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 FWS 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=5.92x10(-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.

Characterization of Within-Host Plasmodium falciparum Diversity Using Next-Generation Sequence Data

MANGANO, VALENTINA;
2012-01-01

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 FWS 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=5.92x10(-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.
2012
Sarah, Auburn; Susana, Campino; Olivo, Miotto; Abdoulaye A., Djimde; Issaka, Zongo; Magnus, Manske; Gareth, Maslen; Mangano, Valentina; Daniel, Alcock; Bronwyn, Macinnis; Kirk A., Rockett; Taane G., Clark; Ogobara K., Doumbo; Jean Bosco, Ouedraogo; Dominic P., Kwiatkowski
File in questo prodotto:
File Dimensione Formato  
Mangano_839783.pdf

accesso aperto

Tipologia: Versione finale editoriale
Licenza: Creative commons
Dimensione 169.77 kB
Formato Adobe PDF
169.77 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/839783
Citazioni
  • ???jsp.display-item.citation.pmc??? 62
  • Scopus 79
  • ???jsp.display-item.citation.isi??? 76
social impact