Combining Aedes aegypti genomics and modeling to improve gene drive strategies and our understanding of resistance evolution

Summary/Abstract
The mosquito, Aedes aegypti, is a primary vector for dengue, chikungunya, Zika, and urban yellow
fever viruses. Dengue has become the most important human arthropod-borne viral infection
worldwide. Each of these pathogens can be associated with explosive epidemics, where high
disease incidence and public fear combine to overwhelm health systems. Public health departments
often react with emergency insecticide-based vector control measures. Spraying with pyrethroid
insecticides is the main approach used for adult Ae. aegypti control in many countries. While the
impact of this spraying on disease suppression has been questioned, there is no doubt that the
repeated use of pyrethroid sprays has caused geographically widespread evolution of resistance
and loss of impact of pyrethroids on mosquito densities.
Over 10,000 archived samples of Ae. aegypti collected from Iquitos, Peru since 2000 are being
held at -80˚C and have intact DNA. Over this period of time pyrethroid spray efficacy in Iquitos has
declined substantially due to resistance. These samples will be used to assess patterns of spatial
and temporal change in genes associated with pyrethroid resistance and in genomic differentiation.
With this genomic information it will be possible to test hypotheses about the dynamics of pyrethroid
resistance evolution and hypotheses about the efficacy of new gene drive strategies that could
suppress Ae. aegypti populations or lower the ability of the mosquito to transmit pathogens. These
tests will be enabled by new algorithms for analysis of mating structure. A spatially explicit,
stochastic model of Ae. aegypti population dynamics and genetics will be parameterized with the
new genomic data and used to predict future dynamics of insecticide resistance and gene drives.
Outcomes of this work will provide research, regulatory, and management communities with
information needed to more accurately predict dynamics of a variety of gene drive strategies as well
as the spread of resistance to insecticides in this arbovirus vector.
We have three Aims in this project that will together result in these more accurate predictions:
AIM 1. Use single gene and genome-wide methods to characterize temporal and spatial genetic
differentiation in Ae. aegypti populations
AIM 2. Use the data from Aim 1 to develop a more accurate understanding of the movement and mating
structure of Ae. aegypti
AIM 3. Incorporate findings from Aim 2 into a detailed Ae. aegypti model, and use it to test a variety of
existing and new strategies for gene drives as well as for monitoring evolution of resistance in Ae.
aegypti to use of gene drives and insecticides.
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