Sasha V. Siegel

Motivation: Rapid growth in life science data generation has led to large and increasingly distributed collections of sensitive genomic data. To analyse this data, researchers increasingly rely on computational workflows to enable scalable, portable and reproducible analysis. However, these workflows are executed by specialized workflow engines across heterogeneous compute environments, each with its own requirements. As a result, users often need engine- and compute-environment-specific knowledge to submit, monitor and manage workflow execution, increasing the barriers to interoperability. These challenges are compounded in large-scale projects, where workflow runs must be dispatched to local clusters, cloud platforms or data hosting infrastructures with different underlying technologies. Results: We describe the Global Alliance for Genomics and Health (GA4GH) Workflow Execution Service (WES) API, an approved GA4GH standard first released in 2018, together with its data model and the endpoints that define a unified interface for workflow execution. By standardizing workflow invocation, the WES API allows a single client to submit, monitor and cancel workflow runs across diverse workflow engines and compute backends, such as scheduling clusters or cloud platforms. We surveyed thirteen adoptions of the standard, covering standalone services and platforms in four programming languages. In a two-site demonstration, a WES implementation from Germany and one from Japan executed the same federated allele-frequency analysis with site-specific adjustments and only aggregated results leaving either site, demonstrating that it is possible to run the same analysis across independently built and operated WES services in different countries. From the gaps identified, we propose extensions for community discussion. Availability and implementations: The latest version of the WES API repository can be found at https://github.com/ga4gh/workflow-execution-service-schemas (DOI: https://doi.org/10.59756/m382x-ww ). The full Reference Documentation can be viewed at: https://ga4gh.github.io/workflow-execution-service-schemas/docs/ Contact: valentin.schneider-lunitz@bih-charite.de

The WES API is a standard way to run and manage portable workflows.

Plasmodium vivax elimination is challenged by dormant liver stages (hypnozoites) that can reactivate months after initial infection resulting in relapses. Relapsing infections confound antimalarial clinical efficacy trials due to the inability to distinguish between recurrences arising from blood-stage treatment failure (recrudescence), reinfection or relapse. Genetic relatedness of paired parasite isolates, measured by identity-by-descent (IBD), can provide important information on whether individuals have had single or multiple mosquito inoculations, thus informing on recurrence origin. We developed a high-throughput amplicon sequencing assay comprising 93 multi-SNP (microhaplotype) markers to determine IBD between P. vivax clinical isolates. The assay was evaluated in 745 global infections, including 128 infection pairs from a randomized controlled trial (RCT) (ClinicalTrials.gov NCT01680406). Simulations demonstrate low error in pairwise IBD estimation at the panel (RMSE < 0.12) and IBD-based networks illustrate strong clustering by geography. IBD analysis in the RCT demonstrates a lower frequency of suspected relapses or recrudescence in patients treated with primaquine compared to those without primaquine; the impact is greater when paired with chloroquine than with artemether-lumefantrine. Our results demonstrate the potential to derive new information on P. vivax treatment and transmission using IBD generated by amplicon sequencing data that can be further improved with time-to-event models.

The elimination of Plasmodium vivax is challenged by dormant liver stages (hypnozoites) that can reactivate months after initial infection resulting in relapses that enhance transmission. Relapsing infections confound antimalarial clinical efficacy trials due to the inability to distinguish between recurrences arising from blood-stage treatment failure (recrudescence), reinfection or relapse. Genetic relatedness of paired parasite isolates, measured by identity-by-descent (IBD), can provide important information on whether individuals have had single or multiple mosquito inoculations, thus informing on recurrence origin. We developed a high-throughput amplicon sequencing assay comprising 93 multi-SNP (microhaplotype) P. vivax markers to determine IBD between P. vivax clinical isolates. The assay was evaluated in 659 independent infections from the Asia-Pacific and Horn of Africa, including 108 pairs of infections from a randomized controlled trial (RCT). A bioinformatics pipeline (vivaxGEN-MicroHaps) was established to support data processing. Simulations using paneljudge demonstrated low error in pairwise IBD estimation in all countries assessed (all RMSE <0.12) and IBD-based networks illustrated strong clustering by geography. IBD analysis in the RCT demonstrated a higher frequency of suspected relapses or recrudescence in patients treated with primaquine regimens (0.84) compared to those without primaquine (0.60). Our results demonstrate the potential to derive information on P. vivax IBD using amplicon sequencing, that informs policy-relevant treatment and transmission dynamics.

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 H_E = 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.

Challenges in understanding the origin of recurrent Plasmodium vivax infections constrains the surveillance of antimalarial efficacy and transmission of this neglected parasite. Recurrent infections within an individual may arise from activation of dormant liver stages (relapse), blood-stage treatment failure (recrudescence) or new inoculations (reinfection). Molecular inference of familial relatedness (identity-by-descent or IBD) based on whole genome sequence data, together with analysis of the intervals between parasitaemic episodes (“time-to-event” analysis), can help resolve the probable origin of recurrences. Whole genome sequencing of predominantly low-density P. vivax infections is challenging, so an accurate and scalable genotyping method to determine the origins of recurrent parasitaemia would be of significant benefit. We have developed a P. vivax genome-wide informatics pipeline to select specific microhaplotype panels that can capture IBD within small, amplifiable segments of the genome. Using a global set of 615 P. vivax genomes, we derived a panel of 100 microhaplotypes, each comprising 3-10 high frequency SNPs within 0.9 in 90% countries tested) and it also captured local infection outbreak and bottlenecking events. The informatics pipeline is available open-source and yields microhaplotypes that can be readily transferred to high-throughput amplicon sequencing assays for surveillance in malaria-endemic regions.

This report describes the MalariaGEN Pv4 dataset, a new release of curated genome variation data on 1,895 samples of Plasmodium vivax collected at 88 worldwide locations between 2001 and 2017. It includes 1,370 new samples contributed by MalariaGEN and VivaxGEN partner studies in addition to previously published samples from these and other sources. We provide genotype calls at over 4.5 million variable positions including over 3 million single nucleotide polymorphisms (SNPs), as well as short indels and tandem duplications. This enlarged dataset highlights major compartments of parasite population structure, with clear differentiation between Africa, Latin America, Oceania, Western Asia and different parts of Southeast Asia. Each sample has been classified for drug resistance to sulfadoxine, pyrimethamine and mefloquine based on known markers at the dhfr, dhps and mdr1 loci. The prevalence of all of these resistance markers was much higher in Southeast Asia and Oceania than elsewhere. This open resource of analysis-ready genome variation data from the MalariaGEN and VivaxGEN networks is driven by our collective goal to advance research into the complex biology of P. vivax and to accelerate genomic surveillance for malaria control and elimination.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21491-y

Plasmodium vivaxgene regulation remains difficult to study due to the lack of a robust in vitro culture method, low parasite densities in peripheral circulation and asynchronous parasite development. We adapted an RNA-seq protocol “DAFT-seq” to sequence the transcriptome of fourP. vivaxfield isolates that were cultured for a short period ex vivo before using a density gradient for schizont enrichment. Transcription was detected from 78% of the PvP01 reference genome, despite being schizont-enriched samples. This extensive data was used to define thousands of 5′ and 3′ untranslated regions, some of which overlapped with neighbouring transcripts, and to improve the gene models of 352 genes, including identifying 20 novel gene transcripts. This dataset has also significantly increased the known amount of heterogeneity betweenP. vivaxschizont transcriptomes from individual patients. The majority of genes found to be differentially expressed between the isolates lackPlasmodium falciparumhomologs and are predicted to be involved in host-parasite interactions, with an enrichment in reticulocyte binding proteins, merozoite surface proteins and exported proteins with unknown function. An improved understanding of the diversity withinP. vivaxtranscriptomes will be essential for the prioritisation of novel vaccine targets.