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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Language: | English |
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Nature Portfolio
2024-03-01
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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. |
first_indexed | 2024-04-24T19:55:02Z |
format | Article |
id | doaj.art-7cae15b4cbd74ccc81153c6622534127 |
institution | Directory Open Access Journal |
issn | 2041-1723 |
language | English |
last_indexed | 2024-04-24T19:55:02Z |
publishDate | 2024-03-01 |
publisher | Nature Portfolio |
record_format | Article |
series | Nature Communications |
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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