Population genomics of a zoonotic disease host: The capybara as study case — Promaco Conventions

Population genomics of a zoonotic disease host: The capybara as study case (#684)

Juan Pablo Torres-Florez 1 , Sarah Hendricks 2 , Ubiratan Piovezan 3 , Francisco Costa 4 , Marcelo B Labruna 4 , Paul Hohenlohe 2 , Pedro M Galetti Jr. 1
  1. Dep. Genética e Evolução, Universidade Federal de São Carlos, São Carlos, SP, Brazil
  2. Dept. of Biological Sciences, University of Idaho, Moscow, ID, USA
  3. Centro de Pesquisas Agropecuárias do Pantanal, EMBRAPA, Corumba, MS, Brazil
  4. Depto. de Med. Vet. Preventiva e Saúde Animal, Universidade de São Paulo, São Paulo, SP, Brazil

Habitat fragmentation creates open areas that could be used by generalist species as corridors among populations, allowing for gene flow, but also facilitating the spread of vector borne diseases that use these species as hosts. With the aim to understand how the genetic diversity of a zoonotic disease host is distributed along a strongly modified habitat and therefore can serve as a proxy of disease spread, we used the capybara (Hydrochoerus hydrochaeris) as study system. The capybara is the largest rodent and inhabits open areas along its distribution. This species also is the main host of the cayenne tick and therefore the vector of Brazilian Spotted Fever (BSF). With habitat modification for sugar cane crops in Sao Paulo state, capybara populations have increased and BSF cases have been increasing in recent years. Here we present results about i) capybara genetic variation assessed by the use of genomic tools and, ii) the population genetic structure of the species in Sao Paulo state. For our analyses we used a reduced representation genomic library created using a RAD-seq protocol. We identified ~20,000 SNPs along the genome in 158 samples distributed along 11 populations in Sao Paulo state and two in Mato Grosso and Mato Grosso do Sul. Our results using pairwise Fst showed eight different populations, while clustering methods showed three different populations. These data will be of great importance for the management of populations, to avoid further spread of BSF.

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