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

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 I...

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Main Authors: 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
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-46659-0
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author 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
author_facet 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
author_sort Bing Guo
collection DOAJ
description 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.
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spelling doaj.art-7cae15b4cbd74ccc81153c66225341272024-03-24T12:25:05ZengNature PortfolioNature Communications2041-17232024-03-0115111410.1038/s41467-024-46659-0Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparumBing Guo0Victor Borda1Roland Laboulaye2Michele D. Spring3Mariusz Wojnarski4Brian A. Vesely5Joana C. Silva6Norman C. Waters7Timothy D. O’Connor8Shannon Takala-Harrison9Institute for Genome Sciences, University of Maryland School of MedicineInstitute for Genome Sciences, University of Maryland School of MedicineInstitute for Genome Sciences, University of Maryland School of MedicineArmed Forces Research Institute of Medical SciencesArmed Forces Research Institute of Medical SciencesArmed Forces Research Institute of Medical SciencesInstitute for Genome Sciences, University of Maryland School of MedicineArmed Forces Research Institute of Medical SciencesInstitute for Genome Sciences, University of Maryland School of MedicineCenter for Vaccine Development and Global Health, University of Maryland School of MedicineAbstract 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.https://doi.org/10.1038/s41467-024-46659-0
spellingShingle 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
Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum
Nature Communications
title Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum
title_full Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum
title_fullStr Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum
title_full_unstemmed Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum
title_short Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum
title_sort strong positive selection biases identity by descent based inferences of recent demography and population structure in plasmodium falciparum
url https://doi.org/10.1038/s41467-024-46659-0
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