Abstract
The diversity in the Plasmodium falciparum genome can be used to explore parasite population dynamics, with practical applications to malaria control. The ability to identify the geographic origin and trace the migratory patterns of parasites with clinically important phenotypes such as drug resistance is particularly relevant. With increasing single-nucleotide polymorphism (SNP) discovery from ongoing Plasmodium genome sequencing projects, a demand for high SNP and sample throughput genotyping platforms for large-scale population genetic studies is required. Low parasitaemias and multiple clone infections present a number of challenges to genotyping P. falciparum. We addressed some of these issues using a custom 384-SNP Illumina GoldenGate assay on P. falciparum DNA from laboratory clones (long-term cultured adapted parasite clones), short-term cultured parasite isolates and clinical (non-cultured isolates) samples from East and West Africa, Southeast Asia and Oceania. Eighty percent of the SNPs (n = 306) produced reliable genotype calls on samples containing as little as 2 ng of total genomic DNA and on whole genome amplified DNA. Analysis of artificial mixtures of laboratory clones demonstrated high genotype calling specificity and moderate sensitivity to call minor frequency alleles. Clear resolution of geographically distinct populations was demonstrated using Principal Components Analysis (PCA), and global patterns of population genetic diversity were consistent with previous reports. These results validate the utility of the platform in performing population genetic studies of P. falciparum.
Highlights
Plasmodium falciparum continues to impose a substantial public health burden across the globe, causing an estimated 500 million clinical cases and 1–2 million deaths each year [1]
Subsets of genetic polymorphisms can be used to explore the dynamics of parasites with important phenotypes such as drug resistance, with practical applications to malaria control and elimination
To successfully implement and monitor malaria control and elimination strategies, we need a greater understanding of the dynamics of parasite gene flow between populations and effective and rapid tools for tracing important parasite genetic traits such as anti-malarial drug resistance
Summary
Plasmodium falciparum continues to impose a substantial public health burden across the globe, causing an estimated 500 million clinical cases and 1–2 million deaths each year [1]. The lack of an effective antimalarial vaccine and the emergence and spread of parasite resistance to affordable antimalarial drugs such as chloroquine and sulfadoxine-pyrimethamine, have greatly contributed to the public health burden of malaria [2]. Key to the success of malaria control strategies is an understanding of the parasite genetic diversity and dynamics/ exchange of gene flow between human populations. With this knowledge, effective spatial and temporal boundaries for intervention can be implemented. The ability to identify the geographic origin and monitor the migration patterns of clinically important parasite genetic traits should greatly facilitate control efforts, with important applications for drug resistance surveillance. Molecular barcodes have already been used successfully by Daniels and colleagues [4] to distinguish parasite clones from one another
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