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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/744
Title: Characterization of within-host Plasmodium falciparum diversity using next-generation sequence data.
Authors: Auburn, Sarah
Campino, Susana
Miotto, Olivo
Djimde, Abdoulaye A.
Zongo, Issaka
Manske, Magnus
Maslen, Gareth
Mangano, Valentina
Alcock, Daniel
MacInnis, Bronwyn
Rockett, Kirk A.
Clark, Taane G.
Doumbo, Ogobara K.
Ouédraogo, Jean Bosco
Kwiatkowski, Dominic P.
Mahidol University. Faculty of Tropical Medicine. Mahidol-Oxford Research Unit.
Auburn, Sarah
Keywords: Plasmodium falciparum;Open Access article
Issue Date: 2012
Citation: Auburn S, Campino S, Miotto O, Djimde AA, Zongo I, Manske M, et al. Characterization of within-host Plasmodium falciparum diversity using next-generation sequence data. PLoS One. 2012;7(2):e32891.
Abstract: Our understanding of the composition of multi-clonal malarial infections and the epidemiological factors which shape their diversity remain poorly understood. Traditionally within-host diversity has been defined in terms of the multiplicity of infection (MOI) derived by PCR-based genotyping. Massively parallel, single molecule sequencing technologies now enable individual read counts to be derived on genome-wide datasets facilitating the development of new statistical approaches to describe within-host diversity. In this class of measures the F(WS) metric characterizes within-host diversity and its relationship to population level diversity. Utilizing P. falciparum field isolates from patients in West Africa we here explore the relationship between the traditional MOI and F(WS) approaches. F(WS) statistics were derived from read count data at 86,158 SNPs in 64 samples sequenced on the Illumina GA platform. MOI estimates were derived by PCR at the msp-1 and -2 loci. Significant correlations were observed between the two measures, particularly with the msp-1 locus (P = 5.92×10(-5)). The F(WS) metric should be more robust than the PCR-based approach owing to reduced sensitivity to potential locus-specific artifacts. Furthermore the F(WS) metric captures information on a range of parameters which influence out-crossing risk including the number of clones (MOI), their relative proportions and genetic divergence. This approach should provide novel insights into the factors which correlate with, and shape within-host diversity.
URI: http://repository.li.mahidol.ac.th/dspace/handle/123456789/744
metadata.dc.identifier.url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3290604/pdf/pone.0032891.pdf
ISSN: 1932-6203 (electronic)
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