Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal
S. F. Schaffner, Aïda Sadikh Badiane, Akanksha Khorgade, Médoune Ndiop, Jules Gomis, Wesley Wong, Yaye Dié Ndiaye, Younouss Diédhiou, Julie Thwing, Mame Cheikh Seck, Angela M. Early, Mouhamad Sy, Awa B. Dème, Mamadou Alpha Diallo, Ngayo Sy, Aita Sène, Tolla Ndiaye, Djiby Sow, Baba Dièye, Ibrahima Ndiaye, Amy Gaye, Aliou Ndiaye, Katherine E. Battle, Joshua L. Proctor, Caitlin Bever, Fatou Fall, Ibrahima Diallo, Seynabou Gaye, Doudou Sène, Daniel L. Hartl, Dyann F. Wirth, Bronwyn MacInnis, Daouda Ndiaye, Sarah K. Volkman
Abstract
We here analyze data from the first year of an ongoing nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal. The analysis is based on 1097 samples collected at health facilities during passive malaria case detection in 2019; it provides a baseline for analyzing parasite genetic metrics as they vary over time and geographic space. The study's goal was to identify genetic metrics that were informative about transmission intensity and other aspects of transmission dynamics, focusing on measures of genetic relatedness between parasites. We found the best genetic proxy for local malaria incidence to be the proportion of polygenomic infections (those with multiple genetically distinct parasites), although this relationship broke down at low incidence. The proportion of related parasites was less correlated with incidence while local genetic diversity was uninformative. The type of relatedness could discriminate local transmission patterns: two nearby areas had similarly high fractions of relatives, but one was dominated by clones and the other by outcrossed relatives. Throughout Senegal, 58% of related parasites belonged to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci and at one novel locus, reflective of ongoing selection pressure.