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Population genetic structure of the malaria vector Anopheles nili in sub-Saharan Africa

Cyrille Ndo12*, Christophe Antonio-Nkondjio1, Anna Cohuet34, Diego Ayala3, Pierre Kengne13, Isabelle Morlais13, Parfait H Awono-Ambene1, Daniel Couret34, Pierre Ngassam2, Didier Fontenille3 and Frédéric Simard34

Author Affiliations

1 Laboratoire de Recherche sur le Paludisme, Organisation de Coordination pour la lutte Contre les Endémies en Afrique Centrale (OCEAC), P.O. Box 288, Yaoundé, Cameroon

2 Faculty of Sciences, University of Yaoundé I, P.O. Box 812, Yaoundé, Cameroon

3 Institut de Recherche pour le Développement (IRD), UR 016, 911 Avenue Agropolis, P.O. Box 64501, 34394 Montpellier Cedex 5, France

4 Institut de Recherche en Sciences de la Santé (IRSS), P.O. Box 545, Bobo-Dioulasso, Burkina Faso

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Malaria Journal 2010, 9:161  doi:10.1186/1475-2875-9-161

Published: 12 June 2010

Abstract

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.