Genetic Diversity and Drug Resistance in Malaria
One major goal of this project is to identify the genes associated with reduced response of parasites to the drug artemisinin in Senegal. Malaria infection causes almost a million deaths annually, mainly African children. The only effective drug treatments available consist of artemisinin-based combination therapies (ACTs). Recent reports indicate that ACTs are becoming less effective because genetic resistance to artemisinin has emerged, and it is generally agreed that spread of resistance would be catastrophic. Tremendous artemisinin drug pressure has been applied worldwide to a very large parasite population, and under these conditions one might expect to see resistance evolve independently in multiple locations throughout the malaria endemic world. The precedent for this model is chloroquine resistance, which evolved independently at least four times. It is therefore not surprising that our group is seeing signs of artemisinin resistance at our study site in Senegal. Our approach to identifying the genes involved is complete genome sequencing of large numbers of artemisinin-sensitive and artemisinin-resistant parasites.
A second major goal of this project is to understand the evolutionary history of the malaria parasite. Our initial studies are based on the complete genome sequences of 25 cultured P. falciparum isolates from three sites in Senegal. By fitting demographic models to the synonymous allele-frequency spectrum, we estimated that a major 60-fold population expansion of the parasite population took place approximately 15,000–30,000 years ago. Using the results on demographic history to produce a null model for coalescent simulation, we identified candidate genes under selection, including genes found previously by other methods, such as pfcrt and PfAMA1, as well as new candidate genes. Other features of the population genetics and evolution of the parasite revealed by analysis of the genome sequences include selection against GC-to-AT substitutions that offsets the large mutational bias toward AT, and the rapid decay of linkage disequilibrium across short distances.
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