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The successful implementation of pathogen genomic surveillance demands rapid, low-cost genotyping solutions for tracking infections. Here we demonstrate the capacity of single nucleotide polymorphism (SNP) barcodes to generate practical information for malaria surveillance and control. The study was conducted in Papua New Guinea (PNG), a country with a wide range of malaria transmission intensities. A panel of 191 candidate SNPs was selected from 5786 SNPs with minor allele frequency greater than 0.1, identified amongst 91Plasmodium falciparumgenomes from three provinces of PNG. We then genotyped 772P. falciparumisolates from a 2008 nationwide malaria indicator survey and 31 clinical infections from an outbreak of unknown origin. We assessed the performance of SNP panels with different allele frequency characteristics, and measured population diversity, structure and connectivity using both whole genome data and the SNP barcode. The full SNP barcode captured similar patterns of population structure evident with 5786 ‘whole genome’ SNPs. Geographically informative SNPs (iSNPs,FST>0.05) show increased population clustering compared to the full barcode whilst randomly selected SNPs (rSNPs) and SNPs with similar allele frequencies (FST<0.05) amongst different countries (universal, uSNPs) or local PNG populations (balanced, bSNPs) indicated little clustering. Applied to samples from all endemic areas of PNG, this barcode identified variable transmission dynamics, and eight major populations. Genetic diversity was high throughout most areas, however, in the southern region, isolates were either closely related, suggesting highly inbred or near-clonal populations; or, they shared ancestry with other parasite populations, consistent with importation. Applied to outbreak samples, only the full barcode, the iSNPs and bSNPs distinguished between locally acquired and imported infections. The full barcode contains more than 100 SNPs prevalent in other endemic regions, allowing the transfer of this tool to other settings. SNP barcodes must be validated in local settings to ensure they capture the diversity and population structure of the target population. Subsets of geographically informative SNPs will be essential for predicting geographic origins but may bias analyses of population structure and gene flow if used alone.AUTHOR SUMMARYPathogen genomic surveillance is a sensitive approach for mapping pathogen transmission dynamics to support decisions about how to prevent and control infectious diseases. High throughput genotyping tools known as single nucleotide polymorphism (SNP) barcodes are used to measure relationships between individuals and connectivity between populations, however, the barcode design may influence these results. We used whole genome sequences from the malaria parasitePlasmodium falciparumto design a barcode that captures the diversity both within and between parasite populations of Papua New Guinea (PNG), where transmission is variable amongst provinces. By investigating the performance of different panels of SNPs, we show that validation for use in the target population is crucial to correctly identifying population genetic structure. Applying the validated SNP barcode on hundreds of samples from all endemic provinces of PNG, high levels of variability in local transmission dynamics, and regions of population subdivision were observed. Some geographic areas show evidence of interrupted transmission, and the substantial genetic differentiation between the northern, eastern and island populations, presents an opportunity to design targeted, subnational control efforts. Application of the barcode to outbreak samples classified cases into imported and locally acquired infections, with substantial local transmission indicating control efforts were not sufficient to prevent the spread of infections. SNP barcodes are useful tools that can be used to supplement existing malaria surveillance tools however careful validation of their effectiveness in different settings is recommended.
The successful implementation of pathogen genomic surveillance demands rapid, low-cost genotyping solutions for tracking infections. Here we demonstrate the capacity of single nucleotide polymorphism (SNP) barcodes to generate practical information for malaria surveillance and control. The study was conducted in Papua New Guinea (PNG), a country with a wide range of malaria transmission intensities. A panel of 191 candidate SNPs was selected from 5786 SNPs with minor allele frequency greater than 0.1, identified amongst 91Plasmodium falciparumgenomes from three provinces of PNG. We then genotyped 772P. falciparumisolates from a 2008 nationwide malaria indicator survey and 31 clinical infections from an outbreak of unknown origin. We assessed the performance of SNP panels with different allele frequency characteristics, and measured population diversity, structure and connectivity using both whole genome data and the SNP barcode. The full SNP barcode captured similar patterns of population structure evident with 5786 ‘whole genome’ SNPs. Geographically informative SNPs (iSNPs,FST>0.05) show increased population clustering compared to the full barcode whilst randomly selected SNPs (rSNPs) and SNPs with similar allele frequencies (FST<0.05) amongst different countries (universal, uSNPs) or local PNG populations (balanced, bSNPs) indicated little clustering. Applied to samples from all endemic areas of PNG, this barcode identified variable transmission dynamics, and eight major populations. Genetic diversity was high throughout most areas, however, in the southern region, isolates were either closely related, suggesting highly inbred or near-clonal populations; or, they shared ancestry with other parasite populations, consistent with importation. Applied to outbreak samples, only the full barcode, the iSNPs and bSNPs distinguished between locally acquired and imported infections. The full barcode contains more than 100 SNPs prevalent in other endemic regions, allowing the transfer of this tool to other settings. SNP barcodes must be validated in local settings to ensure they capture the diversity and population structure of the target population. Subsets of geographically informative SNPs will be essential for predicting geographic origins but may bias analyses of population structure and gene flow if used alone.AUTHOR SUMMARYPathogen genomic surveillance is a sensitive approach for mapping pathogen transmission dynamics to support decisions about how to prevent and control infectious diseases. High throughput genotyping tools known as single nucleotide polymorphism (SNP) barcodes are used to measure relationships between individuals and connectivity between populations, however, the barcode design may influence these results. We used whole genome sequences from the malaria parasitePlasmodium falciparumto design a barcode that captures the diversity both within and between parasite populations of Papua New Guinea (PNG), where transmission is variable amongst provinces. By investigating the performance of different panels of SNPs, we show that validation for use in the target population is crucial to correctly identifying population genetic structure. Applying the validated SNP barcode on hundreds of samples from all endemic provinces of PNG, high levels of variability in local transmission dynamics, and regions of population subdivision were observed. Some geographic areas show evidence of interrupted transmission, and the substantial genetic differentiation between the northern, eastern and island populations, presents an opportunity to design targeted, subnational control efforts. Application of the barcode to outbreak samples classified cases into imported and locally acquired infections, with substantial local transmission indicating control efforts were not sufficient to prevent the spread of infections. SNP barcodes are useful tools that can be used to supplement existing malaria surveillance tools however careful validation of their effectiveness in different settings is recommended.
Challenges in classifying recurrent Plasmodium vivax infections constrain surveillance of antimalarial efficacy and transmission. Recurrent infections may arise from activation of dormant liver stages (relapse), blood-stage treatment failure (recrudescence) or reinfection. Molecular inference of familial relatedness (identity-by-descent or IBD) can help resolve the probable origin of recurrences. As whole genome sequencing of P. vivax remains challenging, targeted genotyping methods are needed for scalability. We describe a P. vivax marker discovery framework to identify and select panels of microhaplotypes (multi-allelic markers within small, amplifiable segments of the genome) that can accurately capture IBD. We evaluate panels of 50–250 microhaplotypes discovered in a global set of 615 P. vivax genomes. A candidate global 100-microhaplotype panel exhibits high marker diversity in the Asia-Pacific, Latin America and horn of Africa (median HE = 0.70–0.81) and identifies 89% of the polyclonal infections detected with genome-wide datasets. Data simulations reveal lower error in estimating pairwise IBD using microhaplotypes relative to traditional biallelic SNP barcodes. The candidate global panel also exhibits high accuracy in predicting geographic origin and captures local infection outbreak and bottlenecking events. Our framework is open-source enabling customised microhaplotype discovery and selection, with potential for porting to other species or data resources.
Despite efforts to eliminate malaria in Sao Tome and Principe (STP), cases have recently increased. Understanding residual transmission structure is crucial for developing effective elimination strategies. This study collected surveillance data and generated amplicon sequencing data from 980 samples between 2010 and 2016 to examine the genetic structure of the parasite population. The mean multiplicity of infection (MOI) was 1.3, with 11% polyclonal infections, indicating low transmission intensity. Temporal trends of these genetic metrics did not align with incidence rates, suggesting that changes in genetic metrics may not straightforwardly reflect changes in transmission intensity, particularly in low transmission settings where genetic drift and importation have a substantial impact. While 88% of samples were genetically linked, continuous turnover in genetic clusters and changes in drug-resistance haplotypes were observed. Principal component analysis revealed some STP samples were genetically similar to those from Central and West Africa, indicating possible importation. These findings highlight the need to prioritize several interventions such as targeted interventions against transmission hotspots, reactive case detection, and strategies to reduce the introduction of new parasites into this island nation as it approaches elimination. This study also serves as a case study for implementing genetic surveillance in a low transmission setting.
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