| Literature DB >> 36246152 |
Wesley Wong1, Sarah Volkman1,2,3, Rachel Daniels1,2, Stephen Schaffner2, Mouhamad Sy4, Yaye Die Ndiaye4, Aida S Badiane4, Awa B Deme4, Mamadou Alpha Diallo4, Jules Gomis4, Ngayo Sy4, Daouda Ndiaye4, Dyann F Wirth1,2, Daniel L Hartl5.
Abstract
Multiple-strain (polygenomic) infections are a ubiquitous feature of Plasmodium falciparum parasite population genetics. Under simple assumptions of superinfection, polygenomic infections are hypothesized to be the result of multiple infectious bites. As a result, polygenomic infections have been used as evidence of repeat exposure and used to derive genetic metrics associated with high transmission intensity. However, not all polygenomic infections are the result of multiple infectious bites. Some result from the transmission of multiple, genetically related strains during a single infectious bite (cotransmission). Superinfection and cotransmission represent two distinct transmission processes, and distinguishing between the two could improve inferences regarding parasite transmission intensity. Here, we describe a new metric, R H, that utilizes the correlation in allelic state (heterozygosity) within polygenomic infections to estimate the likelihood that the observed complexity resulted from either superinfection or cotransmission. R H is flexible and can be applied to any type of genetic data. As a proof of concept, we used R H to quantify polygenomic relatedness and estimate cotransmission and superinfection rates from a set of 1,758 malaria infections genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode. Contrary to expectation, we found that cotransmission was responsible for a significant fraction of 43% to 53% of the polygenomic infections collected in three distinct epidemiological regions in Senegal. The prediction that polygenomic infections frequently result from cotransmission stresses the need to incorporate estimates of relatedness within polygenomic infections to ensure the accuracy of genomic epidemiology surveillance data for informing public health activities.Entities:
Keywords: cotransmission; genetic surveillance; malaria; superinfection
Year: 2022 PMID: 36246152 PMCID: PMC9552330 DOI: 10.1093/pnasnexus/pgac187
Source DB: PubMed Journal: PNAS Nexus ISSN: 2752-6542