Distinguishing gene flow between malaria parasite populations

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 evaluates numerically the ability to distinguish different levels of gene flow between malaria populations, using different amounts of real and simulated data, where data are simulated using parameters that approximate different epidemiological conditions. Specifically, using Plasmodium falciparum whole genome sequence data and sequence data simulated for a metapopulation with different migration rates and effective population sizes, we compare two estimators of gene flow, explore the number of genetic markers and number of individuals required to reliably rank highly connected locations, and describe how these thresholds change given different effective population sizes and migration rates. Our results have implications for the design and implementation of malaria genomic surveillance efforts.

Measurably recombining malaria parasites

“…Analyses of allele frequencies within and across populations feature in many population genetic analyses of malaria parasites. Allele frequencies change with selection (e.g., from drug gene-flow (e.g., due to the mobility of infected hosts), or genetic (particularly in small populations), typically at a rate slower than that which is epidemiologically relevant on an individual level [22,70]. That said, small populations with limited effective recombination, allele frequencies may vary at a rate equivalent to recombination (e.g., [71]).…”

“…from drug pressure), gene-flow (e.g. due to the mobility of infected hosts) or genetic drift (particularly in small populations), typically at a rate slower than that which is epidemiologically relevant on an individual level [ 22 , 70 ]. That said, in small populations with limited effective recombination, allele frequencies may vary at a rate equivalent to recombination (e.g.…”