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An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples
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.
New insights into malaria susceptibility from the genomes of 17,000 individuals from Africa, Asia, and Oceania
We conducted a genome-wide association study of host resistance to severe Plasmodium falciparum malaria 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 in ATP2B4 . Previously reported HLA associations cannot be replicated in this dataset. We estimate substantial heritability of severe malaria ( h 2 ~ 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.
Resistance to malaria through structural variation of red blood cell invasion receptors
Plasmodium falciparum invades human red blood cells by a series of interactions between host and parasite surface proteins. Here we analyse whole genome sequence data from worldwide human populations, including 765 new genomes from across sub-Saharan Africa, and identify a diverse array of large copy number variants affecting the host invasion receptor genes GYPA and GYPB . We find that a nearby reported association with severe malaria is explained by a complex structural variant that involves the loss of GYPB and gain of two hybrid genes, each with a GYPB extracellular domain and GYPA intracellular domain. This variant reduces the risk of severe malaria by 40% and has recently risen in frequency in parts of Kenya. We show that the structural variant encodes the Dantu blood group antigen, and therefore a serologically distinct red cell phenotype. These findings demonstrate that structural variation of red blood cell invasion receptors is associated with natural resistance to P. falciparum malaria.
Investigating the drivers of the spatio-temporal patterns of genetic differences between Plasmodium falciparum malaria infections in Kilifi County, Kenya.
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 0.5 km (95% CI 0.3-1.5), for a distribution with 68% 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.
Genome variation and population structure among 1142 mosquitoes of the African malaria vector species Anopheles gambiae and Anopheles coluzzii.
Mosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with a high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high-quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii We analyzed whole genomes of 1142 individual mosquitoes sampled from the wild in 13 African countries, as well as a further 234 individuals comprising parents and progeny of 11 laboratory crosses. The data resource includes high-confidence single-nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We use these data to analyze genetic population structure and characterize genetic diversity within and between populations. We illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance and for accelerating research and development of new vector control tools. It also provides a unique resource for the study of population genomics and evolutionary biology in eukaryotic species with high levels of genetic diversity under strong anthropogenic evolutionary pressures.
Genetic surveillance in the Greater Mekong subregion and South Asia to support malaria control and elimination.
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.
High-throughput genotyping assays for identification of glycophorin B deletion variants in population studies.
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 Plasmodiumsp., Babesiasp., 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.
Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing.
Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets. Yet the large and low complexity genome of P. falciparum complicates the development of genomic methods, while resource constraints in malaria endemic regions can limit their deployment. Here, we demonstrate an approach for targeted nanopore sequencing of P. falciparum from dried blood spots (DBS) that enables cost-effective genomic surveillance of malaria in low-resource settings. We release software that facilitates flexible design of amplicon sequencing panels and use this software to design two target panels for P. falciparum. The panels generate 3-4 kbp reads for eight and sixteen targets respectively, covering key drug-resistance associated genes, diagnostic test antigens, polymorphic markers and the vaccine target csp. We validate our approach on mock and field samples, demonstrating robust sequencing coverage, accurate variant calls within coding sequences, the ability to explore P. falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure.
Malaria protection due to sickle haemoglobin depends on parasite genotype.
Host genetic factors can confer resistance against malaria1, raising the question of whether this has led to evolutionary adaptation of parasite populations. Here we searched for association between candidate host and parasite genetic variants in 3,346 Gambian and Kenyan children with severe malaria caused by Plasmodium falciparum. We identified a strong association between sickle haemoglobin (HbS) in the host and three regions of the parasite genome, which is not explained by population structure or other covariates, and which is replicated in additional samples. The HbS-associated alleles include nonsynonymous variants in the gene for the acyl-CoA synthetase family member2-4 PfACS8 on chromosome 2, in a second region of chromosome 2, and in a region containing structural variation on chromosome 11. The alleles are in strong linkage disequilibrium and have frequencies that 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.
An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.
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.
Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α 3.7I form of α-thalassaemia using genome-wide microarray data.
Background: The -α 3.7I-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.
An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples
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.
Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data
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.
Copper-based reactions in analyte-responsive fluorescent probes for biological applications.
Copper chemistry has been capitalized on in a wide spectrum of biological events. The central importance of copper in biology lies in the diverse chemical reactivity of the redox-active transition metal ranging from electron transfer, small molecule binding and activation, to catalysis. In addition to its many different roles in natural biological systems, the diverse chemical reactivity of copper also represents a rich opportunity and resource to develop synthetic bioanalytical tools for the study of biologically important species and molecules. In this mini-review, fluorescent probes featuring a specific copper-based chemical reaction to selectively detect a biologically relevant analyte will be discussed. In particular, fluorescent probes for sensing labile copper ions, amino acids and small reactive species will be highlighted. The chemical principles, advantages and limitations of the different types of copper-mediated chemical reactions in these fluorescent probes will be emphasized.
Rhenium complexes of bidentate, bis-bidentate and tridentate N-heterocyclic carbene ligands.
A series of eight Rhenium(I)-N-heterocyclic carbene (NHC) complexes of the general form [ReCl(CO)3(C^C)] (where C^C is a bis(NHC) bidentate ligand), [ReCl(CO)3(C^C)]2 (where C^C is a bis-bidentate tetra-NHC ligand) and [Re(CO)3(C^N^C)](+)[X](-) (where C^N^C is a bis(NHC)-amine ligand and the counter ion X is either the ReO4(-) or PF6(-)) have been synthesised using a Ag2O transmetallation protocol. The novel precursor imidazolium salts and Re(I) complexes were characterized by elemental analysis, (1)H and (13)C NMR spectroscopy and the molecular structures for two imidazolium salt and six Re(I) complexes were determined by single crystal X-ray diffraction. These NHC ligand systems are of interest for possible applications in the development of Tc-99m or Re-186/188 radiopharmaceuticals and as such the stability of two complexes of the form [ReCl(CO)3(C^C)] and [Re(CO)3(C^N^C)][ReO4] were evaluated in ligand challenge experiments using the metal binding amino acids L-histidine or L-cysteine. These studies showed that the former was unstable, with the chloride ligand being replaced by either cysteine or histidine, while no evidence for transchelation was observed for the latter suggesting that bis(NHC)-amine ligands of this type may be suitable for biological applications.
Rhenium and technetium tricarbonyl complexes of N-heterocyclic carbene ligands.
A strategy for the conjugation of N-heterocyclic carbene (NHC) ligands to biomolecules via amide bond formation is described. Both 1-(2-pyridyl)imidazolium or 1-(2-pyridyl)benzimidazolium salts functionalized with a pendant carboxylic acid group were prepared and coupled to glycine benzyl ester using 1-ethyl-3-(3-(dimethylamino)propyl)carbodiimide. A series of 10 rhenium(I) tricarbonyl complexes of the form [ReX(CO)3(ĈN)] (ĈN is a bidentate NHC ligand, and X is a monodentate anionic ligand: Cl(-), RCO2(-)) were synthesized via a Ag2O transmetalation protocol from the Re(I) precursor compound Re(CO)5Cl. The synthesized azolium salts and Re(I) complexes were characterized by elemental analysis and by (1)H and (13)C NMR spectroscopy, and the molecular structures for one imidazolium salt and seven Re(I) complexes were determined by single-crystal X-ray diffraction. (1)H NMR and mass spectrometry studies for an acetonitrile-d3 solution of [ReCl(CO)3(1-(2-pyridyl)-3-methylimidazolylidene)] show that the monodentate chloride ligand is labile and exchanges with this solvent yielding a cationic acetonitrile adduct. For the first time the labeling of an NHC ligand with technetium-99m is reported. Rapid Tc-99m labeling was achieved by heating the imidazolium salt 1-(2-pyridyl)-3-methylimidazolium iodide and Ag2O in methanol, followed by the addition of fac-[(99m)Tc(OH2)3(CO)3](+). To confirm the structure of the (99m)Tc-labeled complex, the equivalent (99)Tc complex was prepared, and mass spectrometric studies showed that the formed Tc complexes are of the form [(99m/99)Tc(CH3CN)(CO)3(1-(2-pyridyl)-3-methylimidazolylidene)](+) with an acetonitrile molecule coordinated to the metal center.