Minimal genetic differentiation of the malaria vector Nyssorhynchus darlingi associated with forest cover level in Amazonian Brazil.

Autor: Prussing C; University at Albany, State University of New York, School of Public Health, Department of Biomedical Sciences, Albany, NY, United States of America., Emerson KJ; Department of Biology, St. Mary's College of Maryland, St. Mary's City, MD, United States of America., Bickersmith SA; Wadsworth Center, New York State Department of Health, Albany, NY, United States of America., Sallum MAM; Departamento de Epidemiologia, Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, SP, Brasil., Conn JE; University at Albany, State University of New York, School of Public Health, Department of Biomedical Sciences, Albany, NY, United States of America.; Wadsworth Center, New York State Department of Health, Albany, NY, United States of America.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2019 Nov 14; Vol. 14 (11), pp. e0225005. Date of Electronic Publication: 2019 Nov 14 (Print Publication: 2019).
DOI: 10.1371/journal.pone.0225005
Abstrakt: The relationship between deforestation and malaria in Amazonian Brazil is complex, and a deeper understanding of this relationship is required to inform effective control measures in this region. Here, we are particularly interested in characterizing the impact of land use and land cover change on the genetics of the major regional vector of malaria, Nyssorhynchus darlingi (Root). We used nextera-tagmented, Reductively Amplified DNA (nextRAD) genotyping-by-sequencing to genotype 164 Ny. darlingi collected from 16 collection sites with divergent forest cover levels in seven municipalities in four municipality groups that span the state of Amazonas in northwestern Amazonian Brazil: São Gabriel da Cachoeira, Presidente Figueiredo, four municipalities in the area around Cruzeiro do Sul, and Lábrea. Using a dataset of 5,561 Single Nucleotide Polymorphisms (SNPs), we investigated the genetic structure of these Ny. darlingi populations with a combination of model- and non-model-based analyses. We identified weak to moderate genetic differentiation among the four municipality groups. There was no evidence for microgeographic genetic structure of Ny. darlingi among forest cover levels within the municipality groups, indicating that there may be gene flow across areas of these municipalities with different degrees of deforestation. Additionally, we conducted an environmental association analysis using two outlier detection methods to determine whether individual SNPs were associated with forest cover level without affecting overall population genetic structure. We identified 14 outlier SNPs, and investigated functions associated with their proximal genes, which could be further characterized in future studies.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
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