This is the first study using microsatellite markers to explore An. nili population genetic structure. All loci successfully amplified in each population and were highly polymorphic compared to the isoenzyme markers previously used . This is consistent with previous studies comparing microsatellite to isoenzymes markers in anophelines species [e.g., [51–53]]. Likewise, microsatellite loci were more polymorphic than the rDNA and the mtDNA genes used in this study. This pattern may reflect the small sample sizes used for sequencing and/or insufficient resolution of the molecular markers . Moreover, a biological process such as different evolutionary rates of the markers or locus/region-specific selective constraints could also be involved [55, 56]. Nonetheless, despite this heterogeneity in overall polymorphism across molecular markers, the same trends emerged whereby An. nili populations from West and Central Africa (i.e., from Senegal to Cameroon) appeared genetically homogeneous, whereas mosquitoes sampled in DRC were highly differentiated from the species' core populations. In addition, although individual inferences were rather weak, all markers showed a pattern of diversity and distribution of molecular polymorphisms that is consistent with recent demographic expansion of An. nili throughout its distribution range in West/Central Africa.
Genetic homogeneity within the rDNA genes is not surprising, given the particular evolutionary dynamics of the rDNA operon subject to concerted evolution [e.g. ], rendering it extremely useful for the resolution of deep phylogenies and/or to distinguish between cryptic species but conversely, of little use for within-species population genetics analysis [55, 58]. Mitochondrial DNA evolves faster than the nuclear genome and has been widely used for population genetics and phylogenetics, including arthropod vectors of human diseases [54, 55, 59]. Because of strongly biased AT content, this non-recombining molecule is however subject to saturation, leading to a rapid lost of phylogenetic signal through homoplasy [55, 59]. On the other hand, its lower effective population size (1/4th that of nuclear markers due to maternal inheritance and haploidy) together with increased selection against slightly deleterious mutations  can rapidly increase divergence between lineages within species and reduce local genetic diversity due to enhanced genetic drift and/or molecular hitchhiking resulting in selective sweep throughout the mitochondrial genome [61, 62]. This is in agreement with increased differentiation of the An. nili population from DRC observed with both mtDNA genes. Apparent segregation of different haplotypes between these two genetic clusters in An. nili prompts for further investigation to increase sample sizes and the geographic span of sampling eastwards and southwards of the present study area.
Reduced variability and increased differentiation of the DRC population was also detected using nuclear DNA microsatellite markers. Within each geographical population, HWE was generally respected. Evidence for null alleles at certain loci, as formerly observed by Berthomieu et al , did not obscure the pattern of differentiation between populations, suggesting the set of loci used in this study were able to capture the main patterns of genetic variability within the dataset. Extensive allele sharing between populations and homogeneity across loci in the level of genetic differentiation suggests enhanced genetic drift in the DRC population, rather than selection was responsible of the pattern observed. Unfortunately, the chromosomal locations of the markers remain unknown in the absence of a reliable chromosomal map for An. nili but linkage equilibrium between markers suggests that they are, at least statistically independent and the results might reflect a genome-wide pattern. Reduced variability and increased differentiation is typically observed in populations leaving in marginal habitats at the edge of species' ranges  and the sparsely populated evergreen forest block of Central Africa is known to be of low overall quality for the development of An. nili which is more frequent at the savanna/forest ecotone [14, 21]. Deviation from MDE observed under a range of mutation models in this isolated population indeed suggests unstable demography, although no evidence for a recent bottleneck was obtained. All molecular markers suggested recent demographic expansion in the Kenge and, to a lesser extent, in all other An. nili populations sampled. Detection of this pattern in multiple independent loci make it possible to distinguish it from the effect of selection, which is locus-specific, and attribute it to past demographic change. This is reminiscent of the situation observed in other major vectors of human malaria in Africa and elsewhere , and prompts for further studies to disentangle the confounding effect of shared ancestral polymorphism from that of ongoing gene flow between geographical populations . Moreover, the role of the evergreen forest block as a geographic barrier to gene flow between An. nili populations needs to be further explored, given the low dispersal ability of this mosquito in this environment . Clearly, extending the sampling area eastwards and southwards is needed to provide an overall picture of the level and distribution of genetic diversity within An. nili throughout its distribution range on the continent, and identify both geographic barriers that prevent gene flow between populations and areas of extensive gene exchange as seems to be the case throughout West Africa. Such knowledge is needed to devise efficient, locally adapted and sustainable strategies for the management and control of these vector populations. It is interesting to note that recent investigations of the population genetic structure of An. moucheti sampled in the same localities as presented here (at least in Cameroon and the DRC) did not detect such high level of population differentiation within and across the forest block [53, 66]. Combined analysis of genetic and ecological data in a comparative framework should reveal further insights into the population biology and demographic history of these neglected malaria vectors, and provide relevant information for their control. Recent advances in theoretical population genetics and the rapidly evolving field of spatial genetics [e.g., ] together with the development and democratization of high throughput sequencing technologies provide the necessary tools for such endeavor in non model species.