The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria
Abstract
Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Furthermore, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD.
Data availability
Metadata on samples is available from ftp://ngs.sanger.ac.uk/production/pf3k/release_5/pf3k_release_5_metadata_20170804.txt.gz. Sequence data (aligned to Plasmodium falciparum strain 3D7 v3.1 reference genome sequences, for details see ftp://ftp.sanger.ac.uk/pub/project/pathogens/gff3/2015-08/Pfalciparum.genome.fasta.gz) is available from ftp://ngs.sanger.ac.uk/production/pf3k/release_5/5.1/. Diagnostic plots for the deconvolution of all samples can be found at https://github.com/mcveanlab/mixedIBD-Supplement and deconvolved haplotypes can be accessed at ftp://ngs.sanger.ac.uk/production/pf3k/technical_working/release_5/mixedIBD_paper_haplotypes/. Code implementing the algorithms described in this paper, DEploidIBD, is available at https://github.com/mcveanlab/DEploid.
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The Pf3k Project (2016): pilot data release 5Wellcome Trust Sanger public ftp site, 5.1 Data.
Article and author information
Author details
Funding
Wellcome (206194)
- Jacob Almagro-Garcia
Wellcome (090770)
- Jacob Almagro-Garcia
- Richard D. Pearson
- Roberto Amato
- Alistair Miles
- Dominic Kwiatkowski
Wellcome (100956/Z/13/Z)
- Sha Joe Zhu
- Gil McVean
Li Ka Shing Foundation (NA)
- Gil McVean
Wellcome (204911)
- Jacob Almagro-Garcia
- Richard D. Pearson
- Roberto Amato
- Alistair Miles
- Dominic Kwiatkowski
Medical Research Council (G0600718)
- Jacob Almagro-Garcia
- Richard D. Pearson
- Roberto Amato
- Alistair Miles
- Dominic Kwiatkowski
Department for International Development (M006212)
- Jacob Almagro-Garcia
- Richard D. Pearson
- Roberto Amato
- Alistair Miles
- Dominic Kwiatkowski
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Zhu et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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