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.

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BackgroundCurrent understanding of the spatial epidemiology and geographical distribution of Plasmodium vivax is far less developed than that for P. falciparum, representing a barrier to rational strategies for control and elimination. Here we present the first systematic effort to map the global endemicity of this hitherto neglected parasite.Methodology and FindingsWe first updated to the year 2010 our earlier estimate of the geographical limits of P. vivax transmission. Within areas of stable transmission, an assembly of 9,970 geopositioned P. vivax parasite rate (PvPR) surveys collected from 1985 to 2010 were used with a spatiotemporal Bayesian model-based geostatistical approach to estimate endemicity age-standardised to the 1–99 year age range (PvPR1–99) within every 5×5 km resolution grid square. The model incorporated data on Duffy negative phenotype frequency to suppress endemicity predictions, particularly in Africa. Endemicity was predicted within a relatively narrow range throughout the endemic world, with the point estimate rarely exceeding 7% PvPR1–99. The Americas contributed 22% of the global area at risk of P. vivax transmission, but high endemic areas were generally sparsely populated and the region contributed only 6% of the 2.5 billion people at risk (PAR) globally. In Africa, Duffy negativity meant stable transmission was constrained to Madagascar and parts of the Horn, contributing 3.5% of global PAR. Central Asia was home to 82% of global PAR with important high endemic areas coinciding with dense populations particularly in India and Myanmar. South East Asia contained areas of the highest endemicity in Indonesia and Papua New Guinea and contributed 9% of global PAR.Conclusions and SignificanceThis detailed depiction of spatially varying endemicity is intended to contribute to a much-needed paradigm shift towards geographically stratified and evidence-based planning for P. vivax control and elimination.

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...

BackgroundPlanning and evaluating malaria control strategies relies on accurate definition of parasite prevalence in the population. A large proportion of asymptomatic parasite infections can only be identified by surveillance with molecular methods, yet these infections also contribute to onward transmission to mosquitoes. The sensitivity of molecular detection by PCR is limited by the abundance of the target sequence in a DNA sample; thus, detection becomes imperfect at low densities. We aimed to increase PCR diagnostic sensitivity by targeting multi-copy genomic sequences for reliable detection of low-density infections, and investigated the impact of these PCR assays on community prevalence data.Methods and FindingsTwo quantitative PCR (qPCR) assays were developed for ultra-sensitive detection of Plasmodium falciparum, targeting the high-copy telomere-associated repetitive element 2 (TARE-2, ∼250 copies/genome) and the var gene acidic terminal sequence (varATS, 59 copies/genome). Our assays reached a limit of detection of 0.03 to 0.15 parasites/μl blood and were 10× more sensitive than standard 18S rRNA qPCR. In a population cross-sectional study in Tanzania, 295/498 samples tested positive using ultra-sensitive assays. Light microscopy missed 169 infections (57%). 18S rRNA qPCR failed to identify 48 infections (16%), of which 40% carried gametocytes detected by pfs25 quantitative reverse-transcription PCR. To judge the suitability of the TARE-2 and varATS assays for high-throughput screens, their performance was tested on sample pools. Both ultra-sensitive assays correctly detected all pools containing one low-density P. falciparum–positive sample, which went undetected by 18S rRNA qPCR, among nine negatives. TARE-2 and varATS qPCRs improve estimates of prevalence rates, yet other infections might still remain undetected when absent in the limited blood volume sampled.ConclusionsMeasured malaria prevalence in communities is largely determined by the sensitivity of the diagnostic tool used. Even when applying standard molecular diagnostics, prevalence in our study population was underestimated by 8% compared to the new assays. Our findings highlight the need for highly sensitive tools such as TARE-2 and varATS qPCR in community surveillance and for monitoring interventions to better describe malaria epidemiology and inform malaria elimination efforts.

The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for malaria elimination. To characterise the genetic diversity of this parasite within individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region, and analysed data on >300,000 SNPs and 9 regions of the genome with large copy number variations. Individual infections showed complex patterns of genetic structure, with variation not only in the number of dominant clones but also in their level of relatedness and inbreeding. At the population level, we observed strong signals of recent evolutionary selection both in known drug resistance genes and at novel loci, and these varied markedly between geographical locations. These findings reveal a dynamic landscape of local evolutionary adaptation in P. vivax populations, and provide a foundation for genomic surveillance to guide effective strategies for control and elimination.

Carriage and density of gametocytes, the transmission stages of malaria parasites, are determined for predicting the infectiousness of humans to mosquitoes. This measure is used for evaluating interventions that aim at reducing malaria transmission. Gametocytes need to be detected by amplification of stage-specific transcripts, which requires RNA-preserving blood sampling. For simultaneous, highly sensitive quantification of both, blood stages and gametocytes, we have compared and optimized different strategies for field and laboratory procedures in a cross sectional survey in 315 5-9 yr old children from Papua New Guinea. qRT-PCR was performed for gametocyte markers pfs25 and pvs25, Plasmodium species prevalence was determined by targeting both, 18S rRNA genes and transcripts. RNA-based parasite detection resulted in a P. falciparum positivity of 24.1%; of these 40.8% carried gametocytes. P. vivax positivity was 38.4%, with 38.0% of these carrying gametocytes. Sensitivity of DNA-based parasite detection was substantially lower with 14.1% for P. falciparum and 19.6% for P. vivax. Using the lower DNA-based prevalence of asexual stages as a denominator increased the percentage of gametocyte-positive infections to 59.1% for P. falciparum and 52.4% for P. vivax. For studies requiring highly sensitive and simultaneous quantification of sexual and asexual parasite stages, 18S rRNA transcript-based detection saves efforts and costs. RNA-based positivity is considerably higher than other methods. On the other hand, DNA-based parasite quantification is robust and permits comparison with other globally generated molecular prevalence data. Molecular monitoring of low density asexual and sexual parasitaemia will support the evaluation of effects of up-scaled antimalarial intervention programs and can also inform about small scale spatial variability in transmission intensity.

Substantial evidence indicates that antibodies to