| Full text | |
| Author(s): |
Prussing, Catharine
[1]
;
Emerson, Kevin J.
[2]
;
Bickersmith, Sara A.
[3]
;
Mureb Sallum, Maria Anice
[4]
;
Conn, Jan E.
[1, 3]
Total Authors: 5
|
| Affiliation: | [1] SUNY Albany, Sch Publ Hlth, Dept Biomed Sci, Albany, NY 12222 - USA
[2] St Marys Coll Maryland, Dept Biol, St Marys City, MD 20686 - USA
[3] New York State Dept Hlth, Wadsworth Ctr, Albany, NY 12203 - USA
[4] Univ Sao Paulo, Fac Saude Publ, Dept Epidemiol, Sao Paulo, SP - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | PLoS One; v. 14, n. 11 NOV 14 2019. |
| Web of Science Citations: | 2 |
| Abstract | |
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: Sao Gabriel da Cachoeira, Presidente Figueiredo, four municipalities in the area around Cruzeiro do Sul, and Labrea. 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. (AU) | |
| FAPESP's process: | 14/26229-7 - Latitudinal landscape genomics and ecology of Anopheles darlingi |
| Grantee: | Maria Anice Mureb Sallum |
| Support type: | Research Projects - Thematic Grants |