Identity-by-descent analyses for measuring population dynamics and selection in recombining pathogens

Genetic surveillance reveals low, sustained malaria transmission with clonal replacement in Sao Tome and Principe

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.

Genomic surveillance of malaria parasites in an indigenous community in the Peruvian Amazon

Hard-to-reach communities represent Peru's main challenge for malaria elimination, but information about transmission in these areas is scarce. Here, we assessed Plasmodium vivax (Pv) and P. falciparum (Pf) transmission dynamics, resistance markers, and Pf hrp2/3 deletions in Nueva Jerusalén (NJ), a remote, indigenous community in the Peruvian Amazon with high population mobility. We collected samples from November 2019 to May 2020 by active (ACD) and passive case detection (PCD) in NJ. Parasites were identified with microscopy and PCR. Then, we analyzed a representative set of positive-PCR samples (Pv = 68, Pf = 58) using highly-multiplexed deep sequencing assays (AmpliSeq) and compared NJ parasites with ones from other remote Peruvian areas using population genetics indexes. The ACD intervention did not reduce malaria cases in the short term, and persistent malaria transmission was observed (at least one Pv infection was detected in 96% of the study days). In Nueva Jerusalen, the Pv population had modest genetic diversity (He = 0.27). Pf population had lower diversity (He = 0.08) and presented temporal clustering, one of these clusters linked to an outbreak in February 2020. Moreover, Pv and Pf parasites from NJ exhibited variable levels of differentiation (Pv Fst = 0.07-0.52 and Pf Fst = 0.11-0.58) with parasites from other remote areas. No artemisin resistance mutations but chloroquine (57%) and sulfadoxine-pyrimethamine (35-67%) were detected in NJ's Pf parasites. Moreover, pfhrp2/3 gene deletions were common (32-50% of parasites with one or both genes deleted). The persistent Pv transmission and the detection of a Pf outbreak with parasites genetically distinct from the local ones highlight the need for tailored interventions focusing on mobility patterns and imported infections in remote areas to eliminate malaria in the Peruvian Amazon.

Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in High-Recombining Plasmodium falciparum Genomes

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is increasingly being used in Plasmodium population genomics to estimate genetic relatedness, effective population size (N e ), population structure, and signals of positive selection. Despite its potential, a thorough evaluation of IBD segment detection tools for species with high recombination rates, such as P. falciparum, remains absent. Here, we perform comprehensive benchmarking of IBD callers - probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD) - using population genetic simulations tailored for high recombination, and IBD quality metrics at both the IBD segment level and the IBD-based downstream inference level. Our results demonstrate that low marker density per genetic unit, related to high recombination relative to mutation, significantly compromises the accuracy of detected IBD segments. In genomes with high recombination rates resembling P. falciparum, most IBD callers exhibit high false negative rates for shorter IBD segments, which can be partially mitigated through optimization of IBD caller parameters, especially those related to marker density. Notably, IBD detected with optimized parameters allows for more accurate capture of selection signals and population structure; IBD-based N e inference is very sensitive to IBD detection errors, with IBD called from hmmIBD uniquely providing less biased estimates of N e in this context. Validation with empirical data from the MalariaGEN Pf 7 database, representing different transmission settings, corroborates these findings. We conclude that context-specific evaluation and parameter optimization are essential for accurate IBD detection in high-recombining species and recommend hmmIBD for quality-sensitive analysis, such as estimation of N e in these species. Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.

Plasmodium vivax genomic surveillance in the Peruvian Amazon with Pv AmpliSeq assay

BACKGROUND

Plasmodium vivax is the most predominant malaria species in Latin America, constituting 71.5% of malaria cases in 2021. With several countries aiming for malaria elimination, it is crucial to prioritize effectiveness of national control programs by optimizing the utilization of available resources and strategically implementing necessary changes. To support this, there is a need for innovative approaches such as genomic surveillance tools that can investigate changes in transmission intensity, imported cases and sources of reintroduction, and can detect molecular markers associated with drug resistance.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we apply a modified highly-multiplexed deep sequencing assay: Pv AmpliSeq v2 Peru. The tool targets a newly developed 41-SNP Peru barcode for parasite population analysis within Peru, the 33-SNP vivaxGEN-geo panel for country-level classification, and 11 putative drug resistance genes. It was applied to 230 samples from the Peruvian Amazon (2007-2020), generating baseline surveillance data. We observed a heterogenous P. vivax population with high diversity and gene flow in peri-urban areas of Maynas province (Loreto region) with a temporal drift using all SNPs detected by the assay (nSNP = 2909). In comparison, in an indigenous isolated area, the parasite population was genetically differentiated (FST = 0.07-0.09) with moderate diversity and high relatedness between isolates in the community. In a remote border community, a clonal P. vivax cluster was identified, with distinct haplotypes in drug resistant genes and ama1, more similar to Brazilian isolates, likely representing an introduction of P. vivax from Brazil at that time. To test its applicability for Latin America, we evaluated the SNP Peru barcode in P. vivax genomes from the region and demonstrated the capacity to capture local population clustering at within-country level.

CONCLUSIONS/SIGNIFICANCE

Together this data shows that P. vivax transmission is heterogeneous in different settings within the Peruvian Amazon. Genetic analysis is a key component for regional malaria control, offering valuable insights that should be incorporated into routine surveillance.

Temporal and spatial dynamics of Plasmodium falciparum clonal lineages in Guyana

Plasmodium parasites, the causal agents of malaria, are eukaryotic organisms that obligately undergo sexual recombination within mosquitoes. In low transmission settings, parasites recombine with themselves, and the clonal lineage is propagated rather than broken up by outcrossing. We investigated whether stochastic/neutral factors drive the persistence and abundance of Plasmodium falciparum clonal lineages in Guyana, a country with relatively low malaria transmission, but the only setting in the Americas in which an important artemisinin resistance mutation (pfk13 C580Y) has been observed. We performed whole genome sequencing on 1,727 Plasmodium falciparum samples collected from infected patients across a five-year period (2016-2021). We characterized the relatedness between each pair of monoclonal infections (n = 1,409) through estimation of identity-by-descent (IBD) and also typed each sample for known or candidate drug resistance mutations. A total of 160 multi-isolate clones (mean IBD ≥ 0.90) were circulating in Guyana during the study period, comprising 13 highly related clusters (mean IBD ≥ 0.40). In the five-year study period, we observed a decrease in frequency of a mutation associated with artemisinin partner drug (piperaquine) resistance (pfcrt C350R) and limited co-occurence of pfcrt C350R with duplications of plasmepsin 2/3, an epistatic interaction associated with piperaquine resistance. We additionally observed 61 nonsynonymous substitutions that increased markedly in frequency over the study period as well as a novel pfk13 mutation (G718S). However, P. falciparum clonal dynamics in Guyana appear to be largely driven by stochastic factors, in contrast to other geographic regions, given that clones carrying drug resistance polymorphisms do not demonstrate enhanced persistence or higher abundance than clones carrying polymorphisms of comparable frequency that are unrelated to resistance. The use of multiple artemisinin combination therapies in Guyana may have contributed to the disappearance of the pfk13 C580Y mutation.

Genomics reveals heterogeneous Plasmodium falciparum transmission and selection signals in Zambia

BACKGROUND

Genomic surveillance is crucial for monitoring malaria transmission and understanding parasite adaptation to interventions. Zambia lacks prior nationwide efforts in malaria genomic surveillance among African countries.

METHODS

We conducted genomic surveillance of Plasmodium falciparum parasites from the 2018 Malaria Indicator Survey in Zambia, a nationally representative household survey of children under five years of age. We whole-genome sequenced and analyzed 241 P. falciparum genomes from regions with varying levels of malaria transmission across Zambia and estimated genetic metrics that are informative about transmission intensity, genetic relatedness between parasites, and selection.

RESULTS

We provide genomic evidence of widespread within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in Zambia. Our analysis reveals country-level clustering of parasites from Zambia and neighboring regions, with distinct separation in West Africa. Within Zambia, identity by descent (IBD) relatedness analysis uncovers local spatial clustering and rare cases of long-distance sharing of closely related parasite pairs. Genomic regions with large shared IBD segments and strong positive selection signatures implicate genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Furthermore, differences in selection signatures, including drug resistance loci, are observed between eastern and western Zambian parasite populations, suggesting variable transmission intensity and ongoing drug pressure.

CONCLUSIONS

Our findings enhance our understanding of nationwide P. falciparum transmission in Zambia, establishing a baseline for analyzing parasite genetic metrics as they vary over time and space. These insights highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.

Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Population genomic evidence of structured and connected Plasmodium vivax populations under host selection in Latin America

Pathogen genomic epidemiology has the potential to provide a deep understanding of population dynamics, facilitating strategic planning of interventions, monitoring their impact, and enabling timely responses, and thereby supporting control and elimination efforts of parasitic tropical diseases. Plasmodium vivax, responsible for most malaria cases outside Africa, shows high genetic diversity at the population level, driven by factors like sub-patent infections, a hidden reservoir of hypnozoites, and early transmission to mosquitoes. While Latin America has made significant progress in controlling Plasmodium falciparum, it faces challenges with residual P. vivax. To characterize genetic diversity and population structure and dynamics, we have analyzed the largest collection of P. vivax genomes to date, including 1474 high-quality genomes from 31 countries across Asia, Africa, Oceania, and America. While P. vivax shows high genetic diversity globally, Latin American isolates form a distinctive population, which is further divided into sub-populations and occasional clonal pockets. Genetic diversity within the continent was associated with the intensity of transmission. Population differentiation exists between Central America and the North Coast of South America, vs. the Amazon Basin, with significant gene flow within the Amazon Basin, but limited connectivity between the Northwest Coast and the Amazon Basin. Shared genomic regions in these parasite populations indicate adaptive evolution, particularly in genes related to DNA replication, RNA processing, invasion, and motility - crucial for the parasite's survival in diverse environments. Understanding these population-level adaptations is crucial for effective control efforts, offering insights into potential mechanisms behind drug resistance, immune evasion, and transmission dynamics.

Genomic surveillance of malaria parasites in an indigenous community in the Peruvian Amazon

Hard-to-reach communities represent Peru's main challenge for malaria elimination, but information about transmission in these areas is scarce. Here, we assessed Plasmodium vivax (Pv) and P. falciparum (Pf) transmission dynamics, resistance markers, and Pf hrp2/3 deletions in Nueva Jerusalén (NJ), a remote, indigenous community in the Peruvian Amazon with high population mobility. We collected samples from November 2019 to May 2020 by active (ACD) and passive case detection (PCD) in NJ. Parasites were identified with microscopy and PCR. Then, we analyzed a representative set of positive-PCR samples (Pv = 68, Pf = 58) using highly-multiplexed deep sequencing assays (AmpliSeq) and compared NJ parasites with ones from other remote Peruvian areas using population genetics indexes. The ACD intervention did not reduce malaria cases in the short term, and persistent malaria transmission was observed (at least one Pv infection was detected in 96% of the study days). In Nueva Jerusalen, the Pv population had modest genetic diversity (He = 0.27). Pf population had lower diversity (He = 0.08) and presented temporal clustering, one of these clusters linked to an outbreak in February 2020. Moreover, Pv and Pf parasites from NJ exhibited variable levels of differentiation (Pv Fst = -0.52 & Pf Fst = 0.11-0.58) with parasites from other remote areas. No artemisin resistance mutations but chloroquine (57%) and sulfadoxine-pyrimethamine (35-67%) were detected in NJ's Pf parasites. Moreover, pfhrp2/3 gene deletions were common (32-50% of parasites with one or both genes deleted). The persistent Pv transmission and the detection of a Pf outbreak with parasites genetically distinct from the local ones highlight the need for tailored interventions focusing on mobility patterns and imported infections in remote areas to eliminate malaria in the Peruvian Amazon.

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of antimalarial drug resistance

The establishment and spread of antimalarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Genomics reveals heterogeneous Plasmodium falciparum transmission and population differentiation in Zambia and bordering countries

Genomic surveillance plays a critical role in monitoring malaria transmission and understanding how the parasite adapts in response to interventions. We conducted genomic surveillance of malaria by sequencing 241 Plasmodium falciparum genomes from regions with varying levels of malaria transmission across Zambia. We found genomic evidence of high levels of within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in the country. We identified country-level clustering of parasites from Zambia and neighboring countries, and distinct clustering of parasites from West Africa. Within Zambia, our identity by descent (IBD) relatedness analysis uncovered spatial clustering of closely related parasite pairs at the local level and rare cases of long-distance sharing. Genomic regions with large shared IBD segments and strong positive selection signatures identified genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Together, our findings enhance our understanding of P. falciparum transmission nationwide in Zambia and highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.

Investigation of an airport-associated cluster of falciparum malaria in Frankfurt, Germany, 2022

Airport malaria is uncommon but increasing in Europe and often difficult to diagnose. We describe the clinical, epidemiological and environmental investigations of a cluster of airport malaria cases and measures taken in response. Three Frankfurt International Airport employees without travel histories to malaria-endemic areas were diagnosed with Plasmodium falciparum malaria in Germany in 2022. Two cases were diagnosed within 1 week, and the third one after 10 weeks. Two cases had severe disease, all three recovered fully. The cases worked in separate areas and no specific location for the transmissions could be identified. No additional cases were detected among airport employees. In June and July, direct flights from Equatorial Guinea, Nigeria and Angola and one parcel originating in Ghana arrived at Frankfurt airport. No vector-competent mosquitoes could be trapped to identify the source of the outbreak. Whole genome sequencing of P. falciparum genomes showed a high genetic relatedness between samples of the three cases and suggested the geographical origin closest to Ghana. A diagnosis of airport malaria should prompt appropriate and comprehensive outbreak investigations to identify the source and to prevent severe forms of falciparum malaria.

Temporal and spatial dynamics of Plasmodium falciparum clonal lineages in Guyana

Plasmodium parasites, the causal agents of malaria, are eukaryotic organisms that obligately undergo sexual recombination within mosquitoes. However, in low transmission settings where most mosquitoes become infected with only a single parasite clone, parasites recombine with themselves, and the clonal lineage is propagated rather than broken up by outcrossing. We investigated whether stochastic/neutral factors drive the persistence and abundance of Plasmodium falciparum clonal lineages in Guyana, a country with relatively low malaria transmission, but the only setting in the Americas in which an important artemisinin resistance mutation (pfk13 C580Y) has been observed. To investigate whether this clonality was potentially associated with the persistence and spatial spread of the mutation, we performed whole genome sequencing on 1,727 Plasmodium falciparum samples collected from infected patients across a five-year period (2016-2021). We characterized the relatedness between each pair of monoclonal infections (n=1,409) through estimation of identity by descent (IBD) and also typed each sample for known or candidate drug resistance mutations. A total of 160 clones (mean IBD ≥ 0.90) were circulating in Guyana during the study period, comprising 13 highly related clusters (mean IBD ≥ 0.40). In the five-year study period, we observed a decrease in frequency of a mutation associated with artemisinin partner drug (piperaquine) resistance (pfcrt C350R) and limited co-occurence of pfcrt C350R with duplications of plasmepsin 2/3, an epistatic interaction associated with piperaquine resistance. We additionally report polymorphisms exhibiting evidence of selection for drug resistance or other phenotypes and reported a novel pfk13 mutation (G718S) as well as 61 nonsynonymous substitutions that increased markedly in frequency. However, P. falciparum clonal dynamics in Guyana appear to be largely driven by stochastic factors, in contrast to other geographic regions. The use of multiple artemisinin combination therapies in Guyana may have contributed to the disappearance of the pfk13 C580Y mutation.

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of anti-malarial drug resistance

The establishment and spread of anti-malarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in Sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal

We here analyze data from the first year of an ongoing nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal. The analysis is based on 1097 samples collected at health facilities during passive malaria case detection in 2019; it provides a baseline for analyzing parasite genetic metrics as they vary over time and geographic space. The study's goal was to identify genetic metrics that were informative about transmission intensity and other aspects of transmission dynamics, focusing on measures of genetic relatedness between parasites. We found the best genetic proxy for local malaria incidence to be the proportion of polygenomic infections (those with multiple genetically distinct parasites), although this relationship broke down at low incidence. The proportion of related parasites was less correlated with incidence while local genetic diversity was uninformative. The type of relatedness could discriminate local transmission patterns: two nearby areas had similarly high fractions of relatives, but one was dominated by clones and the other by outcrossed relatives. Throughout Senegal, 58% of related parasites belonged to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci and at one novel locus, reflective of ongoing selection pressure.

Whole-genome surveillance identifies markers of Plasmodium falciparum drug resistance and novel genomic regions under selection in Mozambique

IMPORTANCE

Malaria is a devastating disease caused by Plasmodium parasites. The evolution of parasite drug resistance continues to hamper progress toward malaria elimination, and despite extensive efforts to control malaria, it remains a leading cause of death in Mozambique and other countries in the region. The development of successful vaccines and identification of molecular markers to track drug efficacy are essential for managing the disease burden. We present an analysis of the parasite genome in Mozambique, a country with one of the highest malaria burdens globally and limited available genomic data, revealing current selection pressure. We contribute additional evidence to limited prior studies supporting the effectiveness of SWGA in producing reliable genomic data from complex clinical samples. Our results provide the identity of genomic loci that may be associated with current antimalarial drug use, including artemisinin and lumefantrine, and reveal selection pressure predicted to compromise the efficacy of current vaccine candidates.

Strong Positive Selection Biases Identity-By-Descent-Based Inferences of Recent Demography and Population Structure in Plasmodium falciparum

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD). Yet, strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we utilized simulations, a true IBD inference algorithm, and empirical datasets from different malaria transmission settings to investigate the extent of such bias and explore potential correction strategies. We analyzed whole genome sequence data generated from 640 new and 4,026 publicly available Plasmodium falciparum clinical isolates. Our findings demonstrated that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discovered that the removal of IBD peak regions partially restored the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Temporal and spatial analysis of Plasmodium falciparum genomics reveals patterns of parasite connectivity in a low-transmission district in Southern Province, Zambia

BACKGROUND

Understanding temporal and spatial dynamics of malaria transmission will help to inform effective interventions and strategies in regions approaching elimination. Parasite genomics are increasingly used to monitor epidemiologic trends, including assessing residual transmission across seasons and importation of malaria into these regions.

METHODS

In a low and seasonal transmission setting of southern Zambia, a total of 441 Plasmodium falciparum samples collected from 8 neighbouring health centres between 2012 and 2018 were genotyped using molecular inversion probes (MIPs n = 1793) targeting a total of 1832 neutral and geographically informative SNPs distributed across the parasite genome. After filtering for quality and missingness, 302 samples and 1410 SNPs were retained and used for downstream population genomic analyses.

RESULTS

The analyses revealed most (67%, n = 202) infections harboured one clone (monogenomic) with some variation at local level suggesting low, but heterogenous malaria transmission. Relatedness identity-by-descent (IBD) analysis revealed variable distribution of IBD segments across the genome and 6% of pairs were highly-related (IBD ≥ 0.25). Some of the highly-related parasite populations persisted across multiple seasons, suggesting that persistence of malaria in this low-transmission region is fueled by parasites "seeding" across the dry season. For recent years, clusters of clonal parasites were identified that were dissimilar to the general parasite population, suggesting parasite populations were increasingly fragmented at small spatial scales due to intensified control efforts. Clustering analysis using PCA and t-SNE showed a lack of substantial parasite population structure.

CONCLUSION

Leveraging both genomic and epidemiological data provided comprehensive picture of fluctuations in parasite populations in this pre-elimination setting of southern Zambia over 7 years.

Chloroquine resistance evolution in Plasmodium falciparum is mediated by the putative amino acid transporter AAT1

Malaria parasites break down host haemoglobin into peptides and amino acids in the digestive vacuole for export to the parasite cytoplasm for growth: interrupting this process is central to the mode of action of several antimalarial drugs. Mutations in the chloroquine (CQ) resistance transporter, pfcrt, located in the digestive vacuole membrane, confer CQ resistance in Plasmodium falciparum, and typically also affect parasite fitness. However, the role of other parasite loci in the evolution of CQ resistance is unclear. Here we use a combination of population genomics, genetic crosses and gene editing to demonstrate that a second vacuolar transporter plays a key role in both resistance and compensatory evolution. Longitudinal genomic analyses of the Gambian parasites revealed temporal signatures of selection on a putative amino acid transporter (pfaat1) variant S258L, which increased from 0% to 97% in frequency between 1984 and 2014 in parallel with the pfcrt1 K76T variant. Parasite genetic crosses then identified a chromosome 6 quantitative trait locus containing pfaat1 that is selected by CQ treatment. Gene editing demonstrated that pfaat1 S258L potentiates CQ resistance but at a cost of reduced fitness, while pfaat1 F313S, a common southeast Asian polymorphism, reduces CQ resistance while restoring fitness. Our analyses reveal hidden complexity in CQ resistance evolution, suggesting that pfaat1 may underlie regional differences in the dynamics of resistance evolution, and modulate parasite resistance or fitness by manipulating the balance between both amino acid and drug transport.

Multiplexed ddPCR-amplicon sequencing reveals isolated Plasmodium falciparum populations amenable to local elimination in Zanzibar, Tanzania

Zanzibar has made significant progress toward malaria elimination, but recent stagnation requires novel approaches. We developed a highly multiplexed droplet digital PCR (ddPCR)-based amplicon sequencing method targeting 35 microhaplotypes and drug-resistance loci, and successfully sequenced 290 samples from five districts covering both main islands. Here, we elucidate fine-scale Plasmodium falciparum population structure and infer relatedness and connectivity of infections using an identity-by-descent (IBD) approach. Despite high genetic diversity, we observe pronounced fine-scale spatial and temporal parasite genetic structure. Clusters of near-clonal infections on Pemba indicate persistent local transmission with limited parasite importation, presenting an opportunity for local elimination efforts. Furthermore, we observe an admixed parasite population on Unguja and detect a substantial fraction (2.9%) of significantly related infection pairs between Zanzibar and the mainland, suggesting recent importation. Our study provides a high-resolution view of parasite genetic structure across the Zanzibar archipelago and provides actionable insights for prioritizing malaria elimination efforts.

Performance of SNP barcodes to determine genetic diversity and population structure of Plasmodium falciparum in Africa

Panels of informative biallelic single nucleotide polymorphisms (SNPs) have been proposed to be an economical method to fast-track the population genetic analysis of Plasmodium falciparum in malaria-endemic areas. Whilst used successfully in low-transmission areas where infections are monoclonal and highly related, we present the first study to evaluate the performance of these 24- and 96-SNP molecular barcodes in African countries, characterised by moderate-to-high transmission, where multiclonal infections are prevalent. For SNP barcodes it is generally recommended that the SNPs chosen i) are biallelic, ii) have a minor allele frequency greater than 0.10, and iii) are independently segregating, to minimise bias in the analysis of genetic diversity and population structure. Further, to be standardised and used in many population genetic studies, these barcodes should maintain characteristics i) to iii) across various iv) geographies and v) time points. Using haplotypes generated from the MalariaGEN P. falciparum Community Project version six database, we investigated the ability of these two barcodes to fulfil these criteria in moderate-to-high transmission African populations in 25 sites across 10 countries. Predominantly clinical infections were analysed, with 52.3% found to be multiclonal, generating high proportions of mixed-allele calls (MACs) per isolate thereby impeding haplotype construction. Of the 24- and 96-SNPs, loci were removed if they were not biallelic and had low minor allele frequencies in all study populations, resulting in 20- and 75-SNP barcodes respectively for downstream population genetics analysis. Both SNP barcodes had low expected heterozygosity estimates in these African settings and consequently biased analyses of similarity. Both minor and major allele frequencies were temporally unstable. These SNP barcodes were also shown to identify weak genetic differentiation across large geographic distances based on Mantel Test and DAPC. These results demonstrate that these SNP barcodes are vulnerable to ascertainment bias and as such cannot be used as a standardised approach for malaria surveillance in moderate-to-high transmission areas in Africa, where the greatest genomic diversity of P. falciparum exists at local, regional and country levels.

Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal

Parasite genetic surveillance has the potential to play an important role in malaria control. We describe here an analysis of data from the first year of an ongoing, nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal, intended to provide actionable information for malaria control efforts. Looking for a good proxy for local malaria incidence, we found that the best predictor was the proportion of polygenomic infections (those with multiple genetically distinct parasites), although that relationship broke down in very low incidence settings (r = 0.77 overall). The proportion of closely related parasites in a site was more weakly correlated ( r = -0.44) with incidence while the local genetic diversity was uninformative. Study of related parasites indicated their potential for discriminating local transmission patterns: two nearby study areas had similarly high fractions of relatives, but one area was dominated by clones and the other by outcrossed relatives. Throughout the country, 58% of related parasites proved to belong to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci as well as at one novel locus, reflective of ongoing selection pressure.

Malaria Molecular Surveillance in the Peruvian Amazon with a Novel Highly Multiplexed Plasmodium falciparum AmpliSeq Assay

Molecular surveillance for malaria has great potential to support national malaria control programs (NMCPs). To bridge the gap between research and implementation, several applications (use cases) have been identified to align research, technology development, and public health efforts. For implementation at NMCPs, there is an urgent need for feasible and cost-effective tools. We designed a new highly multiplexed deep sequencing assay (Pf AmpliSeq), which is compatible with benchtop sequencers, that allows high-accuracy sequencing with higher coverage and lower cost than whole-genome sequencing (WGS), targeting genomic regions of interest. The novelty of the assay is its high number of targets multiplexed into one easy workflow, combining population genetic markers with 13 nearly full-length resistance genes, which is applicable for many different use cases. We provide the first proof of principle for hrp2 and hrp3 deletion detection using amplicon sequencing. Initial sequence data processing can be performed automatically, and subsequent variant analysis requires minimal bioinformatic skills using any tabulated data analysis program. The assay was validated using a retrospective sample collection (n = 254) from the Peruvian Amazon between 2003 and 2018. By combining phenotypic markers and a within-country 28-single-nucleotide-polymorphism (SNP) barcode, we were able to distinguish different lineages with multiple resistance haplotypes (in dhfr, dhps, crt and mdr1) and hrp2 and hrp3 deletions, which have been increasing in recent years. We found no evidence to suggest the emergence of artemisinin (ART) resistance in Peru. These findings indicate a parasite population that is under drug pressure but is susceptible to current antimalarials and demonstrate the added value of a highly multiplexed molecular tool to inform malaria strategies and surveillance systems. IMPORTANCE While the power of next-generation sequencing technologies to inform and guide malaria control programs has become broadly recognized, the integration of genomic data for operational incorporation into malaria surveillance remains a challenge in most countries where malaria is endemic. The main obstacles include limited infrastructure, limited access to high-throughput sequencing facilities, and the need for local capacity to run an in-country analysis of genomes at a large-enough scale to be informative for surveillance. In addition, there is a lack of standardized laboratory protocols and automated analysis pipelines to generate reproducible and timely results useful for relevant stakeholders. With our standardized laboratory and bioinformatic workflow, malaria genetic surveillance data can be readily generated by surveillance researchers and malaria control programs in countries of endemicity, increasing ownership and ensuring timely results for informed decision- and policy-making.

Exploring how space, time, and sampling impact our ability to measure genetic structure across Plasmodium falciparum populations

A primary use of malaria parasite genomics is identifying highly related infections to quantify epidemiological, spatial, or temporal factors associated with patterns of transmission. For example, spatial clustering of highly related parasites can indicate foci of transmission and temporal differences in relatedness can serve as evidence for changes in transmission over time. However, for infections in settings of moderate to high endemicity, understanding patterns of relatedness is compromised by complex infections, overall high forces of infection, and a highly diverse parasite population. It is not clear how much these factors limit the utility of using genomic data to better understand transmission in these settings. In particular, further investigation is required to determine which patterns of relatedness we expect to see with high quality, densely sampled genomic data in a high transmission setting and how these observations change under different study designs, missingness, and biases in sample collection. Here we investigate two identity-by-state measures of relatedness and apply them to amplicon deep sequencing data collected as part of a longitudinal cohort in Western Kenya that has previously been analysed to identify individual-factors associated with sharing parasites with infected mosquitoes. With these data we use permutation tests, to evaluate several hypotheses about spatiotemporal patterns of relatedness compared to a null distribution. We observe evidence of temporal structure, but not of fine-scale spatial structure in the cohort data. To explore factors associated with the lack of spatial structure in these data, we construct a series of simplified simulation scenarios using an agent based model calibrated to entomological, epidemiological and genomic data from this cohort study to investigate whether the lack of spatial structure observed in the cohort could be due to inherent power limitations of this analytical method. We further investigate how our hypothesis testing behaves under different sampling schemes, levels of completely random and systematic missingness, and different transmission intensities.

Measurably recombining malaria parasites

Genomic epidemiology has guided research and policy for various viral pathogens and there has been a parallel effort towards using genomic epidemiology to combat diseases that are caused by eukaryotic pathogens, such as the malaria parasite. However, the central concept of viral genomic epidemiology, namely that of measurably mutating pathogens, does not apply easily to sexually recombining parasites. Here we introduce the related but different concept of measurably recombining malaria parasites to promote convergence around a unifying theoretical framework for malaria genomic epidemiology. Akin to viral phylodynamics, we anticipate that an inferential framework developed around recombination will help guide practical research and thus realize the full public health potential of genomic epidemiology for malaria parasites and other sexually recombining pathogens.

Resolving drug selection and migration in an inbred South American Plasmodium falciparum population with identity-by-descent analysis

The human malaria parasite Plasmodium falciparum is globally widespread, but its prevalence varies significantly between and even within countries. Most population genetic studies in P. falciparum focus on regions of high transmission where parasite populations are large and genetically diverse, such as sub-Saharan Africa. Understanding population dynamics in low transmission settings, however, is of particular importance as these are often where drug resistance first evolves. Here, we use the Pacific Coast of Colombia and Ecuador as a model for understanding the population structure and evolution of Plasmodium parasites in small populations harboring less genetic diversity. The combination of low transmission and a high proportion of monoclonal infections means there are few outcrossing events and clonal lineages persist for long periods of time. Yet despite this, the population is evolutionarily labile and has successfully adapted to changes in drug regime. Using newly sequenced whole genomes, we measure relatedness between 166 parasites, calculated as identity by descent (IBD), and find 17 distinct but highly related clonal lineages, six of which have persisted in the region for at least a decade. This inbred population structure is captured in more detail with IBD than with other common population structure analyses like PCA, ADMIXTURE, and distance-based trees. We additionally use patterns of intra-chromosomal IBD and an analysis of haplotypic variation to explore past selection events in the region. Two genes associated with chloroquine resistance, crt and aat1, show evidence of hard selective sweeps, while selection appears soft and/or incomplete at three other key resistance loci (dhps, mdr1, and dhfr). Overall, this work highlights the strength of IBD analyses for studying parasite population structure and resistance evolution in regions of low transmission, and emphasizes that drug resistance can evolve and spread in small populations, as will occur in any region nearing malaria elimination.

Plasmodium falciparum merozoite invasion ligands, linked antimalarial resistance loci and ex vivo responses to antimalarials in The Gambia

BACKGROUND

Artemether/lumefantrine is the most commonly used artemisinin-based combination treatment (ACT) for malaria in sub-Saharan Africa. Drug resistance to ACT components is a major threat to malaria elimination efforts. Therefore, rigorous monitoring of drug efficacy is required for adequate management of malaria and to sustain the effectiveness of ACTs.

OBJECTIVES

This study identified and described genomic loci that correlate with differences in ex vivo responses of natural Plasmodium falciparum isolates from The Gambia to antimalarial drugs.

METHODS

Natural P. falciparum isolates from The Gambia were assayed for IC50 responses to four antimalarial drugs (artemether, dihydroartemisinin, amodiaquine and lumefantrine). Genome-wide SNPs from 56 of these P. falciparum isolates were applied to mixed-model regression and network analyses to determine linked loci correlating with drug responses. Genomic regions of shared haplotypes and positive selection within and between Gambian and Cambodian P. falciparum isolates were mapped by identity-by-descent (IBD) analysis of 209 genomes.

RESULTS

SNPs in 71 genes, mostly involved in stress and drug resistance mechanisms correlated with drug responses. Additionally, erythrocyte invasion and permeability loci, including merozoite surface proteins (Pfdblmsp, Pfsurfin), and high-molecular-weight rhoptry protein 2 (Pfrhops2) were correlated with responses to multiple drugs. Haplotypes of pfdblmsp2 and known drug resistance loci (pfaat1, pfcrt and pfdhfr) from The Gambia showed high IBD with those from Cambodia, indicating co-ancestry, with significant linkage disequilibrium between their alleles.

CONCLUSIONS

Multiple linked genic loci correlating with drug response phenotypes suggest a genomic backbone may be under selection by antimalarials. This calls for further analysis of molecular pathways to drug resistance in African P. falciparum.

Population genomics in neglected malaria parasites

Malaria elimination includes neglected human malaria parasites Plasmodium vivax, Plasmodium ovale spp., and Plasmodium malariae. Biological features such as association with low-density infection and the formation of hypnozoites responsible for relapse make their elimination challenging. Studies on these parasites rely primarily on clinical samples due to the lack of long-term culture techniques. With improved methods to enrich parasite DNA from clinical samples, whole-genome sequencing of the neglected malaria parasites has gained increasing popularity. Population genomics of more than 2200 P. vivax global isolates has improved our knowledge of parasite biology and host-parasite interactions, identified vaccine targets and potential drug resistance markers, and provided a new way to track parasite migration and introduction and monitor the evolutionary response of local populations to elimination efforts. Here, we review advances in population genomics for neglected malaria parasites, discuss how the rich genomic information is being used to understand parasite biology and epidemiology, and explore opportunities for the applications of malaria genomic data in malaria elimination practice.

Dcifer: an IBD-based method to calculate genetic distance between polyclonal infections

An essential step toward reconstructing pathogen transmission and answering epidemiologically relevant questions from genomic data is obtaining pairwise genetic distance between infections. For recombining organisms such as malaria parasites, relatedness measures quantifying recent shared ancestry would provide a meaningful distance, suggesting methods based on identity by descent (IBD). While the concept of relatedness and consequently an IBD approach is fairly straightforward for individual parasites, the distance between polyclonal infections, which are prevalent in malaria, presents specific challenges, and awaits a general solution that could be applied to infections of any clonality and accommodate multiallelic (e.g. microsatellite or microhaplotype) and biallelic [single nucleotide polymorphism (SNP)] data. Filling this methodological gap, we present Dcifer (Distance for complex infections: fast estimation of relatedness), a method for calculating genetic distance between polyclonal infections, which is designed for unphased data, explicitly accounts for population allele frequencies and complexity of infection, and provides reliable inference. Dcifer’s IBD-based framework allows us to define model parameters that represent interhost relatedness and to propose corresponding estimators with attractive statistical properties. By using combinatorics to account for unobserved phased haplotypes, Dcifer is able to quickly process large datasets and estimate pairwise relatedness along with measures of uncertainty. We show that Dcifer delivers accurate and interpretable results and detects related infections with statistical power that is 2–4 times greater than that of approaches based on identity by state. Applications to real data indicate that relatedness structure aligns with geographic locations. Dcifer is implemented in a comprehensive publicly available software package.

Novel highly-multiplexed AmpliSeq targeted assay for Plasmodium vivax genetic surveillance use cases at multiple geographical scales

Although the power of genetic surveillance tools has been acknowledged widely, there is an urgent need in malaria endemic countries for feasible and cost-effective tools to implement in national malaria control programs (NMCPs) that can generate evidence to guide malaria control and elimination strategies, especially in the case of Plasmodium vivax. Several genetic surveillance applications (‘use cases’) have been identified to align research, technology development, and public health efforts, requiring different types of molecular markers. Here we present a new highly-multiplexed deep sequencing assay (Pv AmpliSeq). The assay targets the 33-SNP vivaxGEN-geo panel for country-level classification, and a newly designed 42-SNP within-country barcode for analysis of parasite dynamics in Vietnam and 11 putative drug resistance genes in a highly multiplexed NGS protocol with easy workflow, applicable for many different genetic surveillance use cases. The Pv AmpliSeq assay was validated using: 1) isolates from travelers and migrants in Belgium, and 2) routine collections of the national malaria control program at sentinel sites in Vietnam. The assay targets 229 amplicons and achieved a high depth of coverage (mean 595.7 ± 481) and high accuracy (mean error-rate of 0.013 ± 0.007). P. vivax parasites could be characterized from dried blood spots with a minimum of 5 parasites/µL and 10% of minority-clones. The assay achieved good spatial specificity for between-country prediction of origin using the 33-SNP vivaxGEN-geo panel that targets rare alleles specific for certain countries and regions. A high resolution for within-country diversity in Vietnam was achieved using the designed 42-SNP within-country barcode that targets common alleles (median MAF 0.34, range 0.01-0.49. Many variants were detected in (putative) drug resistance genes, with different predominant haplotypes in the pvmdr1 and pvcrt genes in different provinces in Vietnam. The capacity of the assay for high resolution identity-by-descent (IBD) analysis was demonstrated and identified a high rate of shared ancestry within Gia Lai Province in the Central Highlands of Vietnam, as well as between the coastal province of Binh Thuan and Lam Dong. Our approach performed well in geographically differentiating isolates at multiple spatial scales, detecting variants in putative resistance genes, and can be easily adjusted to suit the needs in other settings in a country or region. We prioritize making this tool available to researchers and NMCPs in endemic countries to increase ownership and ensure data usage for decision-making and malaria policy.

Genomic epidemiological models describe pathogen evolution across fitness valleys

Genomics is fundamentally changing epidemiological research. However, systematically exploring hypotheses in pathogen evolution requires new modeling tools. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmissibility or resistance to treatment. In this work, we present Opqua, a flexible simulation framework that explicitly links epidemiology to sequence evolution and selection. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high-transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling of selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

Prospective surveillance study to detect antimalarial drug resistance, gene deletions of diagnostic relevance and genetic diversity of Plasmodium falciparum in Mozambique: protocol

INTRODUCTION

Genomic data constitute a valuable adjunct to routine surveillance that can guide programmatic decisions to reduce the burden of infectious diseases. However, genomic capacities remain low in Africa. This study aims to operationalise a functional malaria molecular surveillance system in Mozambique for guiding malaria control and elimination.

METHODS AND ANALYSES

This prospective surveillance study seeks to generate Plasmodium falciparum genetic data to (1) monitor molecular markers of drug resistance and deletions in rapid diagnostic test targets; (2) characterise transmission sources in low transmission settings and (3) quantify transmission levels and the effectiveness of antimalarial interventions. The study will take place across 19 districts in nine provinces (Maputo city, Maputo, Gaza, Inhambane, Niassa, Manica, Nampula, Zambézia and Sofala) which span a range of transmission strata, geographies and malaria intervention types. Dried blood spot samples and rapid diagnostic tests will be collected across the study districts in 2022 and 2023 through a combination of dense (all malaria clinical cases) and targeted (a selection of malaria clinical cases) sampling. Pregnant women attending their first antenatal care visit will also be included to assess their value for molecular surveillance. We will use a multiplex amplicon-based next-generation sequencing approach targeting informative single nucleotide polymorphisms, gene deletions and microhaplotypes. Genetic data will be incorporated into epidemiological and transmission models to identify the most informative relationship between genetic features, sources of malaria transmission and programmatic effectiveness of new malaria interventions. Strategic genomic information will be ultimately integrated into the national malaria information and surveillance system to improve the use of the genetic information for programmatic decision-making.

ETHICS AND DISSEMINATION

The protocol was reviewed and approved by the institutional (CISM) and national ethics committees of Mozambique (Comité Nacional de Bioética para Saúde) and Spain (Hospital Clinic of Barcelona). Project results will be presented to all stakeholders and published in open-access journals.

TRIAL REGISTRATION NUMBER

NCT05306067.

Two fatal autochthonous cases of airport malaria, Belgium, 2020

We report an outbreak investigation of two fatal cases of autochthonous Plasmodium falciparum malaria that occurred in Belgium in September 2020. Various hypotheses of the potential source of infection were investigated. The most likely route of transmission was through an infectious exotic Anopheles mosquito that was imported via the international airport of Brussels or the military airport Melsbroek and infected the cases who lived at 5 km from the airports. Based on genomic analysis of the parasites collected from the two cases, the most likely origin of the Plasmodium was Gabon or Cameroon. Further, the parasites collected from the two Belgian patients were identical by descent, which supports the assumption that the two infections originated from the bite of the same mosquito, during interrupted feeding. Although airport malaria remains a rare event, it has significant implications, particularly for the patient, as delayed or missed diagnosis of the cause of illness often results in complications and mortality. Therefore, to prevent such severe or fatal outcomes, we suggest a number of public health actions including increased awareness among health practitioners, especially those working in the vicinity of airports, and increased surveillance of exotic mosquito species at airports.

Design and implementation of multiplexed amplicon sequencing panels to serve genomic epidemiology of infectious disease: a malaria case study

Multiplexed PCR amplicon sequencing (AmpSeq) is an increasingly popular application for cost-effective monitoring of threatened species and managed wildlife populations, and shows strong potential for genomic epidemiology of infectious disease. AmpSeq data from infectious microbes can inform disease control in multiple ways, including measuring drug resistance marker prevalence, distinguishing imported from local cases, and determining the effectiveness of therapeutics. We describe the design and comparative evaluation of two new AmpSeq assays for Plasmodium falciparum malaria parasites: a four-locus panel ('4CAST') composed of highly diverse antigens, and a 129-locus panel ('AMPLseq') composed of drug resistance markers, highly diverse loci for inferring relatedness, and a locus to detect Plasmodium vivax co-infection. We explore the performance of each panel in various public health use cases with in silico simulations as well as empirical experiments. The 4CAST panel appears highly suitable for evaluating the number of distinct parasite strains within samples (complexity of infection), showing strong performance across a wide range of parasitemia levels without a DNA pre-amplification step. For relatedness inference, the larger AMPLseq panel performs similarly to two existing panels of comparable size, despite differences in the data and approach used for designing each panel. Finally, we describe an R package (paneljudge) that facilitates the design and comparative evaluation of genetic panels for relatedness estimation, and we provide general guidance on the design and implementation of AmpSeq panels for genomic epidemiology of infectious disease.

Global diversity and balancing selection of 23 leading Plasmodium falciparum candidate vaccine antigens

Investigation of the diversity of malaria parasite antigens can help prioritize and validate them as vaccine candidates and identify the most common variants for inclusion in vaccine formulations. Studies of vaccine candidates of the most virulent human malaria parasite, Plasmodium falciparum, have focused on a handful of well-known antigens, while several others have never been studied. Here we examine the global diversity and population structure of leading vaccine candidate antigens of P. falciparum using the MalariaGEN Pf3K (version 5.1) resource, comprising more than 2600 genomes from 15 malaria endemic countries. A stringent variant calling pipeline was used to extract high quality antigen gene 'haplotypes' from the global dataset and a new R-package named VaxPack was used to streamline population genetic analyses. In addition, a newly developed algorithm that enables spatial averaging of selection pressure on 3D protein structures was applied to the dataset. We analysed the genes encoding 23 leading and novel candidate malaria vaccine antigens including csp, trap, eba175, ama1, rh5, and CelTOS. Our analysis shows that current malaria vaccine formulations are based on rare haplotypes and thus may have limited efficacy against natural parasite populations. High levels of diversity with evidence of balancing selection was detected for most of the erythrocytic and pre-erythrocytic antigens. Measures of natural selection were then mapped to 3D protein structures to predict targets of functional antibodies. For some antigens, geographical variation in the intensity and distribution of these signals on the 3D structure suggests adaptation to different human host or mosquito vector populations. This study provides an essential framework for the diversity of P. falciparum antigens to be considered in the design of the next generation of malaria vaccines.

Population-level genome-wide STR discovery and validation for population structure and genetic diversity assessment of Plasmodium species

Short tandem repeats (STRs) are highly informative genetic markers that have been used extensively in population genetics analysis. They are an important source of genetic diversity and can also have functional impact. Despite the availability of bioinformatic methods that permit large-scale genome-wide genotyping of STRs from whole genome sequencing data, they have not previously been applied to sequencing data from large collections of malaria parasite field samples. Here, we have genotyped STRs using HipSTR in more than 3,000 Plasmodium falciparum and 174 Plasmodium vivax published whole-genome sequence data from samples collected across the globe. High levels of noise and variability in the resultant callset necessitated the development of a novel method for quality control of STR genotype calls. A set of high-quality STR loci (6,768 from P. falciparum and 3,496 from P. vivax) were used to study Plasmodium genetic diversity, population structures and genomic signatures of selection and these were compared to genome-wide single nucleotide polymorphism (SNP) genotyping data. In addition, the genome-wide information about genetic variation and other characteristics of STRs in P. falciparum and P. vivax have been available in an interactive web-based R Shiny application PlasmoSTR (https://github.com/bahlolab/PlasmoSTR).

Genetic surveillance for monitoring the impact of drug use on Plasmodium falciparum populations

The use of antimalarial drugs is an effective strategy in the fight against malaria. However, selection of drug resistant parasites is a constant threat to the continued use of this approach. Antimalarial drugs are used not only to treat infections but also as part of population-level strategies to reduce malaria transmission toward elimination. While there is strong evidence that the ongoing use of antimalarial drugs increases the risk of the emergence and spread of drug-resistant parasites, it is less clear how population-level use of drug-based interventions like seasonal malaria chemoprevention (SMC) or mass drug administration (MDA) may contribute to drug resistance or loss of drug efficacy. Critical to sustained use of drug-based strategies for reducing the burden of malaria is the surveillance of population-level signals related to transmission reduction and resistance selection. Here we focus on Plasmodium falciparum and discuss the genetic signatures of a parasite population that are correlated with changes in transmission and related to drug pressure and resistance as a result of drug use. We review the evidence for MDA and SMC contributing to malaria burden reduction and drug resistance selection and examine the use and impact of these interventions in Senegal. Throughout we consider best strategies for ongoing surveillance of both population and resistance signals in the context of different parasite population parameters. Finally, we propose a roadmap for ongoing surveillance during population-level drug-based interventions to reduce the global malaria burden.

Advances and opportunities in malaria population genomics

Almost 20 years have passed since the first reference genome assemblies were published for Plasmodium falciparum, the deadliest malaria parasite, and Anopheles gambiae, the most important mosquito vector of malaria in sub-Saharan Africa. Reference genomes now exist for all human malaria parasites and nearly half of the ~40 important vectors around the world. As a foundation for genetic diversity studies, these reference genomes have helped advance our understanding of basic disease biology and drug and insecticide resistance, and have informed vaccine development efforts. Population genomic data are increasingly being used to guide our understanding of malaria epidemiology, for example by assessing connectivity between populations and the efficacy of parasite and vector interventions. The potential value of these applications to malaria control strategies, together with the increasing diversity of genomic data types and contexts in which data are being generated, raise both opportunities and challenges in the field. This Review discusses advances in malaria genomics and explores how population genomic data could be harnessed to further support global disease control efforts.

Genomic Approaches to Drug Resistance in Malaria

Although the last two decades have seen a substantial decline in malaria incidence and mortality due to the use of insecticide-treated bed nets and artemisinin combination therapy, the threat of drug resistance is a constant obstacle to sustainable malaria control. Given that patients can die quickly from this disease, public health officials and doctors need to understand whether drug resistance exists in the parasite population, as well as how prevalent it is so they can make informed decisions about treatment. As testing for drug efficacy before providing treatment to malaria patients is impractical, researchers need molecular markers of resistance that can be more readily tracked in parasite populations. To this end, much work has been done to unravel the genetic underpinnings of drug resistance in Plasmodium falciparum. The aim of this review is to provide a broad overview of common genomic approaches that have been used to discover the alleles that drive drug response phenotypes in the most lethal human malaria parasite.

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.

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.

Using deep learning to identify recent positive selection in malaria parasite sequence data

BACKGROUND

Malaria, caused by Plasmodium parasites, is a major global public health problem. To assist an understanding of malaria pathogenesis, including drug resistance, there is a need for the timely detection of underlying genetic mutations and their spread. With the increasing use of whole-genome sequencing (WGS) of Plasmodium DNA, the potential of deep learning models to detect loci under recent positive selection, historically signals of drug resistance, was evaluated.

METHODS

A deep learning-based approach (called "DeepSweep") was developed, which can be trained on haplotypic images from genetic regions with known sweeps, to identify loci under positive selection. DeepSweep software is available from https://github.com/WDee/Deepsweep .

RESULTS

Using simulated genomic data, DeepSweep could detect recent sweeps with high predictive accuracy (areas under ROC curve > 0.95). DeepSweep was applied to Plasmodium falciparum (n = 1125; genome size 23 Mbp) and Plasmodium vivax (n = 368; genome size 29 Mbp) WGS data, and the genes identified overlapped with two established extended haplotype homozygosity methods (within-population iHS, across-population Rsb) (~ 60-75% overlap of hits at P < 0.0001). DeepSweep hits included regions proximal to known drug resistance loci for both P. falciparum (e.g. pfcrt, pfdhps and pfmdr1) and P. vivax (e.g. pvmrp1).

CONCLUSION

The deep learning approach can detect positive selection signatures in malaria parasite WGS data. Further, as the approach is generalizable, it may be trained to detect other types of selection. With the ability to rapidly generate WGS data at low cost, machine learning approaches (e.g. DeepSweep) have the potential to assist parasite genome-based surveillance and inform malaria control decision-making.

Antimalarial Drug Resistance and Implications for the WHO Global Technical Strategy

PURPOSE OF REVIEW

Five years have passed since the World Health Organization released its Global Technical Strategy for Malaria (GTS). In that time, progress against malaria has plateaued. This review focuses on the implications of antimalarial drug resistance for the GTS and how interim progress in parasite genomics and antimalarial pharmacology offer a bulwark against it.

RECENT FINDINGS

For the first time, drug resistance-conferring genes have been identified and validated before their global expansion in malaria parasite populations. More efficient methods for their detection and elaboration have been developed, although low-density infections and polyclonality remain a nuisance to be solved. Clinical trials of alternative regimens for multidrug-resistant malaria have delivered promising results. New agents continue down the development pipeline, while a nascent infrastructure in sub-Saharan Africa for conducting phase I trials and trials of transmission-blocking agents has come to fruition after years of preparation.

SUMMARY

These and other developments can help inform the GTS as the world looks ahead to the next two decades of its implementation. To remain ahead of the threat that drug resistance poses, wider application of genomic-based surveillance and optimization of existing and forthcoming antimalarial drugs are essential.

Emergence of artemisinin-resistant Plasmodium falciparum with kelch13 C580Y mutations on the island of New Guinea

The rapid and aggressive spread of artemisinin-resistant Plasmodium falciparum carrying the C580Y mutation in the kelch13 gene is a growing threat to malaria elimination in Southeast Asia, but there is no evidence of their spread to other regions. We conducted cross-sectional surveys in 2016 and 2017 at two clinics in Wewak, Papua New Guinea (PNG) where we identified three infections caused by C580Y mutants among 239 genotyped clinical samples. One of these mutants exhibited the highest survival rate (6.8%) among all parasites surveyed in ring-stage survival assays (RSA) for artemisinin. Analyses of kelch13 flanking regions, and comparisons of deep sequencing data from 389 clinical samples from PNG, Indonesian Papua and Western Cambodia, suggested an independent origin of the Wewak C580Y mutation, showing that the mutants possess several distinctive genetic features. Identity by descent (IBD) showed that multiple portions of the mutants' genomes share a common origin with parasites found in Indonesian Papua, comprising several mutations within genes previously associated with drug resistance, such as mdr1, ferredoxin, atg18 and pnp. These findings suggest that a P. falciparum lineage circulating on the island of New Guinea has gradually acquired a complex ensemble of variants, including kelch13 C580Y, which have affected the parasites' drug sensitivity. This worrying development reinforces the need for increased surveillance of the evolving parasite populations on the island, to contain the spread of resistance.

SNP barcodes provide higher resolution than microsatellite markers to measure Plasmodium vivax population genetics

BACKGROUND

Genomic surveillance of malaria parasite populations has the potential to inform control strategies and to monitor the impact of interventions. Barcodes comprising large numbers of single nucleotide polymorphism (SNP) markers are accurate and efficient genotyping tools, however may need to be tailored to specific malaria transmission settings, since 'universal' barcodes can lack resolution at the local scale. A SNP barcode was developed that captures the diversity and structure of Plasmodium vivax populations of Papua New Guinea (PNG) for research and surveillance.

METHODS

Using 20 high-quality P. vivax genome sequences from PNG, a total of 178 evenly spaced neutral SNPs were selected for development of an amplicon sequencing assay combining a series of multiplex PCRs and sequencing on the Illumina MiSeq platform. For initial testing, 20 SNPs were amplified in a small number of mono- and polyclonal P. vivax infections. The full barcode was then validated by genotyping and population genetic analyses of 94 P. vivax isolates collected between 2012 and 2014 from four distinct catchment areas on the highly endemic north coast of PNG. Diversity and population structure determined from the SNP barcode data was then benchmarked against that of ten microsatellite markers used in previous population genetics studies.

RESULTS

From a total of 28,934,460 reads generated from the MiSeq Illumina run, 87% mapped to the PvSalI reference genome with deep coverage (median = 563, range 56-7586) per locus across genotyped samples. Of 178 SNPs assayed, 146 produced high-quality genotypes (minimum coverage = 56X) in more than 85% of P. vivax isolates. No amplification bias was introduced due to either polyclonal infection or whole genome amplification (WGA) of samples before genotyping. Compared to the microsatellite panels, the SNP barcode revealed greater variability in genetic diversity between populations and geographical population structure. The SNP barcode also enabled assignment of genotypes according to their geographic origins with a significant association between genetic distance and geographic distance at the sub-provincial level.

CONCLUSIONS

High-throughput SNP barcoding can be used to map variation of malaria transmission dynamics at sub-national resolution. The low cost per sample and genotyping strategy makes the transfer of this technology to field settings highly feasible.

Population genomics reveals the expansion of highly inbred Plasmodium vivax lineages in the main malaria hotspot of Brazil

BACKGROUND

Plasmodium vivax is a neglected human malaria parasite that causes significant morbidity in the Americas, the Middle East, Asia, and the Western Pacific. Population genomic approaches remain little explored to map local and regional transmission pathways of P. vivax across the main endemic sites in the Americas, where great progress has been made towards malaria elimination over the past decades.

METHODOLOGY/PRINCIPAL FINDINGS

We analyze 38 patient-derived P. vivax genome sequences from Mâncio Lima (ML)-the Amazonian malaria hotspot next to the Brazil-Peru border-and 24 sequences from two other sites in Acre State, Brazil, a country that contributes 23% of malaria cases in the Americas. We show that the P. vivax population of ML is genetically diverse (π = 4.7 × 10-4), with a high polymorphism particularly in genes encoding proteins putatively involved in red blood cell invasion. Paradoxically, however, parasites display strong genome-wide linkage disequilibrium, being fragmented into discrete lineages that are remarkably stable across time and space, with only occasional recombination between them. Using identity-by-descent approaches, we identified a large cluster of closely related sequences that comprises 16 of 38 genomes sampled in ML over 26 months. Importantly, we found significant ancestry sharing between parasites at a large geographic distance, consistent with substantial gene flow between regional P. vivax populations.

CONCLUSIONS/SIGNIFICANCE

We have characterized the sustained expansion of highly inbred P. vivax lineages in a malaria hotspot that can seed regional transmission. Potential source populations in hotspots represent a priority target for malaria elimination in the Amazon.

A cautionary note on the use of unsupervised machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices

Genetic surveillance of malaria parasites supports malaria control programmes, treatment guidelines and elimination strategies. Surveillance studies often pose questions about malaria parasite ancestry (e.g. how antimalarial resistance has spread) and employ statistical methods that characterise parasite population structure. Many of the methods used to characterise structure are unsupervised machine learning algorithms which depend on a genetic distance matrix, notably principal coordinates analysis (PCoA) and hierarchical agglomerative clustering (HAC). PCoA and HAC are sensitive to both the definition of genetic distance and algorithmic specification. Importantly, neither algorithm infers malaria parasite ancestry. As such, PCoA and HAC can inform (e.g. via exploratory data visualisation and hypothesis generation), but not answer comprehensively, key questions about malaria parasite ancestry. We illustrate the sensitivity of PCoA and HAC using 393 Plasmodium falciparum whole genome sequences collected from Cambodia and neighbouring regions (where antimalarial resistance has emerged and spread recently) and we provide tentative guidance for the use and interpretation of PCoA and HAC in malaria parasite genetic epidemiology. This guidance includes a call for fully transparent and reproducible analysis pipelines that feature (i) a clearly outlined scientific question; (ii) a clear justification of analytical methods used to answer the scientific question along with discussion of any inferential limitations; (iii) publicly available genetic distance matrices when downstream analyses depend on them; and (iv) sensitivity analyses. To bridge the inferential disconnect between the output of non-inferential unsupervised learning algorithms and the scientific questions of interest, tailor-made statistical models are needed to infer malaria parasite ancestry. In the absence of such models speculative reasoning should feature only as discussion but not as results.

Genomic and chemical evidence for local adaptation in resistance to different herbivores in Datura stramonium

Because most species are collections of genetically variable populations distributed to habitats differing in their abiotic/biotic environmental factors and community composition, the pattern and strength of natural selection imposed by species on each other's traits are also expected to be highly spatially variable. Here, we used genomic and quantitative genetic approaches to understand how spatially variable selection operates on the genetic basis of plant defenses to herbivores. To this end, an F₂ progeny was generated by crossing Datura stramonium (Solanaceae) parents from two populations differing in their level of chemical defense. This F₂ progeny was reciprocally transplanted into the parental plants' habitats and by measuring the identity by descent (IBD) relationship of each F₂ plant to each parent, we were able to elucidate how spatially variable selection imposed by herbivores operated on the genetic background (IBD) of resistance to herbivory, promoting local adaptation. The results highlight that plants possessing the highest total alkaloid concentrations (sum of all alkaloid classes) were not the most well-defended or fit. Instead, specific alkaloids and their linked loci/alleles were favored by selection imposed by different herbivores. This has led to population differentiation in plant defenses and thus, to local adaptation driven by plant-herbivore interactions.

Identity by descent analysis identifies founder events and links SOD1 familial and sporadic ALS cases

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterised by the loss of upper and lower motor neurons resulting in paralysis and eventual death. Approximately 10% of ALS cases have a family history of disease, while the remainder present as apparently sporadic cases. Heritability studies suggest a significant genetic component to sporadic ALS, and although most sporadic cases have an unknown genetic aetiology, some familial ALS mutations have also been found in sporadic cases. This suggests that some sporadic cases may be unrecognised familial cases with reduced disease penetrance in their ancestors. A powerful strategy to uncover a familial link is identity-by-descent (IBD) analysis, which detects genomic regions that have been inherited from a common ancestor. IBD analysis was performed on 83 Australian familial ALS cases from 25 families and three sporadic ALS cases, each of whom carried one of three SOD1 mutations (p.I114T, p.V149G and p.E101G). We defined five unique 350-SNP haplotypes that carry these mutations in our cohort, indicative of five founder events. This included two founder haplotypes that carry SOD1 p.I114T; linking familial and sporadic cases. We found that SOD1 p.E101G arose independently in each family that carries this mutation and linked two families that carry SOD1 p.V149G. The age of disease onset varied between cases that carried each SOD1 p.I114T haplotype. Linking families with identical ALS mutations allows for larger sample sizes and increased statistical power to identify putative phenotypic modifiers.