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Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission
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 stra...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777656/ https://www.ncbi.nlm.nih.gov/pubmed/29315306 http://dx.doi.org/10.1371/journal.pcbi.1005923 |
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author | Wong, Wesley Wenger, Edward A. Hartl, Daniel L. Wirth, Dyann F. |
author_facet | Wong, Wesley Wenger, Edward A. Hartl, Daniel L. Wirth, Dyann F. |
author_sort | Wong, Wesley |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5777656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57776562018-02-05 Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission Wong, Wesley Wenger, Edward A. Hartl, Daniel L. Wirth, Dyann F. PLoS Comput Biol Research Article 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. Public Library of Science 2018-01-09 /pmc/articles/PMC5777656/ /pubmed/29315306 http://dx.doi.org/10.1371/journal.pcbi.1005923 Text en © 2018 Wong et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wong, Wesley Wenger, Edward A. Hartl, Daniel L. Wirth, Dyann F. Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission |
title | Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission |
title_full | Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission |
title_fullStr | Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission |
title_full_unstemmed | Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission |
title_short | Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission |
title_sort | modeling the genetic relatedness of plasmodium falciparum parasites following meiotic recombination and cotransmission |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777656/ https://www.ncbi.nlm.nih.gov/pubmed/29315306 http://dx.doi.org/10.1371/journal.pcbi.1005923 |
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