Poster #46 - Esther Weyer

Population genomic analysis of H. majoris and its host the blue tit (Cyanistes caeruleus) over a quarter of a century

Esther Weyer, BS Center for Bioinformatics and Computational Biology & Department of Entomology and Wildlife Ecology, University of Delaware, Newark, DE, USA Diana Ekman, PhD Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Sweden Vincenzo A. Ellis, PhD Department of Entomology and Wildlife Ecology, University of Delaware, Newark, DE, USA Dag Ahrén, PhD National Bioinformatics Infrastructure Sweden (NBIS), SciLifeLab, Department of Biology, Lund University, Lund, Sweden Olof Hellgren, PhD Evolutionary Ecology and Infection Biology, Department of Biology, Lund University, SE-22362 Lund, Sweden Jan-Åke Nilsson, PhD Ecological and Evolutionary Physiology & Evolutionary Ecology and Infection Biology, Department of Biology, Lund University, SE-22362 Lund, Sweden

Determining pathogen and host dynamics at the genomic level is essential for understanding underlying mechanisms for infectivity and fitness. A perfect study system to investigate host- pathogen evolution and ecology exists in a population of Eurasian bluetits (Cyanistes caeruleus) around Krankesjön in Southern Sweden. Infections of these birds with the avian malaria pathogen Haemoproteus majoris, have been monitored over decades, with sample collections covering multiple generations of the host species. By applying a newly developed selective whole genome amplification (SWGA) method, we are able to utilize these historically collected samples to study genomic fluctuations in the host and pathogen populations over time. This study incorporates approximately 100 samples of positive infections spanning a 28-year period from the same geographic region experiencing an increase in pathogen prevalence from ~40% to ~90% among the adult birds. We aim to identify host and pathogen population structures, genomic-level variation, and shifts in genotype frequencies across temporal scales. Measures will include fixation index (Fst), population structure analysis with ADMIXTURE and UMAP, and identification of significantly altered genotype frequencies. We expect results to show three distinct populations separated by collection year and that SNPs associated with infectivity pathways in the pathogen or immunological response in the host will undergo a shift in frequency between alleles over the years correlating to the observed increase in presence of the pathogen.