Selective whole genome amplification of Plasmodium malariae DNA from clinical samples reveals insights into population structure

Abstract

AbstractThe genomic diversity of Plasmodium malariae malaria parasites is understudied, partly because infected individuals tend to present with low parasite densities, leading to difficulties in obtaining sufficient parasite DNA for genome analysis. Selective whole genome amplification (SWGA) increases the relative levels of pathogen DNA in a clinical sample, but has not been adapted for P. malariae parasites. Here we design customized SWGA primers which successfully amplify P. malariae DNA extracted directly from unprocessed clinical blood samples obtained from patients with P. malariae-mono-infections from six countries, and further test the efficacy of SWGA on mixed infections with other Plasmodium spp. SWGA enables the successful whole genome sequencing of samples with low parasite density (i.e. one sample with a parasitaemia of 0.0064% resulted in 44% of the genome covered by ≥ 5 reads), leading to an average 14-fold increase in genome coverage when compared to unamplified samples. We identify a total of 868,476 genome-wide SNPs, of which 194,709 are unique across 18 high-quality isolates. After exclusion of the hypervariable subtelomeric regions, a high-quality core subset of 29,899 unique SNPs is defined. Population genetic analysis suggests that P. malariae parasites display clear geographical separation by continent. Further, SWGA successfully amplifies genetic regions of interest such as orthologs of P. falciparum drug resistance-associated loci (Pfdhfr, Pfdhps, Pfcrt, Pfk13 and Pfmdr1), and several non-synonymous SNPs were detected in these genes. In conclusion, we have established a robust SWGA approach that can assist whole genome sequencing of P. malariae, and thereby facilitate the implementation of much-needed large-scale multi-population genomic studies of this neglected malaria parasite. As demonstrated in other Plasmodia, such genetic diversity studies can provide insights into the biology underlying the disease and inform malaria surveillance and control measures.