I’m broadly interested in population genetics/genomics, landscape genetics, invasive species, disease vectors, conservation, and human evolution and health. My graduate work combined genetic tools and spatial analyses to understand gene flow and the invasion dynamics of the Yellow Fever mosquito (Aedes aegypti). Ae. aegpyti is an invasive species that has colonized much of the tropical and subtropical world, and it is a primary vector for dengue, Zika, chikungunya, and yellow fever. As a postdoc I explored population genomics of another widespread species, Homo sapiens!
Migration and adaptation in humans in eastern Africa
The high diversity of ethnicities, languages, and environments in eastern Africa offer an exceptional opportunity to explore the variables that shape migration and genetic structure in humans. I developed SPRUCE (Spatial Prediction using Random forest to Uncover Connectivity among Environments), a machine learning method for identifying the variables which best explain migration rates, with migration rate calculated from shared identical-by-descent tracts between individuals. To further test how environment, subsistence strategy, and disease are exerting selection in eastern Africa, I advised two undergraduate research projects using genome-wide selection scans and haplotype networks.
Pless, Evlyn, Anders M. Eckburg, and Brenna M. Henn. “Predicting environmental and ecological drivers of human population structure.” bioRxiv (2022): 2022-06.
Leadership and bioinformatics with CAAPA
As a postdoc, I served as co-leader of a population genetics working group with >30 international collaborators through the Consortium on Asthma among African-Ancestry Populations in the Americas (CAAPA). This consortium sequenced >300 individuals from 14 diverse populations. In my leadership role, I organized monthly working group meetings and biweekly data analysis meetings, and I helped plan the flagship papers that will be released with the new genomes. I also helped with the bioinformatics processes, e.g. running computational pipelines for alignment and variant calling.
Modeling genetic connectivity in humans and vectors
Landscape genetics involves integrating population genetics with spatial analyses in order to detect and describe gene flow. By combining a random forest modeling approach with an iterative optimization procedure I developed a method to integrate genetic and environmental data to map landscape connectivity. I applied and validated the method for the Aedes aegypti mosquito, with the goal of informing vector control, particularly the release of genetically modified or Wolbachia-infected mosquitoes. I am also adapting the method to take advantage of higher resolution genomic data available for many human populations.
Pless, Evlyn, et al. “A machine-learning approach to map landscape connectivity in Aedes aegypti with genetic and environmental data.” Proceedings of the National Academy of Sciences 118.9 (2021): e2003201118.
Invasion dynamics in a mosquito disease vector
The Yellow Fever mosquito was first detected in northern California (CA) in 2013 and in southern CA in 2014. Using genetic analyses (microsatellites and SNPs) and approximate Bayesian computation, our work shows that the northern and southern CA groups are genetically distinct and originated from separate invasions. I have expanded on this work to consider the new invasion into Las Vegas (2017), and the invasion history across North America more broadly.
Pless, Evlyn, et al. “Multiple introductions of the dengue vector, Aedes aegypti, into California.” PLoS neglected tropical diseases 11.8 (2017): e0005718.
Decision-making in red harvester ants
Social insect colonies use interactions among workers to regulate collective behavior. Previous studies of the activation of foragers in red harvester ants show that an outgoing forager inside the nest experiences an increase in brief antennal contacts before it leaves the nest to forage. With Dr. Deborah, Jovel Queirolo and I investigated whether ants that leave the nest experienced more interactions than those that did not, how the rate of forager return affects the number of available foragers in the entrance chamber, and where most interactions occur.
Pless, Evlyn, et al. “Interactions increase forager availability and activity in harvester ants.” PLoS One 10.11 (2015): e0141971.