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Microgeographical structure in the major Neotropical malaria vector Anopheles darlingi using microsatellites and SNP markers

  • Melina Campos
  • , Jan E. Conn
  • , Diego Peres Alonso
  • , Joseph M. Vinetz
  • , Kevin J. Emerson
  • , Paulo Eduardo Martins Ribolla
  • Universidade Estadual Paulista "Júlio de Mesquita Filho"
  • State University of New York-Albany
  • Wadsworth Center for Laboratories and Research
  • Department of Medicine
  • St. Mary's College of Maryland

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Background: In recent decades, throughout the Amazon Basin, landscape modification contributing to profound ecological change has proceeded at an unprecedented rate. Deforestation that accompanies human activities can significantly change aspects of anopheline biology, though this may be site-specific. Such local changes in anopheline biology could have a great impact on malaria transmission. The aim of this study was to investigate population genetics of the main malaria vector in Brazil, Anopheles darlingi, from a microgeographical perspective. Methods: Microsatellites and ddRADseq-derived single nucleotide polymorphisms (SNPs) were used to assess levels of population genetic structuring among mosquito populations from two ecologically distinctive agricultural settlements (~60 km apart) and a population from a distant (~700 km) urban setting in the western Amazon region of Brazil. Results: Significant microgeographical population differentiation was observed among Anopheles darlingi populations via both model- and non-model-based analysis only with the SNP dataset. Microsatellites detected moderate differentiation at the greatest distances, but were unable to differentiate populations from the two agricultural settlements. Both markers showed low polymorphism levels in the most human impacted sites. Conclusions: At a microgeographical scale, signatures of genetic heterogeneity and population divergence were evident in Anopheles darlingi, possibly related to local environmental anthropic modification. This divergence was observed only when using high coverage SNP markers.

Original languageEnglish
Article number76
Pages (from-to)1-8
Number of pages8
JournalParasites and Vectors
Volume10
Issue number1
DOIs
StatePublished - 13 Feb 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Amazonian Brazil
  • Anopheles darlingi
  • DdRADseq
  • Malaria
  • Microsatellite markers
  • SNPs

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