Phylogeography and Population Structure of Glossina fuscipes fuscipes in Uganda: Implications for Control of Tsetse

Abstract

Background Glossina fuscipes fuscipes, a riverine species of tsetse, is the main vector of both human and animal trypanosomiasis in Uganda. Successful implementation of vector control will require establishing an appropriate geographical scale for these activities. Population genetics can help to resolve this issue by characterizing the extent of linkage among apparently isolated groups of tsetse.Methodology/Principal FindingsWe conducted genetic analyses on mitochondrial and microsatellite data accumulated from approximately 1000 individual tsetse captured in Uganda and neighboring regions of Kenya and Sudan. Phylogeographic analyses suggested that the largest scale genetic structure in G. f. fuscipes arose from an historical event that divided two divergent mitochondrial lineages. These lineages are currently partitioned to northern and southern Uganda and co-occur only in a narrow zone of contact extending across central Uganda. Bayesian assignment tests, which provided evidence for admixture between northern and southern flies at the zone of contact and evidence for northerly gene flow across the zone of contact, indicated that this structure may be impermanent. On the other hand, microsatellite structure within the southern lineage indicated that gene flow is currently limited between populations in western and southeastern Uganda. Within regions, the average FST between populations separated by less than 100 km was less than ∼0.1. Significant tests of isolation by distance suggested that gene flow is ongoing between neighboring populations and that island populations are not uniformly more isolated than mainland populations.Conclusions/SignificanceDespite the presence of population structure arising from historical colonization events, our results have revealed strong signals of current gene flow within regions that should be accounted for when planning tsetse control in Uganda. Populations in southeastern Uganda appeared to receive little gene flow from populations in western or northern Uganda, supporting the feasibility of area wide control in the Lake Victoria region by the Pan African Tsetse and Trypanosomiasis Eradication Campaign.

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

“…This lake runs east to west with multiple finger‐like inlets and wetland's across most of central Uganda. The extent of its wetlands and satellite lakes marks the eastern boundary of the G. f. fuscipes distribution and coincides with a clear genetic break between northern and southern Uganda G. f. fuscipes populations (Abila et al., 2008; Aksoy et al., 2013; Beadell et al., 2010, 2010). The updated habitat suitability model reflects this by identifying patchy habitat along the eastern margin of the G. f. fuscipes distribution (Figure 5b).…”

“…This suggests that the major patterns of genetic differentiation were created under conditions of migration‐drift balance and that bottlenecks did not confound results in this study. This conclusion is also supported by previous population genetics studies that have shown evidence of ongoing gene flow among distinct populations separated by over 100 km (Abila et al., 2008; Beadell et al., 2010; Echodu et al., 2013; Hyseni et al., 2012; Opiro et al., 2017). Perhaps genetic drift contributes to high levels of genetic differentiation across small spatial scales and is counterbalanced periodically by rare long‐distance dispersal that connects populations along the habitat corridors identified in our analyses.…”

“…These discrete and spatially isolated populations could be used to explore the feasibility of new control approaches, such as genetic‐based ones including transgenesis and paratransgenesis (reviewed in McGraw & O'Neill, 2013), because of their lower risk of migration in/out of the area and thereby reduced recolonization from neighboring sites outside the control area. However, as with any control measure, caution should be practiced because long‐range migration is also known to occur in this system (Beadell et al., 2010; Krafsur, Marquez, & Ouma, 2008; Opiro et al., 2017). …”

“…When we combine this output (Figure 2: O 3 ) with models of connectivity using field‐survey presence data, we integrate the evolutionary and ecological time scales to obtain a more complete understanding of patterns of migration over hundreds to thousands of generations and current regions of high ecological suitability. This is especially relevant in this context because long‐range migration events have been described in G. f. fuscipes populations, as evidenced by the finding of migrants from distances of up to ~60 km (Beadell et al., 2010; Krafsur et al., 2008; Opiro et al., 2017). …”

“…We used the default program parameters, which included a logistic output that provides a 0‐1 scale probability of a presence. We gave a 0% predicted probability of presence to large continuous water bodies, such as Lake Albert, Lake Kyoga, Victoria Nile, and Albert Nile (Figure 1), as studies have shown that stretches of >10 km of open water are effective barrier to G. f. fuscipes dispersal and gene flow (Beadell et al., 2010; Echodu et al., 2013). Note that in this step, we used MaxEnt in a univariate rather that multivariate analyses, as we only had one environmental variable of significant correlation with genetic differentiation (see results).…”