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Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum

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Listed:
  • Bing Guo

    (University of Maryland School of Medicine
    University of Maryland School of Medicine)

  • Victor Borda

    (University of Maryland School of Medicine)

  • Roland Laboulaye

    (University of Maryland School of Medicine)

  • Michele D. Spring

    (Armed Forces Research Institute of Medical Sciences)

  • Mariusz Wojnarski

    (Armed Forces Research Institute of Medical Sciences)

  • Brian A. Vesely

    (Armed Forces Research Institute of Medical Sciences)

  • Joana C. Silva

    (University of Maryland School of Medicine
    University of Maryland School of Medicine
    Universidade NOVA de Lisboa (NOVA))

  • Norman C. Waters

    (Armed Forces Research Institute of Medical Sciences)

  • Timothy D. O’Connor

    (University of Maryland School of Medicine)

  • Shannon Takala-Harrison

    (University of Maryland School of Medicine)

Abstract

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population’s background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Suggested Citation

  • Bing Guo & Victor Borda & Roland Laboulaye & Michele D. Spring & Mariusz Wojnarski & Brian A. Vesely & Joana C. Silva & Norman C. Waters & Timothy D. O’Connor & Shannon Takala-Harrison, 2024. "Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46659-0
    DOI: 10.1038/s41467-024-46659-0
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