Abstract

BackgroundAlthough Plasmodium vivax contributes to almost half of all malaria cases outside Africa, it has been relatively neglected compared to the more deadly P. falciparum. It is known that P. vivax populations possess high genetic diversity, differing geographically potentially due to different vector species, host genetics and environmental factors.ResultsWe analysed the high-quality genomic data for 46 P. vivax isolates spanning 10 countries across 4 continents. Using population genetic methods we identified hotspots of selection pressure, including the previously reported MRP1 and DHPS genes, both putative drug resistance loci. Extra copies and deletions in the promoter region of another drug resistance candidate, MDR1 gene, and duplications in the Duffy binding protein gene (PvDBP) potentially involved in erythrocyte invasion, were also identified. For surveillance applications, continental-informative markers were found in putative drug resistance loci, and we show that organellar polymorphisms could classify P. vivax populations across continents and differentiate between Plasmodia spp.ConclusionsThis study has shown that genomic diversity that lies within and between P. vivax populations can be used to elucidate potential drug resistance and invasion mechanisms, as well as facilitate the molecular barcoding of the parasite for surveillance applications.

Highlights

  • Plasmodium vivax contributes to almost half of all malaria cases outside Africa, it has been relatively neglected compared to the more deadly P. falciparum

  • Using population genetic methods we identified hotspots of selection pressure, including the previously reported MRP1 and DHPS genes, both putative drug resistance loci

  • Continental-informative markers were found in putative drug resistance loci, and we show that organellar polymorphisms could classify P. vivax populations across continents and differentiate between Plasmodia spp

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Summary

Methods

Available whole genome sequence data for 74 P. vivax samples were gathered from multiple sources, and included reference strains (India VII, Mauritania X, North Korea II, Brazil I, Sal-1 from El Salvador (see [2])), field and clinical isolates (Cambodia (n = 3) [13], Thailand (n = 39) [13], Madagascar (n = 3) [2,17], Colombia (n = 8) [14] and Peru (n = 11) [7,15]) and clinical samples from travellers (to Papua Indonesia (n = 2) [13], India (n = 2) [13], and. The final high quality dataset consisted of 46 (62.2%) isolates (Thailand 22, Southeast Asia 24, South America 11; other 11; S1 Table) and 219,288 SNPs, and used as the basis of population genetic analyses. Regions identified as CNVs were inspected visually and assessed using de novo assembly methods [20]

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