ArticlePLoS computational biology2018
Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Molecular surveillance of multiplicity of infection, haplotype frequencies, and prevalence in infectious diseases.PLoS computational biology · 2026Article
- Comparison of techniques and markers to distinguish Plasmodium falciparum recrudescence from new infection in Rwanda.Scientific reports · 2026Article
- Malaria-MOI: A flexible and scalable tool for predicting multiplicity of infection in malaria parasites.Genome medicine · 2026Article
- Genetic metrics decodeFrontiers in genetics · 2026Article
- Systematic bias in malaria parasite relatedness estimation.G3 (Bethesda, Md.) · 2025Article
- MalKinID: A classification model for identifying malaria parasite genealogical relationships using identity-by-descent.Genetics · 2025Article
- MOIRE: a software package for the estimation of allele frequencies and effective multiplicity of infection from polyallelic data.Bioinformatics (Oxford, England) · 2024Article
- MalKinID: A Likelihood-Based Model for Identifying Malaria Parasite Genealogical Relationships Using Identity-by-Descent.bioRxiv : the preprint server for biology · 2024Article
- Article
- Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of anti-malarial drug resistance.bioRxiv : the preprint server for biology · 2023Article
- Multiplexed ddPCR-amplicon sequencing reveals isolated Plasmodium falciparum populations amenable to local elimination in Zanzibar, Tanzania.Nature communications · 2023Article
- coiaf: Directly estimating complexity of infection with allele frequencies.PLoS computational biology · 2023Article
- Measurably recombining malaria parasites.Trends in parasitology · 2023Review
- Neutral vs. non-neutral genetic footprints of Plasmodium falciparum multiclonal infections.PLoS computational biology · 2023Article
- Article
- Declines in prevalence alter the optimal level of sexual investment for the malaria parasiteProceedings of the National Academy of Sciences of the United States of America · 2022Article
- Genomic epidemiological models describe pathogen evolution across fitness valleys.Science advances · 2022Article
- A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data.Frontiers in epidemiology · 2022Article
- The many definitions of multiplicity of infection.Frontiers in epidemiology · 2022Article
- Evolutionary genetics of malaria.Frontiers in genetics · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
Unlike in most pathogens, multiple-strain (polygenomic) infections of P. falciparum are frequently composed of genetic siblings. These genetic siblings are the result of sexual reproduction and can coinfect the same host when cotransmitted by the same mosquito. The degree with which coinfecting strains are related varies among infections and populations. Because sexual recombination occurs within the mosquito, the relatedness of cotransmitted strains could depend on transmission dynamics, but little is actually known of the factors that influence the relatedness of cotransmitted strains. Part of the uncertainty stems from an incomplete understanding of how within-host and within-vector dynamics affect cotransmission. Cotransmission is difficult to examine experimentally but can be explored using a computational model. We developed a malaria transmission model that simulates sexual reproduction in order to understand what determines the relatedness of cotransmitted strains. This study highlights how the relatedness of cotransmitted strains depends on both within-host and within-vector dynamics including the complexity of infection. We also used our transmission model to analyze the genetic relatedness of polygenomic infections following a series of multiple transmission events and examined the effects of superinfection. Understanding the factors that influence the relatedness of cotransmitted strains could lead to a better understanding of the population-genetic correlates of transmission and therefore be important for public health.
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