Plasmodium falciparum population structure in southwestern Africa, using whole genome sequence data

Abstract

Malaria continues to be the principal cause of morbidity and mortality in Angola, primarily due to Plasmodium falciparum (Pf) infection. Angola ranked 9th worldwide in number of malaria deaths in 2021 but the distribution of disease is remarkably heterogeneous, with provinces varying between <1% and >50% malaria prevalence. Despite malaria’s heavy toll on public health in Angola, Pf genetic diversity and demography in the country remain largely unexplored. Here we aimed to characterize malaria infections in six provinces in Angola, two each in regions where malaria transmission is hyperendemic (Cabinda, Uíge), mesoendemic stable (Luanda, Cuanza Sul) and seasonal with low prevalence (Cunene, Namibe). We hypothesize that (1) multiplicity of infection is positively correlated with transmission intensity and (2) that Pf transmission among provinces conforms to a model of isolation by distance. Finally, (3) Pf genetic diversity in Angola will be contrasted with that found in neighboring countries. To address these questions, parasite DNA was isolated from 150 dried blood spots collected in 2022, and subjected to selective whole genome amplification, and sequencing in an Illumina NovaSeq 6000 platform. The sequencing data was mapped against the P. falciparum reference genome, single nucleotide polymorphisms (SNPs) were identified according to best practices, and joint SNPs calling was done together with WGS data from several hundred publicly available Pf samples from East, West and Central Africa, as well as Brazil and French Guiana. A Principal Component Analysis (PCA) done on the SNP calls revealed that Pf samples from Angola cluster with others from Central Africa. Admixture analyses are still ongoing, to determine the extent to which the ancestry of the Angolan Pf population differs from those of neighboring countries. In addition, average multiplicity of infection and overall nucleotide diversity will be estimated for each province, and population differentiation between provinces will be estimated with Wright’s fixation index (FST). To test isolation by distance, FST will be compared with geographic distance using a Mantel test.