Baobab Index

Major advances in Plasmodium sequencing approaches, bioinformatic pipelines, and data analysis tools have provided valuable insights into malaria epidemiology from parasite genomic data. However, translating genetic data into actionable information for decision-makers remains a challenge. Significant barriers limit the integration of these advances into a functional data analysis ecosystem that produces standardized, interpretable results for use by national malaria control programs. The Plasmodium Genomic Epidemiology network convened 18 subject matter experts across 15 institutions at the Reproducibility, Accessibility, Documentation, and Interoperability Standards Hackathon in 2023 to identify available analysis tools, evaluate software standards, improve documentation, and outline workflows. Eight use cases for genomic data were identified, and a subset was developed into analysis workflows comprising a series of connected functionalities. Software tools were then mapped against functionalities to outline a modular approach to data analysis for these use cases. In addition to outlining workflows, a set of objective criteria was developed for evaluating software standards. A total of 40 Plasmodium genomic analysis tools were identified, 22 of which were prioritized for software standards evaluation. Additional tutorials were developed for 10 tools in the form of reproducible code applied to shared datasets. These resources are available on PGEforge (mrc-ide.github.io/PGEforge), a new community resource that serves as a central, open repository for current and future resources for malaria genomic data analysis.

Enteric bacterial pathogens are a major cause of diarrhoeal disease in low-income and middle-income countries, with complex transmission pathways involving human, animal and environmental reservoirs. Conventional epidemiological and microbiological approaches provide important insights into pathogen burden and distribution but lack the resolution needed to characterise fine-scale diversity, antimicrobial resistance (AMR) and transmission dynamics. Whole-genome sequencing offers high-resolution tools to investigate these processes within a One Health framework. The Genomic Epidemiology and Transmission of Ethical approval was obtained from relevant national and institutional committees in all participating countries. Written informed consent was obtained from participants or their guardians prior to enrolment. Findings will be disseminated through peer-reviewed publications, stakeholder engagement activities and open-access platforms to support public health interventions and policy development.

The continuing spread of partially artemisinin-resistant Plasmodium falciparum in Africa is a health challenge that requires urgent attention. The World Health Organization has recommended multiple first-line therapies (MFT) as a response strategy. Implementing a response is critical for Uganda where four artemisinin resistance mutations are at local allele frequencies >0.20 and partner-drug efficacy may be at risk. Using a Uganda-calibrated individual-based mathematical model of P. falciparum transmission and evolution, we evaluate 53 public-sector deployment strategies for artemisinin-based combination therapies and report projected reductions in drug-resistance associated treatment failure from 2025 to 2031. Changing first-line therapy from artemether-lumefantrine (AL) to artesunate-amodiaquine (ASAQ) is projected to reduce treatment failures by 34.7% to 38.3% (90% range) while a first-line policy change to dihydroartemisinin-piperaquine (DHA-PPQ) is projected to reduce treatment failures by 10.0% to 12.9%. Optimal MFT deployments and cycling approaches balance their treatment distribution to higher ASAQ use and lower DHA-PPQ use, with projected treatment failure reduction at ~36% when compared to status quo AL use. Deployment of the triple therapy artemether-lumefantrine-amodiaquine is projected to reduce treatment failures by ~42% if enacted immediately. Increased adoption of and coverage with ASAQ is projected to play a large near-term role in reducing malaria treatment failure counts in Uganda.

Emerging evidence suggests presence of novel or unclassified taxa within the Genomic regions under selection in Common and taxon-specific signatures of selection are evolving in

Hepatitis E virus (HEV) is a major cause of acute viral hepatitis worldwide, with zoonotic genotypes detected in humans and animals. In Africa, limited data exist on environmental HEV circulation. Here, we report the first detection of

Human leukocyte antigen (HLA) class I and II are cell surface proteins that display peptide antigens to immune cells, thereby mediating detection of infected cells and production of antibodies. Pathogen exposure and demographic events, including local adaptation and admixture, have driven and maintained exceptional polymorphism of HLA genes across human populations. Papua New Guinea has a complex demography, with geographically distinct populations in the highlands and lowlands and exceptional linguistic heterogeneity throughout the island. The lowland populations retain signatures of Austronesian expansion ∼3,000 years ago. Papua New Guinea populations are also differentially exposed to endemic malarial pathogens, with a greater burden in the lowlands. We analyzed genome-wide autosomal SNP data together with HLA allele sequences, linguistic, and geographical data from 337 Papuans. We find the substructure of HLA alleles to be highly correlated with altitude in Papua New Guinea, a signal that is distinct from the rest of the genome. In addition, specific HLA-B and HLA-DP alleles in lowland groups have a greater number of homozygous genotypes than expected under neutrality. Some of these HLA alleles are of Austronesian genetic ancestry. We find that the HLA-binding repertoires at candidate loci are significantly enriched for antigenic P. falciparum-derived peptides. Together, these results indicate that pathogen-driven selective pressures correlate with the observed HLA genetic substructure in Papua New Guinea, highlighting the critical importance of characterizing highly complex HLA variation in understanding differences in disease susceptibility across diverse human groups.

Pangolins have become emblematic of the global wildlife trade crisis due to intense trafficking for consumption and traditional medicine. Coupled with habitat loss, the illicit trade in pangolins has severely threatened wild populations. Genetic identification of distinct pangolin populations is an imperative step toward guiding effective and informed conservation management. These populations can serve as a reference for assigning seized individuals to their geographic origins, and thus tracing trafficking networks. However, pangolin population genetics studies have been hindered by limited sampling of geo-referenced individuals, largely due to the species' elusive nature. To address this, we developed a tailored gene-capture approach targeting 671 loci totaling 627 kb with high evolutionary and adaptive value across all eight pangolin species. We optimized the approach for low-quality DNA, including samples from museum collections and wildlife trade, such as bushmeat and scale seizures. We reassessed range-wide population delineations for the three most traded species, the white-bellied (Phataginus tricuspis), Sunda (Manis javanica), and Chinese (M. pentadactyla) pangolins, highlighting the need for biogeographically consistent lineage nomenclature and spatially aware analyses to support coherent conservation planning. The unprecedented geo-referenced DNA database for the three species yielded snapshot insights into pangolin trafficking hotspots and trade dynamics of both domestic markets and global trade seizures, the former providing novel insights into bushmeat trade. Domestic trade reflects local and occasional cross-border sourcing, averaging 454 km across the three species, while international trafficking seizures in mostly scales point to broader, regional procurement. However, common sourcing regions between the two trade market types indicate their interconnectivity, suggesting that local trade may contribute to international trade supply. Our study identified significant international trade hotspots for the white-bellied, Sunda, and Chinese pangolins, centered around southwestern Cameroon, southwestern Borneo Island, and Myanmar, respectively. Addressing geo-referenced sampling gaps and increasing local-to-global seizure data over time may offer deeper spatiotemporal insights into pangolin trade dynamics. Our study design may serve as a replicable model for enabling authorities and practitioners to implement intelligence-driven, geographically targeted interventions, by identifying the key regions most implicated in pangolin trafficking.

With over 10,000 recognized species, birds constitute one of the most diverse and widely distributed vertebrate groups. Although avian genomics has advanced rapidly over the past decade, substantial gaps remain across the global avifauna. Filling these gaps is essential for understanding macroevolutionary patterns, population structure, and the molecular basis of ecological and behavioral diversity. Worldwide museum collections represent invaluable resources for filling these gaps, yet the typically degraded DNA and limited quantities from historical specimens have posed significant challenges for generating high-quality genome assemblies. Here, the Bird Genome 10 K Project adopted low-input sequencing strategies that reduce costs while improving assembly quality compared with earlier order- and family-level genomes. Using mainly stLFR, complemented by 10X Genomics and standard next-generation sequencing, we assembled 177 avian genomes from museum specimens and tissue collections representing 161 genera, including 102 newly sequenced at the genomic level. The assemblies average ∼1.2 Gb in size, with scaffold N50 = 8.03 Mb, contig N50 = 120 kb, 93% BUSCO completeness, and Merqury Quality Value score of 56. These genomes greatly expand avian taxonomic coverage and demonstrate the efficiency of low-input sequencing for generating high-quality assemblies from limited and often degraded material sourced from museum specimens. This resource provides a foundation for comparative genomics, conservation genetics, and evolutionary studies across the avian tree of life.

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