Presentation description

Malaria poses a global burden with approximately 250 million cases annually. Due to rapid evolution in the parasite, it is able to evade host immune responses, thus causing disease and breaking down current treatment measures. Plasmodium falciparum is responsible for the majority of these cases, so understanding the evolutionary mechanisms allowing it to persist in the face of drug and immune pressure is pivotal in disease mitigation and control. Immune evasion genes are often balancing selection which is a selective pressure that maintains multiple alleles in the gene pool. A signature of balancing selection commonly detected by previous genomic methods is excess heterozygosity and a deficit of substitutions, but these methods have low power. Here, we use a metric called β statistics that detects balancing selection by identifying a cluster of alleles at similar frequencies. This leads to higher precision and minimizes the effects of population structure. To find regions containing immune gene candidates, we used genetic variation data from the P. falciparum genome (Pf7) isolated from infections in Cameroon and calculated β statistics. Variants maintained at similar allele frequencies exhibit β scores above zero with the highest β scores being the most indicative of genes under balancing selection. We found several genes previously reported to be under balancing selection as well as additional candidates not detected under previous methods such as PF3D7_0701900 and PF3D7_1035200. Through a deeper understanding of evolutionary patterns underlying parasite biology, we can leverage host-parasite coevolution to combat one of the world's major public health challenges.