Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. 1,2 Here we describe methods for large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short term culture. Analysis of 86,158 exonic SNPs that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome.

We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10 −7 to P = 4 × 10 −14 , with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations.The malaria parasite Plasmodium falciparum kills on the order of a million African children each year 1 , and this is a small fraction of the number of infected individuals in the population [1][2][3] . In communities where everyone is repeatedly infected with P. falciparum, host genetic factors account for ~25% of the risk of severe malaria, that is, life-threatening forms of the disease 3 . The strongest known determinant of risk, hemoglobin S (HbS), accounts for 2% of the total variation, implying that only a small fraction of genetic resistance factors have so far been discovered 3 . Identifying the genetic basis of protective immunity against severe malaria may provide important insights for vaccine development.Here we examine the possibility of approaching this problem by genome-wide association (GWA) analysis. There are many unsolved methodological questions about how to conduct an effective GWA study in Africa 4 . High levels of ethnic diversity may result in false-positive associations owing to population structure. Variations in haplotype structure between different ethnic groups may reduce power to detect GWA signals, particularly when data are amalgamated across multiple study sites. Low LD implies the need for denser genotyping arrays than are currently available: a crude estimate is that an African GWA study with 1.5 million SNPs would have approximately the same statistical power as a European study with Jallow et al.Page 2Nat Genet. Author manuscript; available in PMC 2010 September 21. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript 0.6 million SNPs5, but this is based on HapMap data from a single ethnic group and a larger number of SNPs may be needed to achieve adequate power across different ethnic groups.We carried out an initial GWA study in Gambian children that explores these methodological questions. Genotyping of ~500,000 SNPs was conducted on 1,060 cases of severe malaria and 1...

The sustainability of malaria control in Africa is threatened by the rise of insecticide resistance in Anopheles mosquitoes that transmit the disease1. To gain a deeper understanding of how mosquito populations are evolving, we sequenced the genomes of 765 specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa, identifying over 50 million single nucleotide polymorphisms within the accessible genome. These data revealed complex population structure and patterns of gene flow, with evidence of ancient expansions, recent bottlenecks, and local variation in effective population size. Strong signals of recent selection were observed in insecticide resistance genes, with multiple sweeps spreading over large geographical distances and between species. The design of novel tools for mosquito control using gene drive will need to take account of high levels of genetic diversity in natural mosquito populations.

The malaria parasite Plasmodium falciparum invades human red blood cells via interactions between host and parasite surface proteins. By analyzing genome sequence data from human populations, including 1269 individuals from sub-Saharan Africa, we identify a diverse array of large copy number variants affecting the host invasion receptor genes GYPA and GYPB. We find that a nearby association with severe malaria is explained by a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which encode a serologically distinct blood group antigen known as Dantu. This variant reduces the risk of severe malaria by 40% and has recently risen in frequency in parts of Kenya, yet it appears to be absent from west Africa. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.