Close-Kin Genetic Methods to Infer Demography and Dispersal Patterns of Mosquitoes

Seminar | March 7 | 4-5 p.m. | 1011 Evans Hall

 Professor John Marshall, Division of Epidemiology and Biostatistics, UC Berkeley

 Department of Statistics

Malaria, dengue, Zika and other mosquito-borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticide-based tools and antimalarial drugs. Consequently, there is interest in novel strategies to control these diseases, including the release of mosquitoes transfected with Wolbachia and engineered with CRISPR-based gene drive and disease-refractory systems. The safety and effectiveness of these strategies are critically dependent on a detailed understanding of mosquito demography and movement patterns at both fine and broad spatial scales, yet there are major gaps in our understanding of these. The declining cost of genome sequencing and novel methods for analyzing geocoded genomic data provide opportunities to address these knowledge gaps. In this talk, we discuss a new approach to infer fine-scale mosquito dispersal patterns and demographic parameters, such as population size and mating structure, by considering the information contained in a set of pairs of closely-related individuals whose locations are known. These methods have previously been applied to fish such as tuna, sharks and coral trout; but have not yet been applied to insects. We propose in silico simulations of mosquito ecology and dispersal to determine sampling routines capable of quantifying known dispersal patterns and demographic parameters. The resulting models will be used to explore the potential impact of novel mosquito control interventions, and to inform biosafety and trial design considerations.