Evidence map›Paper›PMID 38509066›Full record

ArticleNature communications2024

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

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

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Article
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  7. Towards an evolutionary baseline model ofbioRxiv : the preprint server for biology · 2025
    Article
  8. Article
  9. Article
  10. Identity-by-descent segments in large samples.Theoretical population biology · 2025
    Article
  11. Article
  12. Article
  13. Parasitology · 2025
    Article
  14. Article
  15. Fast simulation of identity-by-descent segments.Bulletin of mathematical biology · 2025
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Fast simulation of identity-by-descent segments.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Bing GuoInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.ORCID 0000-0002-3998-5981
Victor BordaInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.ORCID 0000-0003-3209-3961
Roland LaboulayeInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
Michele D SpringArmed Forces Research Institute of Medical Sciences, Bangkok, Thailand.
Mariusz WojnarskiArmed Forces Research Institute of Medical Sciences, Bangkok, Thailand.
Brian A VeselyArmed Forces Research Institute of Medical Sciences, Bangkok, Thailand.ORCID 0009-0009-5708-5782
Joana C SilvaInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.ORCID 0000-0001-6502-7026
Norman C WatersArmed Forces Research Institute of Medical Sciences, Bangkok, Thailand.
Timothy D O'ConnorInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. timothydoconnor@gmail.com.ORCID 0000-0002-0276-1896
Shannon Takala-HarrisonCenter for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA. STakala@som.umaryland.edu.ORCID 0000-0003-4674-8500

Funding

Genomic and geospatial analyses of malaria parasite migration to inform eliminationR01AI145852 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI HARRISON, SHANNON TAKALA, O'CONNOR, TIMOTHY DAVID · 2020 to 2024
$3.7M
Identification and validation of molecular markers of piperaquine resistanceR01AI125579 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI HARRISON, SHANNON TAKALA · 2017 to 2021
$1.6M
NIAID NIH HHS R01 AI125579NIAID NIH HHS R01 AI145852Wellcome Trust
6 · The paper itself

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.

Indexed as

AntimalarialsMalaria, FalciparumDemographyHumansPlasmodium falciparumSelection BiasAntimalarials

Identifiers

PMID38509066
PMCPMC10954658

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.