Inferring Developmental Stage Composition from Gene Expression in Human Malaria

Regina Joice, Vagheesh Narasimhan, Jacqui Montgomery, Amar Bir Sidhu, Keunyoung Oh, Evan Meyer, Willythssa Pierre-Louis, Karl Seydel, Danny Milner, Kim Williamson, Roger Wiegand, Daouda Ndiaye, Johanna Daily, Dyann Wirth, Terrie Taylor, Curtis Huttenhower, Matthias Marti

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


In the current era of malaria eradication, reducing transmission is critical. Assessment of transmissibility requires tools that can accurately identify the various developmental stages of the malaria parasite, particularly those required for transmission (sexual stages). Here, we present a method for estimating relative amounts of Plasmodium falciparum asexual and sexual stages from gene expression measurements. These are modeled using constrained linear regression to characterize stage-specific expression profiles within mixed-stage populations. The resulting profiles were analyzed functionally by gene set enrichment analysis (GSEA), confirming differentially active pathways such as increased mitochondrial activity and lipid metabolism during sexual development. We validated model predictions both from microarrays and from quantitative RT-PCR (qRT-PCR) measurements, based on the expression of a small set of key transcriptional markers. This sufficient marker set was identified by backward selection from the whole genome as available from expression arrays, targeting one sentinel marker per stage. The model as learned can be applied to any new microarray or qRT-PCR transcriptional measurement. We illustrate its use in vitro in inferring changes in stage distribution following stress and drug treatment and in vivo in identifying immature and mature sexual stage carriers within patient cohorts. We believe this approach will be a valuable resource for staging lab and field samples alike and will have wide applicability in epidemiological studies of malaria transmission.

Original languageEnglish (US)
Article numbere1003392
JournalPLoS Computational Biology
Issue number12
StatePublished - Dec 2013

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics


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