risks in urban landscapes.</span></p>; <b>Usage notes</b><br />
<u><strong>Full_SNP_genotypes.vcf</strong></u></p>
A vcf file containing the original dataset of 519,939 SNP genotypes from 617 Norway rats.</p>
<u><strong>Filtered_SNP_genotypes.vcf</strong></u></p>
A vcf file containing a subset of 1,495 SNP genotypes from 605 Norway rats obtained through filtering steps outlined in the manuscript.</p>
<u><strong>Rat_MetaData_All.csv</strong></u></p>
This file contains relevant metadata for rats included in this analysis, such as location and season of capture, sex, maturity, age, and pathogen status. This data sheet contains the data for all 617 rats included in the Full_SNP_genotypes file.</p>
<u><strong>Rat_MetaData_Subset.csv</strong></u></p>
This file contains relevant metadata for rats included in this analysis, such as location and season of capture, sex, maturity, age, and pathogen status. This data sheet contains the data for the subset of 605 rats analyzed in this paper.</p>
<u><strong>MetaData_Variables_Explained.pdf</strong></u></p>
This file includes details regarding how variables in the Rat MetaData files are coded.</p>
Item Metadata
Title |
Data from: Using genetic relatedness to understand heterogeneous distributions of urban rat-associated pathogens
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Creator | |
Date Issued |
2021-05-19
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Description |
<b>Abstract</b><br/>
Urban Norway rats (<i>Rattus norvegicus</i>) 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 <i>Leptospira interrogans</i>, <i>Bartonella tribocorum</i>, and <i>Clostridium difficile</i>, 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. <span lang="EN-US" style="background:white;">Our findings also highlight the utility of evolutionary tools to understand movement and rat-associated health risks in urban landscapes.</span></p>; <b>Usage notes</b><br /> <u><strong>Full_SNP_genotypes.vcf</strong></u></p> A vcf file containing the original dataset of 519,939 SNP genotypes from 617 Norway rats.</p> <u><strong>Filtered_SNP_genotypes.vcf</strong></u></p> A vcf file containing a subset of 1,495 SNP genotypes from 605 Norway rats obtained through filtering steps outlined in the manuscript.</p> <u><strong>Rat_MetaData_All.csv</strong></u></p> This file contains relevant metadata for rats included in this analysis, such as location and season of capture, sex, maturity, age, and pathogen status. This data sheet contains the data for all 617 rats included in the Full_SNP_genotypes file.</p> <u><strong>Rat_MetaData_Subset.csv</strong></u></p> This file contains relevant metadata for rats included in this analysis, such as location and season of capture, sex, maturity, age, and pathogen status. This data sheet contains the data for the subset of 605 rats analyzed in this paper.</p> <u><strong>MetaData_Variables_Explained.pdf</strong></u></p> This file includes details regarding how variables in the Rat MetaData files are coded.</p> |
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Type | |
Notes |
Dryad version number: 4</p> Version status: submitted</p> Dryad curation status: Published</p> Sharing link: https://datadryad.org/stash/share/tTJv7dq9TyRdSzJFIfeOJJs41_6BAJyvkMmB97syonI</p> Storage size: 3528757707</p> Visibility: public</p> |
Date Available |
2020-08-21
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Provider |
University of British Columbia Library
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License |
CC0 1.0
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DOI |
10.14288/1.0397650
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URI | |
Publisher DOI | |
Grant Funding Agency |
Canadian Institutes of Health Research; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; National Science Foundation
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Rights URI | |
Aggregated Source Repository |
Dataverse
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CC0 1.0