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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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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1004408
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资源简介:
Malaria genomic surveillance often estimates parasite genetic relatednessusing metrics such as Identity-By-Decent (IBD). However, strong positiveselection stemming from antimalarial drug resistance or other interventions maybias IBD-based estimates of parasite population demography. In this study, weinvestigated the extent of such bias and potential correction strategies toallow more accurate inference of parasite population structure and effectivepopulation size. We used simulations and a true IBD inference algorithm toevaluate the effects of positive selection on IBD-based inferences and validatedour findings using empirical datasets from different malaria transmissionsettings. Our results showed that selection distorts IBD distributions, leadingto underestimated Ne and blurred population structure. Removing IBD peak regionspartially restored the accuracy of IBD-based inferences, but this effectdepended on background genetic relatedness in the population. We recommendselection correction for parasite populations undergoing strong, recent positiveselection, particularly in high transmission settings.
创建时间:
2023-08-10
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