Dataset Information

Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi.

ABSTRACT: BACKGROUND: Anopheles darlingi is the main malaria mosquito vector in the Amazonia region. In spite of being considered a riverine, forest-dwelling species, this mosquito is becoming more abundant in peri-urban areas, increasing malaria risk. This has been associated with human-driven environmental changes such as deforestation. METHODS: Microsatellites were used to characterize A. darlingi from seven localities along the Madeira River, Rondônia (Brazil), collected in the early and late periods of the rainy season. RESULTS: Two genetically distinct subpopulations were detected: one (subpopulation A) was associated with the late rainfall period and seems to be ecologically closer to the typical forest A. darlingi; the other (subpopulation B) was associated with the early rainfall period and is probably more adapted to drier conditions by exploiting permanent anthropogenic breeding sites. Results suggest also a pattern of asymmetric introgression, with more subpopulation A alleles introgressed into subpopulation B. Both subpopulations (and admixed mosquitoes) presented similar malaria infection rates, highlighting the potential for perennial malaria transmission in the region. CONCLUSIONS: The co-occurrence of two genetically distinct subpopulations of A. darlingi adapted to different periods of rainfall may promote a more perennial transmission of malaria throughout the year. These findings, in a context of strong environmental impact due to deforestation and dam construction, have serious implications for malaria epidemiology and control in the Amazonian region.

SUBMITTER: Angella AF

PROVIDER: S-EPMC4059831 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi.

Angêlla Aline F AF Salgueiro Patrícia P Gil Luiz H S LH Vicente José L JL Pinto João J Ribolla Paulo E M PE

Malaria journal 20140529

<h4>Background</h4>Anopheles darlingi is the main malaria mosquito vector in the Amazonia region. In spite of being considered a riverine, forest-dwelling species, this mosquito is becoming more abundant in peri-urban areas, increasing malaria risk. This has been associated with human-driven environmental changes such as deforestation.<h4>Methods</h4>Microsatellites were used to characterize A. darlingi from seven localities along the Madeira River, Rondônia (Brazil), collected in the early and ...[more]

PMID: 24885508

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Project description:BACKGROUND:Anopheles nili is a widespread efficient vector of human malaria parasites in the humid savannas and forested areas of sub-Saharan Africa. Understanding An. nili population structure and gene flow patterns could be useful for the development of locally-adapted vector control measures. METHODS:Polymorphism at eleven recently developed microsatelitte markers, and sequence variation in four genes within the 28s rDNA subunit (ITS2 and D3) and mtDNA (COII and ND4) were assessed to explore the level of genetic variability and differentiation among nine populations of An. nili from Senegal, Ivory Coast, Burkina Faso, Nigeria, Cameroon and the Democratic Republic of Congo (DRC). RESULTS:All microsatellite loci successfully amplified in all populations, showing high and very similar levels of genetic diversity in populations from West Africa and Cameroon (mean Rs = 8.10-8.88, mean He = 0.805-0.849) and much lower diversity in the Kenge population from DRC (mean Rs = 5.43, mean He = 0.594). Bayesian clustering analysis of microsatellite allelic frequencies revealed two main genetic clusters in the dataset. The first one included only the Kenge population and the second grouped together all other populations. High Fst estimates based on microsatellites (Fst > 0.118, P < 0.001) were observed in all comparisons between Kenge and all other populations. By contrast, low Fst estimates (Fst < 0.022, P < 0.05) were observed between populations within the second cluster. The correlation between genetic and geographic distances was weak and possibly obscured by demographic instability. Sequence variation in mtDNA genes matched these results, whereas low polymorphism in rDNA genes prevented detection of any population substructure at this geographical scale. CONCLUSION:Overall, high genetic homogeneity of the An. nili gene pool was found across its distribution range in West and Central Africa, although demographic events probably resulted in a higher level of genetic isolation in the marginal population of Kenge (DRC). The role of the equatorial forest block as a barrier to gene flow and the implication of such findings for vector control are discussed.

Dataset Information

Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi.

Publications

Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi.

Similar Datasets

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