Whole genome sequencing (WGS) is an ever expanding tool in the field of genetics, and is widely used to characterize human genetic variation. There are multiple large-scale sequencing studies being conducted today worldwide, like All of Us, Three Million African Genomes, and GenomeAsia 100k. The addition of these diverse datasets alone can be transformative to our understanding of genetics, but the increase in the diversity of populations sampled also has the potential to reveal additional and novel information relevant to health and disease. Specifically, whole genome sequence (WGS) analyses of DNA from human whole blood may be able to capture genetic variation in other species that can affect both individual and public health.
The research detailed in this dissertation aims to illustrate the utility of human WGS data for infectious disease, by showing that the malaria causing parasite Plasmodium can be sensitively detected from unmapped reads (UMRs) from WGS data. Malaria has a significant global health burden, and elimination of the disease has been a goal since the 1950s. Recently, there have been roadblocks in the progress of malaria elimination that can only be resolved through additional research efforts. Development of this detection methodology could be the tool required to better define the parasite population, identify problematic populations, and solve the roadblocks limiting elimination success.