TY - JOUR TI - The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria AU - Zhu, Sha Joe AU - Hendry, Jason A AU - Almagro-Garcia, Jacob AU - Pearson, Richard D AU - Amato, Roberto AU - Miles, Alistair AU - Weiss, Daniel J AU - Lucas, Tim CD AU - Nguyen, Michele AU - Gething, Peter W AU - Kwiatkowski, Dominic AU - McVean, Gil A2 - Franco, Eduardo A2 - Daniels, Rachel A2 - Greenhouse, Bryan A2 - Schaffner, Steve VL - 8 PY - 2019 DA - 2019/07/12 SP - e40845 C1 - eLife 2019;8:e40845 DO - 10.7554/eLife.40845 UR - https://doi.org/10.7554/eLife.40845 AB - 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. KW - malaria KW - genome KW - epidemiology KW - relatedness JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -