A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
Ecology and evolution
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 s amples f rom a m odel-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.
Description
Keywords
Landscape genetics, Maximum entropy model, Sleeping sickness, Spatial genetics, Tsetse fly, Vector control
Citation
Saarman, N., Burak, M., Opiro, R., Hyseni, C., Echodu, R., Dion, K., ... & Caccone, A. (2018). A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda. Ecology and evolution, 8(11), 5336-5354. DOI: 10.1002/ece3.4050