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Population genetic analysis of Plasmodium falciparum parasites using a customized Illumina GoldenGate genotyping assay
Authors:Campino Susana  Auburn Sarah  Kivinen Katja  Zongo Issaka  Ouedraogo Jean-Bosco  Mangano Valentina  Djimde Abdoulaye  Doumbo Ogobara K  Kiara Steven M  Nzila Alexis  Borrmann Steffen  Marsh Kevin  Michon Pascal  Mueller Ivo  Siba Peter  Jiang Hongying  Su Xin-Zhuan  Amaratunga Chanaki  Socheat Duong  Fairhurst Rick M  Imwong Mallika  Anderson Timothy  Nosten François  White Nicholas J  Gwilliam Rhian  Deloukas Panos  MacInnis Bronwyn  Newbold Christopher I  Rockett Kirk  Clark Taane G  Kwiatkowski Dominic P
Institution:Wellcome Trust Sanger Institute, Hinxton, United Kingdom. sc11@sanger.ac.uk
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.
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