Abstract
Tsetse flies (genus Glossina) are the only vector for the parasitic trypanosomes responsible for sleeping sickness and nagana across sub‐Saharan Africa. In Uganda, the tsetse fly Glossina fuscipes fuscipes is responsible for transmission of the parasite in 90% of sleeping sickness cases, and co‐occurrence of both forms of human‐infective trypanosomes makes vector control a priority. We use population genetic data from 38 samples from northern Uganda in a novel methodological pipeline that integrates genetic data, remotely sensed environmental data, and hundreds of field‐survey observations. This methodological pipeline identifies isolated habitat by first identifying environmental parameters correlated with genetic differentiation, second, predicting spatial connectivity using field‐survey observations and the most predictive environmental parameter(s), and third, overlaying the connectivity surface onto a habitat suitability map. Results from this pipeline indicated that net photosynthesis was the strongest predictor of genetic differentiation in G. f. fuscipes in northern Uganda. The resulting connectivity surface identified a large area of well‐connected habitat in northwestern Uganda, and twenty‐four isolated patches on the northeastern margin of the G. f. fuscipes distribution. We tested this novel methodological pipeline by completing an ad hoc sample and genetic screen of G. f. fuscipes samples from a model‐predicted isolated patch, and evaluated whether the ad hoc sample was in fact as genetically isolated as predicted. Results indicated that genetic isolation of the ad hoc sample was as genetically isolated as predicted, with differentiation well above estimates made in samples from within well‐connected habitat separated by similar geographic distances. This work has important practical implications for the control of tsetse and other disease vectors, because it provides a way to identify isolated populations where it will be safer and easier to implement vector control and that should be prioritized as study sites during the development and improvement of vector control methods.
Highlights
Tsetse flies are the only vectors of the trypanosome parasites that cause animal African trypanosomiasis (AAT) and human African trypanosomiasis (HAT), respectively, known as nagana and sleeping sickness
Recent work has shown that strong isolation by distance (IBD) can create a false signal of population structure (Frantz et al, 2009; Meirmans et al, 2012; Falush et al, 2016) and can result in a STRUCTURE pattern that looks like a smooth transition between two genetic clusters, which is exactly what we find at K = 2 in this study area (Figure S3, Appendix S2)
Results from the multiple matrix regression with randomization (MMRR) and the partial Mantel tests (Figure 2: M3) indicated that net photosynthesis, PSN, is the strongest predictor of tsetse fly genetic differentiation beyond that expected based on geographic distance alone (Table 2), and support the use of PSN in the step of the pipeline, maximum entropy modeling (Figure 2: M4)
Summary
Tsetse flies (genus Glossina) are the only vectors of the trypanosome parasites that cause animal African trypanosomiasis (AAT) and human African trypanosomiasis (HAT), respectively, known as nagana and sleeping sickness. Rhodesiense, respectively, the formal taxonomic rank is under revision (Berriman et al, 2005; Echodu et al, 2015; Gibson, Marshall, Marshall, & Godfrey, 1980; Jackson et al, 2010; Sistrom et al, 2016) Regardless of taxonomy, both forms of the disease cause serious human illness and are difficult to treat, and the specific drug treatment course depends on the type and stage of the infection (Fèvre, Picozzi, Jannin, Welburn, & Maudlin, 2006; Fèvre, Wissmann, Welburn, & Lutumba, 2008). One of the most effective means of disease control is to reduce tsetse fly populations and thereby interrupt the transmission cycle
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