Abstract
Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report examines the use of population-level summaries of genetic divergence (FST) and relatedness (identity-by-descent) to distinguish levels of gene flow between malaria populations, focused on field-relevant questions about data size, sampling, and interpretability of observations from genomic surveillance studies. To do this, we use P. falciparum whole genome sequence data and simulated sequence data approximating malaria populations evolving under different current and historical epidemiological conditions. We employ mobile-phone associated mobility data to estimate parasite migration rates over different spatial scales and use this to inform our analysis. This analysis underscores the complementary nature of divergence- and relatedness-based metrics for distinguishing gene flow over different temporal and spatial scales and characterizes the data requirements for using these metrics in different contexts. Our results have implications for the design and implementation of malaria genomic surveillance studies.
Highlights
Measuring the extent to which malaria parasite populations are linked across different geographic locations (“connectivity”) can provide important guidance for the design and implementation of malaria control interventions
We explore how changes in population size and migration rates over time influence identical by descent (IBD)- and FST-based estimates of gene flow. We examine populations that have undergone recent reduction in their effective population sizes or changes in relative parasite migration rates between locations, given the direct relevance of this scenario to real-world malaria populations
We restricted our analysis to samples from the Greater Mekong Subregion (GMS), excluding more widely divergent P. falciparum populations from Sub-Saharan Africa and Bangladesh that are less relevant to the context of our analysis, and including only individual sequences from clinical cases or survey participants
Summary
Measuring the extent to which malaria parasite populations are linked across different geographic locations (“connectivity”) can provide important guidance for the design and implementation of malaria control interventions. Other recent work has focused on estimating the probability that a pair of genomes are identical by descent (IBD) at a particular locus [4] and using population-level summaries of IBD estimates to assess gene flow between malaria populations [5]. These relatedness-based approaches have uncovered spatial structure in malaria populations at small, local scales, where conventional methods using differentiation-based estimators (including the fixation index, FST) fail to identify population structure [5]. IBD-based measures capture variation due to recombination and as such may be well suited for measuring more recent gene flow between malaria populations (in which mutation rates are relatively slow, but variation due to recombination can accrue more quickly)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
