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Glycophorins are the most abundant sialoglycoproteins on the surface of human erythrocyte membranes. Genetic variation in glycophorin region of human chromosome 4 (containing GYPA, GYPB, and GYPE genes) is of interest because the gene products serve as receptors for pathogens of major public health interest, including Plasmodium sp., Babesia sp., Influenza virus, Vibrio cholerae El Tor Hemolysin, and Escherichia coli. A large structural rearrangement and hybrid glycophorin variant, known as Dantu, which was identified in East African populations, has been linked with a 40% reduction in risk for severe malaria. Apart from Dantu, other large structural variants exist, with the most common being deletion of the whole GYPB gene and its surrounding region, resulting in multiple different deletion forms. In West Africa particularly, these deletions are estimated to account for between 5 and 15% of the variation in different populations, mostly attributed to the forms known as DEL1 and DEL2. Due to the lack of specific variant assays, little is known of the distribution of these variants. Here, we report a modification of a previous GYPB DEL1 assay and the development of a novel GYPB DEL2 assay as high-throughput PCR-RFLP assays, as well as the identification of the crossover/breakpoint for GYPB DEL2. Using 393 samples from three study sites in Ghana as well as samples from HapMap and 1000 G projects for validation, we show that our assays are sensitive and reliable for genotyping GYPB DEL1 and DEL2. To the best of our knowledge, this is the first report of such high-throughput genotyping assays by PCR-RFLP for identifying specific GYPB deletion types in populations. These assays will enable better identification of GYPB deletions for large genetic association studies and functional experiments to understand the role of this gene cluster region in susceptibility to malaria and other diseases.

Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.

Background: The -α3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study, we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha (HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.

Author(s): Jacob, Christopher G; Thuy-Nhien, Nguyen; Mayxay, Mayfong; Maude, Richard J; Quang, Huynh Hong; Hongvanthong, Bouasy; Vanisaveth, Viengxay; Ngo Duc, Thang; Rekol, Huy; van der Pluijm, Rob; von Seidlein, Lorenz; Fairhurst, Rick; Nosten, Francois; Hossain, Md Amir; Park, Naomi; Goodwin, Scott; Ringwald, Pascal; Chindavongsa, Keobouphaphone; Newton, Paul; Ashley, Elizabeth; Phalivong, Sonexay; Maude, Rapeephan; Leang, Rithea; Huch, Cheah; Dong, Le Thanh; Nguyen, Kim-Tuyen; Nhat, Tran Minh; Hien, Tran Tinh; Nguyen, Hoa; Zdrojewski, Nicole; Canavati, Sara; Sayeed, Abdullah Abu; Uddin, Didar; Buckee, Caroline; Fanello, Caterina I; Onyamboko, Marie; Peto, Thomas; Tripura, Rupam; Amaratunga, Chanaki; Myint Thu, Aung; Delmas, Gilles; Landier, Jordi; Parker, Daniel M; Chau, Nguyen Hoang; Lek, Dysoley; Suon, Seila; Callery, James; Jittamala, Podjanee; Hanboonkunupakarn, Borimas; Pukrittayakamee, Sasithon; Phyo, Aung Pyae; Smithuis, Frank; Lin, Khin; Thant, Myo; Hlaing, Tin Maung; Satpathi, Parthasarathi; Satpathi, Sanghamitra; Behera, Prativa K; Tripura, Amar; Baidya, Subrata; Valecha, Neena; Anvikar, Anupkumar R; Ul Islam, Akhter; Faiz, Abul; Kunasol, Chanon; Drury, Eleanor; Kekre, Mihir; Ali, Mozam; Love, Katie; Rajatileka, Shavanthi; Jeffreys, Anna E; Rowlands, Kate; Hubbart, Christina S; Dhorda, Mehul; Vongpromek, Ranitha; Kotanan, Namfon; Wongnak, Phrutsamon; Almagro Garcia, Jacob; Pearson, Richard D; Ariani, Cristina V; Chookajorn, Thanat; Malangone, Cinzia; Nguyen, T; Stalker, Jim; Jeffery, Ben | Abstract: BackgroundNational Malaria Control Programmes (NMCPs) currently make limited use of parasite genetic data. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS) that enables NMCPs to implement large-scale surveillance projects by integrating simple sample collection procedures in routine public health procedures.MethodsSamples from symptomatic patients are processed by SpotMalaria, a high-throughput system that produces a comprehensive set of genotypes comprising several drug resistance markers, species markers and a genomic barcode. GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions used to map prevalence of resistance to multiple drugs.ResultsGenRe-Mekong has worked with NMCPs and research projects in eight countries, processing 9623 samples from clinical cases. Monitoring resistance markers has been valuable for tracking the rapid spread of parasites resistant to the dihydroartemisinin-piperaquine combination therapy. In Vietnam and Laos, GenRe-Mekong data have provided novel knowledge about the spread of these resistant strains into previously unaffected provinces, informing decision-making by NMCPs.ConclusionsGenRe-Mekong provides detailed knowledge about drug resistance at a local level, and facilitates data sharing at a regional level, enabling cross-border resistance monitoring and providing the public health community with valuable insights. The project provides a rich open data resource to benefit the entire malaria community.FundingThe GenRe-Mekong project is funded by the Bill and Melinda Gates Foundation (OPP11188166, OPP1204268). Genotyping and sequencing were funded by the Wellcome Trust (098051, 206194, 203141, 090770, 204911, 106698/B/14/Z) and Medical Research Council (G0600718). A proportion of samples were collected with the support of the UK Department for International Development (201900, M006212), and Intramural Research Program of the National Institute of Allergy and Infectious Diseases.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed. Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

Host genetic factors can confer resistance against malaria, raising the question of whether this has led to evolutionary adaptation of parasite populations. In this study we investigated the correlation between host and parasite genetic variation in 4,171 Gambian and Kenya children ascertained with severe malaria due to Plasmodium falciparum. We identified a strong association between sickle haemoglobin (HbS) in the host and variation in three regions of the parasite genome, including nonsynonymous variants in the acyl-CoA synthetase family member PfACS8 on chromosome 2, in a second region of chromosome 2, and in a region containing structural variation on chromosome 11. The HbS-associated parasite alleles are in strong linkage disequilibrium and have frequencies which covary with the frequency of HbS across populations, in particular being much more common in Africa than other parts of the world. The estimated protective effect of HbS against severe malaria, as determined by comparison of cases with population controls, varies greatly according to the parasite genotype at these three loci. These findings open up a new avenue of enquiry into the biological and epidemiological significance of the HbS-associated polymorphisms in the parasite genome, and the evolutionary forces that have led to their high frequency and strong linkage disequilibrium in African P. falciparum populations.

Vector population control using insecticides is a key element of current strategies to prevent malaria transmission in Africa. The introduction of effective insecticides, such as the organophosphate pirimiphos-methyl, is essential to overcome the recurrent emergence of resistance driven by the highly diverse Anopheles genomes. Here, we use a population genomic approach to investigate the basis of pirimiphos-methyl resistance in the major malaria vectors Anopheles gambiae and A. coluzzii. A combination of copy number variation and a single non-synonymous substitution in the acetylcholinesterase gene, Ace1, provides the key resistance diagnostic in an A. coluzzii population from Côte d’Ivoire that we used for sequence-based association mapping, with replication in other West African populations. The Ace1 substitution and duplications occur on a unique resistance haplotype that evolved in A. gambiae and introgressed into A. coluzzii, and is now common in West Africa primarily due to selection imposed by other organophosphate or carbamate insecticides. Our findings highlight the predictive value of this complex resistance haplotype for phenotypic resistance and clarify its evolutionary history, providing tools to for molecular surveillance of the current and future effectiveness of pirimiphos-methyl based interventions., Author summary Control of mosquito populations via insecticidal tools or interventions is a mainstay of campaigns to reduce malaria transmission. However, especially in sub-Saharan Africa, continued insecticidal selection pressure on the most important species of Anopheles malaria mosquitoes has favoured the evolutionary selection of increasingly effective resistance mechanisms. We investigate the genetic basis of resistance to the organophosphate pirimiphos-methyl, the dominant insecticide now used for indoor residual spraying campaigns in Africa. Genome-wide association analysis of a population from Cote d’Ivoire showed that resistant specimens share a unique combination of mutations in one gene, the acetylcholinesterase enzyme, which constitute the prime cause of pirimiphos-methyl resistance. Further testing of these mutations in diagnostic assays involving two major malaria vectors, A. coluzzii and A. gambiae, validate their use as informative predictors of pirimiphos-methyl resistance. Using data from a large collection of whole genome sequenced specimens from a broader range of locations (Burkina-Faso, Côte d’Ivoire, Ghana, and Guinea), our evolutionary analyses demonstrate that these mutations emerged in A. gambiae and transferred into A. coluzzii by inter-specific hybridisation. Our results show how resistance mechanisms in key malaria vectors have developed and spread, and provide validated tools for molecular surveillance to inform public health campaigns.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed. Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

The two most efficient and most recently radiated Afrotropical vectors of human malaria – Anopheles coluzzii and An. gambiae – are identified by single‐locus diagnostic PCR assays based on species‐specific markers in a 4 Mb region on chromosome‐X centromere. Inherently, these diagnostic assays cannot detect interspecific autosomal admixture shown to be extensive at the westernmost and easternmost extremes of the species range. The main aim of this study was to develop novel, easy‐to‐implement tools for genotyping An. coluzzii and An. gambiae‐specific ancestral informative markers (AIMs) identified from the Anopheles gambiae 1000 genomes (Ag1000G) project. First, we took advantage of this large set of data in order to develop a multilocus approach to genotype 26 AIMs on all chromosome arms valid across the species range. Second, we tested the multilocus assay on samples from Guinea Bissau, The Gambia and Senegal, three countries spanning the westernmost hybridization zone, where conventional species diagnostic is problematic due to the putative presence of a novel “hybrid form”. The multilocus assay was able to capture patterns of admixture reflecting those revealed by the whole set of AIMs and provided new original data on interspecific admixture in the region. Third, we developed an easy‐to‐use, cost‐effective PCR approach for genotyping two AIMs on chromosome‐3 among those included in the multilocus approach, opening the possibility for advanced identification of species and of admixed specimens during routine large scale entomological surveys, particularly, but not exclusively, at the extremes of the range, where WGS data highlighted unexpected autosomal admixture.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.4 km (95% CI 0.24, 1.20), for a distribution with 58% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes.

The sustainability of malaria control in Africa is threatened by the rise of insecticide resistance in Anopheles mosquitoes, which transmit the disease(1). To gain a deeper understanding of how mosquito populations are evolving, here we sequenced the genomes of 765 specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa, and identified 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 several sweeps spreading over large geographical distances and between species. The design of new tools for mosquito control using gene-drive systems will need to take account of high levels of genetic diversity in natural mosquito populations.

Advances in genetic sequencing and accompanying methodological approaches have resulted in pathogen genetics being used in the control of infectious diseases. To utilise these methodologies for malaria we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment. Here we develop an individual-based transmission model to simulate malaria parasite genetics parameterised using estimated relationships between complexity of infection and age from 5 regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterise the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The best performing model successfully predicted malaria prevalence with mean absolute error of 0.055, suggesting genetic tools could be used for monitoring the impact of malaria interventions.

The spread of resistance to insecticides in the mosquito vectors of diseases such as malaria and dengue poses a threat to the effectiveness of control programmes, which rely largely on insecticide-based interventions. Monitoring the resistance status of mosquito populations is therefore essential, but obtaining direct phenotypic measurements of resistance is laborious and error-prone. In contrast, high-throughput genotyping offers the prospect of quick and repeatable estimates of resistance, while also allowing the genotypic markers of resistance to be tracked and studied. We developed a panel of 28 known or putative markers of resistance in the major malaria vectorAnopheles gambiae, which we use to test the association of these markers with resistance and to study their geographic distribution. We screened resistance-phenotypedAn.gambiaefrom populations from a wide swathe of Sub-Saharan Africa (Burkina Faso, Ghana, Democratic Republic of Congo (DRC) and Kenya), and found evidence of resistance association for four mutations, including a novel mutation in the detoxification geneGste2(Gste2-119V). We also identified a gene duplication inGste2which combines a resistance-associated mutant form of the gene with its wild-type counterpart, potentially alleviating the costs of resistance. Finally, we describe the distribution of the multiple evolutionary origins ofkdrresistance, finding unprecedented levels of diversity in the DRC. This panel represents the first step towards developing a quantitative predictive genotypic model of insecticide resistance that can be used to screenAn.gambiaepopulations and predict resistance status.

We conducted a genome-wide association study of host resistance to severePlasmodium falciparummalaria in over 17,000 individuals from 11 malaria-endemic countries, undertaking a wide ranging analysis which identifies five replicable associations with genome-wide levels of evidence. Our findings include a newly implicated variant on chromosome 6 associated with risk of cerebral malaria, and the discovery of an erythroid-specific transcription start site underlying the association inATP2B4. Previously reported HLA associations cannot be replicated in this dataset. We estimate substantial heritability of severe malaria (h2~ 23%), of which around 10% is explained by the currently identified associations. Our dataset will provide a major building block for future research on the genetic determinants of disease in these diverse human populations.

Recent developments in genotyping technologies coupled with the growing desire to characterize genome variation in Anopheles populations open the opportunity to develop more effective genotyping strategies for high-throughput screening. A major bottleneck of this goal is nucleic acid extraction. Here, we examined the feasibility of using intact portions of a mosquito's leg as sources of template DNA for whole-genome amplification (WGA) by primer-extension preamplification. We used the Agena Biosciences MassARRAY(®) platform (formerly Sequenom) to genotype 78 SNPs for 265 WGA leg samples. We performed nucleic acid extraction on 36 mosquito carcasses and compared the genotype call concordance with their corresponding legs and observed full concordance. Using three legs instead of one improved genotyping success rates (96% vs. 89%, respectively), although this difference was not significant. We provide a proof of concept that WGA reactions can be performed directly on mosquito legs, thereby eliminating the need to extract nucleic acid. This approach is straightforward and sensitive and allows both species determination and genotyping of Anopheles mosquitoes to be performed in a high-throughput manner. Our protocol also leaves the mosquito body intact facilitating other experimental analysis to be undertaken on the same sample. Based on our findings, this method would also be suitable for use with other insect species.

Background. Malaria control, and finally malaria elimination, requires the identification and targeting of residual foci or hotspots of transmission. However, the level of parasite mixing within and between geographical locations is likely to impact the effectiveness and durability of control interventions and thus should be taken into consideration when developing control programs. Methods. In order to determine the geographic-genetic patterns of Plasmodium falciparum parasite populations at a sub-national level in Kenya, we used the Sequenom platform to genotype 111 genome-wide distributed single nucleotide polymorphic (SNP) positions in 2486 isolates collected from children in 95 primary schools in western Kenya. We analysed these parasite genotypes for genetic structure using principal component analysis and assessed local and global clustering using statistical measures of spatial autocorrelation. We further examined the region for spatial barriers to parasite movement as well as directionality in the patterns of parasite movement. Results. We found no evidence of population structure and little evidence of spatial autocorrelation of parasite genotypes (correlation coefficients Conclusions. Our findings illustrate a pattern of high parasite mixing within the study region. If this mixing is due to rapid gene flow, then “one-off” targeted interventions may not be currently effective at the sub-national scale in Western Kenya, due to the high parasite movement that is likely to lead to re-introduction of infection from surrounding regions. However repeated targeted interventions may reduce transmission in the surrounding regions.

Summary Genetic association within several malaria candidate genes was examined in 24 villages of northeast Tanzania, using different measures of malaria transmission intensity. We demonstrate that the classic hemoglobinopathies were associated with measures of transmission intensity that had longer time scales., Background. Human malaria susceptibility is determined by multiple genetic factors. It is unclear, however, which genetic variants remain important over time. Methods. Genetic associations of 175 high-quality polymorphisms within several malaria candidate genes were examined in a sample of 8096 individuals from northeast Tanzania using altitude, seroconversion rates, and parasite rates as proxies of historical, recent, and current malaria transmission intensity. A principal component analysis was used to derive 2 alternative measures of overall malaria propensity of a location across different time scales. Results. Common red blood cell polymorphisms (ie, hemoglobin S, glucose-6-phosphate dehydrogenase, and α-thalassemia) were the only ones to be associated with all 3 measures of transmission intensity and the first principal component. Moderate associations were found between some immune response genes (ie, IL3 and IL13) and parasite rates, but these could not be reproduced using the alternative measures of malaria propensity. Conclusions. We have demonstrated the potential of using altitude and seroconversion rate as measures of malaria transmission capturing medium- to long-term time scales to detect genetic associations that are likely to persist over time. These measures also have the advantage of minimizing the deleterious effects of random factors affecting parasite rates on the respective association signals.

As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings., Author Summary Monitoring malaria epidemiology is critical for evaluating the impact of interventions and designing strategies for control and elimination. Population genetics has been used to inform malaria epidemiology, but it is limited by the fact that a fundamental metric needed for most analyses—the frequency of alleles in a population—is difficult to estimate from blood samples containing more than one genetically distinct parasite (polygenomic infections). A widely used approach has been to restrict analysis to monogenomic infections, which may represent a biased subset and potentially ignores a large amount of data. Therefore, we developed a new analytical approach that uses data from all infections to simultaneously estimate allele frequency and the number of distinct parasites within each infection. The method, called THE REAL McCOIL, was evaluated using simulations and was then applied to data from cross-sectional surveys performed in three regions of Uganda. Simulations demonstrated accurate performance, and analyses of samples from Uganda using THE REAL McCOIL revealed epidemiologically relevant differences within and between the three regions that previous methods could not. THE REAL McCOIL thus facilitates population genetic analysis when there are polygenomic infections, which are common in many malaria endemic areas.

Many human genetic associations with resistance to malaria have been reported, but few have been reliably replicated. We collected data on 11,890 cases of severe malaria due to Plasmodium falciparum and 17,441 controls from 12 locations in Africa, Asia and Oceania. We tested 55 SNPs in 27 loci previously reported to associate with severe malaria. There was evidence of association at P < 1 × 10(-4) with the HBB, ABO, ATP2B4, G6PD and CD40LG loci, but previously reported associations at 22 other loci did not replicate in the multicenter analysis. The large sample size made it possible to identify authentic genetic effects that are heterogeneous across populations or phenotypes, with a striking example being the main African form of G6PD deficiency, which reduced the risk of cerebral malaria but increased the risk of severe malarial anemia. The finding that G6PD deficiency has opposing effects on different fatal complications of P. falciparum infection indicates that the evolutionary origins of this common human genetic disorder are more complex than previously supposed.

The sustainability of malaria control in Africa is threatened by rising levels of insecticide resistance, and new tools to prevent malaria transmission are urgently needed. To gain a better understanding of the mosquito populations that transmit malaria, we sequenced the genomes of 765 wild specimens ofAnopheles gambiaeandAnopheles coluzziisampled from 15 locations across Africa. The data reveal high levels of genetic diversity, with over 50 million single nucleotide polymorphisms across the 230 Mbp genome. We observe complex patterns of population structure and marked variations in local population size, some of which may be due at least in part to malaria control interventions. Insecticide resistance genes show strong signatures of recent selection associated with multiple independent mutations spreading over large geographical distances and between species. The genetic variability of natural populations substantially reduces the target space for novel gene-drive strategies for mosquito control. This large dataset provides a foundation for tracking the emergence and spread of insecticide resistance and developing new vector control tools.

INTRODUCTION Malaria parasites cause human disease by invading and replicating inside red blood cells. In the case of Plasmodium falciparum , this can lead to severe forms of malaria that are a major cause of childhood mortality in Africa. This species of parasite enters the red blood cell through interactions with surface proteins including the glycophorins GYPA and GYPB, which determine the polymorphic MNS blood group system. In a recent genome-wide association study, we identified alleles associated with protection against severe malaria near the cluster of genes encoding these invasion receptors. RATIONALE Investigation of genetic variants at this locus and their relation to severe malaria is challenging because of the high sequence similarity between the neighboring glycophorin genes and the relative lack of available sequence data capturing the genetic diversity of sub-Saharan Africa. To better assess whether variation in the glycophorin genes could explain the signal of association, we generated additional sequence data from sub-Saharan African populations and developed an analytical approach to characterize structural variation at this complex locus. RESULTS Using 765 newly sequenced human genomes from 10 African ethnic groups along with data from the 1000 Genomes Project, we generated a reference panel of haplotypes across the glycophorin region. In addition to single-nucleotide polymorphisms and short indels, we assayed large copy number variants (CNVs) using sequencing read depth and uncovered extensive structural diversity. By imputing from this reference panel into 4579 severe malaria cases and 5310 controls from three African populations, we found that a complex CNV, here called DUP4, is associated with resistance to severe malaria and fully explains the previously reported signal of association. In our sample, DUP4 is present only in east Africa, and this localization, as well as the extent of similarity between DUP4 haplotypes, suggests that it has recently increased in frequency, presumably under natural selection due to malaria. To evaluate the potential functional consequences of this structural variant, we analyzed high-coverage sequence-read data from multiple individuals to generate a model of the DUP4 chromosome structure. The DUP4 haplotype contains five glycophorin genes, including two hybrid genes that juxtapose the extracellular domain of GYPB with the transmembrane and intracellular domains of GYPA. Noting that these predicted hybrids are characteristic of the Dantu antigen in the MNS blood group system, we sequenced a Dantu positive individual and confirmed that DUP4 is the molecular basis of the Dantu NE blood group variant. CONCLUSION Although a role for GYPA and GYPB in parasite invasion is well known, a direct link between glycophorin polymorphisms and clinical susceptibility to malaria has been elusive. Here we have provided a systematic catalog of CNVs, describing structural diversity that may have functional importance at this locus. Our results identify a specific variant that encodes hybrid glycophorin proteins and is associated with protection against severe malaria. This discovery calls for further work to determine how this particular molecular rearrangement affects parasite invasion and the red blood cell response and may lead us toward new parasite vulnerabilities that can be utilized in future interventions against this deadly disease.

Aims Current screening methods, such as single strand conformational polymorphism (SSCP) and denaturing high performance liquid chromatography (dHPLC) that are used for detecting mutations in familial hypercholesterolaemia (FH) subjects are time consuming, costly and only 80–90% sensitive. Here we have tested high-resolution melt (HRM) analysis for mutation detection using the Rotor-Gene6000 realtime rotary analyser. Methods and subjects Polymerase chain reaction and melt conditions (HRM) for 23 fragments of the LDL-receptor gene, a region of exon 26 in the APOB gene (including p.R3527Q) and exon 7 of the PCSK9 gene (including p.D374Y) were optimized. Two double stranded DNA saturating dyes, LC-Green and Syto9, were compared for sensitivity. Eighty-two samples with known mutations were used as positive controls. Twenty-eight Greek FH heterozygous patients and two homozygous patients from the UK and Croatia were screened. Results HRM was able to identify all the positive control mutations tested, with similar results with either dye. Eight different variations were found in 17 of the 28 Greek FH patients for an overall detection rate of 61%: c.41delT (1), p.W165X (1), p.C173R (3), p.S286R (2), p.V429M (4), p.G549D (4), p.V613I (1), and a previously unreported mutation p.F694V (1) which is predicted to be FH-causing by functional algorithms. Mutations were found in both the homozygous patients; p.Q92X (Croatia) and p.Y489C (UK); both patients were homozygous for their respective mutations. Conclusions HRM is a sensitive, robust technique that could significantly reduce the time and cost of screening for mutations in a clinical setting.

Similarity between two individuals in the combination of genetic markers along their chromosomes indicates shared ancestry and can be used to identify historical connections between different population groups due to admixture. We use a genome-wide, haplotype-based, analysis to characterise the structure of genetic diversity and gene-flow in a collection of 48 sub-Saharan African groups. We show that coastal populations experienced an influx of Eurasian haplotypes over the last 7000 years, and that Eastern and Southern Niger-Congo speaking groups share ancestry with Central West Africans as a result of recent population expansions. In fact, most sub-Saharan populations share ancestry with groups from outside of their current geographic region as a result of gene-flow within the last 4000 years. Our in-depth analysis provides insight into haplotype sharing across different ethno-linguistic groups and the recent movement of alleles into new environments, both of which are relevant to studies of genetic epidemiology. DOI: http://dx.doi.org/10.7554/eLife.15266.001, eLife digest Our genomes contain a record of historical events. This is because when groups of people are separated for generations, the DNA sequence in the two groups’ genomes will change in different ways. Looking at the differences in the genomes of people from the same population can help researchers to understand and reconstruct the historical interactions that brought their ancestors together. The mixing of two populations that were previously separate is known as admixture. Africa as a continent has few written records of its history. This means that it is somewhat unknown which important movements of people in the past generated the populations found in modern-day Africa. Busby et al. have now attempted to use DNA to look into this and reconstruct the last 4000 years of genetic history in African populations. As has been shown in other regions of the world, the new analysis showed that all African populations are the result of historical admixture events. However, Busby et al. could characterize these events to unprecedented level of detail. For example, multiple ethnic groups from The Gambia and Mali all show signs of sharing the same set of ancestors from West Africa, Europe and Asia who mixed around 2000 years ago. Evidence of a migration of people from Central West Africa, known as the Bantu expansion, could also be detected, and was shown to carry genes to the south and east. An important next step will be to now look at the consequences of the observed gene-flow, and ask if it has contributed to spreading beneficial, or detrimental, mutations around Africa. DOI: http://dx.doi.org/10.7554/eLife.15266.002

Background Glucose-6-phosphate dehydrogenase (G6PD) deficiency exhibits considerable allelic heterogeneity which manifests with variable biochemical and clinical penetrance. It has long been thought that G6PD deficiency confers partial protection against severe malaria, however prior genetic association studies have disagreed with regard to the strength and specificity of a protective effect, which might reflect differences in the host genetic background, environmental influences, or in the specific clinical phenotypes considered. Methods A case-control association study of severe malaria was conducted in The Gambia, a region in West Africa where there is considerable allelic heterogeneity underlying expression of G6PD deficiency trait, evaluating the three major nonsynonymous polymorphisms known to be associated with enzyme deficiency (A968G, T542A, and C202T) in a cohort of 3836 controls and 2379 severe malaria cases. Results Each deficiency allele exhibited a similar trend toward protection against severe malaria overall (15–26 % reduced risk); however, in stratifying severe malaria to two of its constituent clinical subphenotypes, severe malarial anaemia (SMA) and cerebral malaria (CM), the three deficiency alleles exhibited trends of opposing effect, with risk conferred to SMA and protection with respect to CM. To assess the overall effect of G6PD deficiency trait, deficiency alleles found across all three loci were pooled. G6PD deficiency trait was found to be significantly associated with protection from severe malaria overall (OR 0.83 [0.75–0.92], \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 0.0006$$\end{document}P=0.0006), but this was limited to CM (OR 0.73 [0.61–0.87], \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 0.0005$$\end{document}P=0.0005), with a trend toward increased risk for SMA, especially in fully-deficient individuals (OR 1.43 [0.99–2.08], \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 0.056$$\end{document}P=0.056). Sex-stratified testing largely comported with these results, with evidence suggesting that protection by G6PD deficiency trait is conferred to both males and females, though susceptibility to SMA may be restricted to fully-deficient male hemizygotes. Conclusions In a part of Africa where multiple alleles contribute to expression of G6PD deficiency trait, these findings clarify and extend previous work done in populations where a single variant predominates, and taken together suggest a causal role for G6PD deficiency trait itself with respect to severe malaria, with opposing effects seen on two major clinical subphenotypes.

The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for the elimination of malaria. To characterize the genetic diversity of this parasite in individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region and analyzed data on >300,000 SNPs and nine 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 new loci, and these varied markedly between geographical locations. These findings demonstrate a dynamic landscape of local evolutionary adaptation in the parasite population and provide a foundation for genomic surveillance to guide effective strategies for control and elimination of P. vivax.

Background: The first models of malaria transmission assumed a completely mixed and homogeneous population of parasites. Recent models include spatial heterogeneity and variably mixed populations. However, there are few empiric estimates of parasite mixing with which to parametize such models. Methods: Here we genotype 276 single nucleotide polymorphisms (SNPs) in 5199 P. falciparum isolates from two Kenyan sites (Kilifi county and Rachuonyo South district) and one Gambian site (Kombo coastal districts) to determine the spatio-temporal extent of parasite mixing, and use Principal Component Analysis (PCA) and linear regression to examine the relationship between genetic relatedness and distance in space and time for parasite pairs. Results: Using 107, 177 and 82 SNPs that were successfully genotyped in 133, 1602, and 1034 parasite isolates from The Gambia, Kilifi and Rachuonyo South district, respectively, we show that there are no discrete geographically restricted parasite sub-populations, but instead we see a diffuse spatio-temporal structure to parasite genotypes. Genetic relatedness of sample pairs is predicted by relatedness in space and time. Conclusions: Our findings suggest that targeted malaria control will benefit the surrounding community, but unfortunately also that emerging drug resistance will spread rapidly through the population.

We describe an analysis of genome variation in 825 Plasmodium falciparum samples from Asia and Africa that reveals an unusual pattern of parasite population structure at the epicentre of artemisinin resistance in western Cambodia. Within this relatively small geographical area we have discovered several distinct but apparently sympatric parasite subpopulations with extremely high levels of genetic differentiation. Of particular interest are three subpopulations, all associated with clinical resistance to artemisinin, which have skewed allele frequency spectra and remarkably high levels of haplotype homozygosity, indicative of founder effects and recent population expansion. We provide a catalogue of SNPs that show high levels of differentiation in the artemisinin-resistant subpopulations, including codon variants in various transporter proteins and DNA mismatch repair proteins. These data provide a population genetic framework for investigating the biological origins of artemisinin resistance and for defining molecular markers to assist its elimination.

The last author's name was spelled incorrectly. The correct name is: Malaria Genomic Epidemiology Network

Background Resistance to anti-malarial drugs is a widespread problem for control programmes for this devastating disease. Molecular tests are available for many anti-malarial drugs and are useful tools for the surveillance of drug resistance. However, the correlation of treatment outcome and molecular tests with particular parasite markers is not perfect, due in part to individuals who are able to clear genotypically drug-resistant parasites. This study aimed to identify molecular markers in the human genome that correlate with the clearance of malaria parasites after drug treatment, despite the drug resistance profile of the protozoan as predicted by molecular approaches. Methods 3721 samples from five African countries, which were known to contain genotypically drug resistant parasites, were analysed. These parasites were collected from patients who subsequently failed to clear their infection following drug treatment, as expected, but also from patients who successfully cleared their infections with drug-resistant parasites. 67 human polymorphisms (SNPs) on 17 chromosomes were analysed using Sequenom's mass spectrometry iPLEX gold platform, to identify regions of the human genome, which contribute to enhanced clearance of drug resistant parasites. Results An analysis of all data from the five countries revealed significant associations between the phenotype of ability to clear drug-resistant Plasmodium falciparum infection and human immune response loci common to all populations. Overall, three SNPs showed a significant association with clearance of drug-resistant parasites with odds ratios of 0.76 for SNP rs2706384 (95% CI 0.71-0.92, P = 0.005), 0.66 for SNP rs1805015 (95% CI 0.45-0.97, P = 0.03), and 0.67 for SNP rs1128127 (95% CI 0.45-0.99, P = 0.05), after adjustment for possible confounding factors. The first two SNPs (rs2706384 and rs1805015) are within loci involved in pro-inflammatory (interferon-gamma) and anti-inflammatory (IL-4) cytokine responses. The third locus encodes a protein involved in the degradation of misfolded proteins within the endoplasmic reticulum, and its role, if any, in the clearance phenotype is unclear. Conclusions The study showed significant association of three loci in the human genome with the ability of parasite to clear drug-resistant P. falciparum in samples taken from five countries distributed across sub-Saharan Africa. Both SNP rs2706384 and SNP1805015 have previously been reported to be associated with risk of malaria infection in African populations. The loci are involved in the Th1/Th2 balance, and the association of SNPs within these genes suggests a key role for antibody in the clearance of drug-resistant parasites. It is possible that patients able to clear drug-resistant infections have an enhanced ability to control parasite growth.

Large-scale studies of genomic variation could assist efforts to eliminate malaria. But there are scientific, ethical and practical challenges to carrying out such studies in developing countries, where the burden of disease is greatest. The Malaria Genomic Epidemiology Network (MalariaGEN) is now working to overcome these obstacles, using a consortial approach that brings together researchers from 21 countries. © 2008 Macmillan Publishers Limited. All rights reserved.

The behavioural and psychological impact of genetic testing for lung cancer susceptibility was examined among smokers ( N = 61) who were randomly allocated to a GSTM1 genetic testing group (with GSTM1-missing or GSTM1-present result) or no-test control group. The GSTM1-missing (higher risk) group reported greater motivation to quit smoking, and both genetic testing groups reported lower depression than the control group at one-week follow-up ( p < .05 for all). Differences were not significant at two months follow-up. This study indicates the feasibility of much-needed research into the risks and benefits for individuals of emerging lifestyle-related genetic susceptibility tests.

Familial hypercholesterolemia (FH) (OMIM 143890) is most commonly caused by variations in the LDLR gene which encodes the receptor for Low Density Lipoprotein (LDL) cholesterol particles. We have updated the University College London (UCL) LDLR FH database (http://www.ucl.ac.uk/ldlr) by adding variants reported in the literature since 2001, converting existing entries to standard nomenclature, and transferring the database to the Leiden Open Source Variation Database (LOVD) platform. As of July 2007 the database listed 1066 unique LDLR gene events. Sixty five percent (n = 689) of the variants are DNA substitutions, 24% (n = 260) small DNA rearrangements (100bp) and 11% (n = 117) large DNA rearrangements (100bp), proportions which are similar to those reported in the 2001 database (n = 683, 62%, 24% and 14% respectively). The DNA substitutions and small rearrangements occur along the length of the gene, with 24 in the promoter region, 86 in intronic sequences and 839 in the exons (93 nonsense variants, 499 missense variants and 247 small rearrangements). These occur in all exons, with the highest proportion (20%) in exon 4 (186/949); this exon is the largest and codes for the critical ligand binding region, where any missense variant is likely to be pathogenic. Using the PolyPhen and SIFT prediction computer programmes 87% of the missense variants are predicted to have a deleterious effect on LDLR activity, and it is probable that at least 48% of the remainder are also pathogenic, but their role in FH causation requires confirmation by in vitro or family studies.

Large increases in inflammatory markers, particularly IL-6, occur after cardiac surgery. However, despite interventions to reduce the inflammatory response, great variability still remains which could in part be attributable to genetic predisposition. Since increased IL-6 levels following surgery are also associated with poorer outcome we sought to determine whether baseline and post-operative levels of Interleukin-6 (IL-6) and functional common variants of the Interleukin-6 ( IL6 ) gene are associated with post-operative outcome following coronary artery bypass grafting (CABG). Caucasian patients undergoing first-time elective CABG were studied. IL-6 levels were measured pre-, 6h and 24h following surgery and genotypes for IL6 gene variants −174G>C and −572G>C were obtained. Clinical data was collected daily until patient discharge. Patient outcome was categorised as with (ICUC, n =177) and without (NICUC, n =189) a post-operative complication during the ICU period and with (POC, n =215) and without (NC, n =151) a post-operative complication during hospitalisation. IL-6 levels pre- and at 24h were greater in POC and ICUC than NC and NICUC, respectively. Pre- IL-6 levels independently predicted (for 1 standard deviation increase in log IL-6) POC (OR 1.4, 95% CI 1.1–1.7, p =0.008) and ICUC (OR 1.3, 95% CI 1.0–1.6, p =0.02) outcomes. Overall, the IL6 -572G>C had an effect over time on IL-6 levels ( p =0.04) and on IL-6 levels in NC (P=0.008) and NICUC ( p =0.006). However, no associations were found with the IL6 −572G>C or −174G>C variants on IL-6 levels at individual time-points or by outcome group. Thus, in conclusion, elevated pre-operative IL-6 levels, but not IL6 gene variants predict poor patient outcome following CABG.

In the present study, we have determined the relative frequency of the R46L, I474V and E670G variants in the PCSK9 (protein convertase subtilisin/kexin type 9) gene and its association with plasma lipid levels and CHD (coronary heart disease) in healthy U.K. men and patients with clinically defined definite FH (familial hypercholesterolaemia). Genotypes were determined using PCR and restriction enzyme digestion in 2444 healthy middle-aged (50–61 years) men from the prospective NPHSII (Second Northwick Park Heart Study), with 275 CHD events (15 years of follow-up), and in 597 U.K. FH patients from the Simon Broome Register. In the NPHSII healthy men, the R46L genotype distribution was in Hardy–Weinberg equilibrium and the frequency of 46L was 0.010 [95% CI (confidence interval), 0.007–0.013], with one man homozygous for the 46L allele. There was significant association of the 46L allele with lower mean (S.D.) total cholesterol [5.74 (1.01) mmol/l for RR compared with 5.26±1.03 mmol/l for RL; P=0.001], apolipoprotein B [0.87 (0.24) g/l for RR compared with 0.75 (0.26) g/l for RL; P

Introduction Glutathione S transferases (GST) are enzymes responsible for the metabolism of numerous xenobiotics and play a major cellular antioxidant role. Our aim was firstly, to examine the association between the GST M1/GST mu-1 (GSTM1) and GST T1/GST theta-1 (GSTT1) gene variants with markers of oxidative stress and inflammation in diabetic patients, and secondly to examine the association and potential interaction between these variants and cigarette smoking. Methods Seven hundred and seventy-three Caucasian subjects with diabetes and 2592 Caucasian non-diabetic subjects were successfully genotyped. Plasma total antioxidant status, C-reactive protein (CRP), oxidized-LDL (Ox-LDL) and LDL-mean/peak particle diameter were recorded in the diabetes sample. Results No association was seen between genotype and cardiovascular disease (CVD) risk. In the diabetic subjects, GSTT1-1 compared to GSTT1-0 subjects had significantly higher CRP ( p =0.001), Ox-LDL ( p =0.004) and smaller LDL particles ( p =0.01). In subjects without CVD, there was a significant interaction between the GSTT1-1 variant and smoking in determining Ox-LDL ( p =0.04). Furthermore, CVD risk was higher in smokers compared to non-smokers with GSTT1-1. No significant associations were observed by GSTM1. Within the non-diabetic sample, no association was observed between genotype and prospective coronary heart disease (CHD) risk. Of note, the frequency of the GSTT1-1 variant was significantly lower in the diabetes subjects compared to the non-diabetic sample ( p =0.01). Conclusions This study demonstrates an association between the GSTT1-1 variant and markers of inflammation and lipid peroxidation. Furthermore this variant interacts with smoking to increase lipid peroxidation.