Baobab Index

This invited commentary explores the paradox of progress in genetic counselling in South Africa, where established training programmes and professional recognition have not yet translated into sustainable clinical genetic services. Drawing on workforce data and insights into training, employment and service delivery, the authors highlight how limited funded public-sector posts, geographic concentration of services and loss of professionals from patient-facing roles constrain equitable access to genetic counselling. The commentary aims to support coordinated workforce planning and investment to ensure that the expansion of genomic medicine is accompanied by accessible, sustainable and equitable genetic counselling services.

The hepatitis E virus (HEV) causes major outbreaks in sub-Saharan Africa. Here, we present four genome sequences of HEV-1e from the 2018 outbreak in the Central African Republic. Despite high identity with known African isolates, these sequences constitute a new cluster and suggest local transmission and diversification.

Tropical rain forest is the most diverse terrestrial biome, yet the drivers of its diversification across space and time remain poorly understood. Although heterogeneous diversification rates, including both ancient and recent radiations, have been reported, these dynamics have rarely been examined within a single lineage across deep evolutionary timescales. Here, we reconstruct a dated phylogenomic tree of the pantropical plant family Annonaceae, sampling 2045 species (∼82% of its diversity) and spanning ∼100 million years of evolutionary history. Diversification dynamics vary markedly across tropical regions, correlated with distinct environmental factors rather than uniform processes. Sea level fluctuations dominate in the Asia-Pacific, whereas paleotemperature shapes diversification in the Afrotropics and Neotropics. We also detect a Late Cretaceous increase in diversification, indicating that a substantial portion of Annonaceae diversity originated before the Cretaceous-Paleogene boundary. Together, these results highlight how regional environmental trajectories have shaped the assembly of a diverse tropical plant family over deep evolutionary time.

The classification of the epilepsies has traditionally relied on clinical and electroencephalographic features. However, advancements in molecular genetics, neuroimaging, and our understanding of epilepsy pathophysiology necessitate a shift toward an etiology-based approach. Etiology-specific classification enables precision diagnosis and precision management by integrating genetic, structural, metabolic, infection, and immune-related insights. Genetic advances have identified more than 1000 epilepsy-related genes, revealing how variations in a single gene can produce diverse phenotypes and syndromes. Similarly, neuroimaging innovations, such as high-resolution magnetic resonance imaging and functional imaging, have enhanced detection of subtle structural abnormalities and epileptogenic zones. In 2022, the International League Against Epilepsy introduced the concept of etiology-specific epilepsy syndromes, emphasizing the interplay between etiology and syndrome. This paradigm shift moves beyond traditional classifications, offering tailored treatments that address seizures and comorbidities to improve prognosis and quality of life. Despite this progress, challenges persist. These include the complexity of defining genotype-phenotype functional relationships, limitations in diagnostic accessibility in resource-limited settings, and the integration of multifactorial causes. This article proposes extending the concept of etiology-specific epilepsy syndromes to encompass broader spectrums of phenotypes within each etiology, supported by detailed frameworks for analyzing clinical, imaging, genetic, and functional data. The aim is to refine the classification system to guide personalized, evidence-based care. This etiology-syndromic spectrum model underscores the importance of lifelong, multidisciplinary approaches to epilepsy management, balancing the value of syndrome-based insights with the transformative potential of precision medicine.

Oral squamous cell carcinoma (OSCC) is represented as a major global health concern with few treatment options. Codon usage bias (CUB) is a non-random selection of synonymous codons. It offers information on gene expression patterns and molecular evolution. This study examined CUB patterns in 1328 differentially expressed genes (651 up-regulated, 677 down-regulated) from oral cancer tissues. Nucleotide composition analysis, effective number of codons (ENC), Relative Synonymous Codon Usage (RSCU) analysis, neutrality plot analysis, and gene expression analysis were performed to assess codon usage patterns and their relationship to gene expression levels and pathway classification. Nucleotide composition analysis indicated a clear GC-rich tendency with base frequencies arranged as C > G > A > T for up-regulated genes and C > A > G > T for down-regulated genes. The average ENC values were 47.21 (up-regulated) and 49.08 (down-regulated), suggesting a low codon usage bias. RSCU analysis revealed 25 more frequently used (mean RSCU >1.0) and 34 less frequently used (mean RSCU <1.0) codons in up-regulated genes, while down-regulated genes had 30 more frequently used and 29 less frequently used codons. Neutrality plot analysis showed that both gene groups were predominantly shaped by selective constraints rather than mutational pressure (slopes of 0.202 and 0.228 for up- and down-regulated genes, respectively), though these slopes provide only indirect, qualitative evidence and should not be interpreted as exact quantitative contributions. Gene expression analysis revealed 1328 differentially expressed genes with functional enrichment in metabolic pathways and cellular components. These discoveries offer molecular insights into the genetic pathways that support oral cancer development. It implies that codon optimization could affect the translation efficiency of cancer-promoting genes.

Adansonia digitata L., known as the African Baobab, is renowned for its extraordinary longevity and its long-standing use in traditional African medicine. However, the genomic basis underlying its specialized secondary metabolism remains largely unexplored. This study aimed to computationally identify and characterize putative biosynthetic gene clusters (BGCs) within the publicly available A. digitata genome assembly (GenBank accession GCA_029448705.1) using an integrated bioinformatics pipeline. Ab initio gene structure prediction was performed with AUGUSTUS (Arabidopsis thaliana species model), functional protein domains were annotated with InterProScan, and candidate BGCs were mined using the plantiSMASH 2.0 webserver. Gene prediction yielded 52 721 protein-coding gene models genome-wide, of which 45 641 (86.6%) received at least one InterProScan domain annotation. The analysis identified 50 putative BGCs distributed across 13 scaffolds, ranging from 15.3 to 492.8 kb in size and provisionally classified into eight chemical categories, most frequently saccharide-type (n = 20) and cyclopeptide-type (n = 9) clusters. Notably, nine clusters carried a BURP-domain core gene consistent with a cyclopeptide/defense-peptide-associated pathway, including the single largest cluster identified (492.8 kb); other clusters carried core domains consistent with terpene synthase, squalene-hopene cyclase, chalcone/stilbene synthase (Chal_sti_synt_N), and dirigent-protein/lignan-associated biosynthesis. None of the 50 clusters showed a significant match to a characterized reference cluster in the MIBiG database, suggesting these represent largely uncharacterized biosynthetic loci. These results represent in silico predictions rather than experimentally confirmed metabolic functions, since no transcriptomic, metabolomic, or biochemical validation was performed as part of this study. Nonetheless, this work provides one of the first genome-wide catalogues of putative BGCs in A. digitata and offers a preliminary resource to guide future comparative genomics, expression profiling, and experimental validation of specialized metabolism in this species.

Multiple myeloma (MM) is a biologically and clinically heterogeneous plasma cell malignancy characterized by clonal expansion in the bone marrow and a highly variable clinical course. Despite major therapeutic advances, MM remains incurable, largely due to the associated genomic complexity, clonal evolution, and the emergence of treatment resistance. In this context, next-generation sequencing (NGS) has emerged as a transformative tool for improving disease characterization, risk stratification, and clinical management. This review summarizes current evidence on the application of NGS technologies, including whole-exome sequencing, whole-genome sequencing, and targeted gene panels-in the diagnosis, prognostic assessment, and monitoring of MM. Genomic profiling has consistently revealed recurrent alterations in key driver genes, copy number abnormalities, and structural variants that underlie disease heterogeneity and influence clinical outcomes. In addition to baseline characterization, NGS enables high-resolution analysis of clonal architecture and evolution, offering critical insights into mechanisms of relapse and therapeutic resistance. Importantly, NGS-based assessment of minimal residual disease (MRD) has demonstrated superior sensitivity compared with conventional techniques, providing a powerful prognostic marker and a promising tool for treatment monitoring and response-adapted strategies. Indeed, by integrating genomic and MRD data, NGS supports a more precise and dynamic approach to patient management. Overall, the growing body of evidence highlights NGS as a central component of precision medicine in multiple myeloma. Continued efforts toward standardization, validation of emerging biomarkers, and clinical implementation of sequencing-guided strategies are expected to enhance personalized treatment further and improve patient outcomes.

Ursolic acid (UA) is a natural pentacyclic triterpene present in many fruits, vegetables and medicinal plants. We tested whether adding UA to the freezing extender improves the quality of frozen-thawed goat sperm. Ejaculates from six bucks were pooled at each collection, and the pooled sample was split into six equal aliquots diluted in Andromed® extender either without UA (UA-0, control) or with 0.5 µM (UA-1), 2 µM (UA-2), 5 µM (UA-3), 15 µM (UA-4) or 30 µM (UA-5). Samples were frozen using a standard protocol and thawed at 37 °C for 30 s. Post-thaw sperm quality was assessed by computer-assisted sperm analysis (CASA) for motility, the hypo-osmotic swelling test for membrane integrity, and flow cytometry for acrosome status (FITC-PSA/PI), phosphatidylserine externalization (Annexin V-FITC), mitochondrial membrane potential (Rhodamine 123) and intracellular reactive oxygen species (H₂DCFDA). Adding UA changed progressive motility (PR) and mitochondrial activity (MA), and both peaked at 0.5 µM. PR at 0.5 µM was significantly higher than at 15-30 µM, and MA at 0.5-2 µM was significantly higher than at 30 µM; however, no UA concentration differed significantly from the control. Total motility, membrane integrity (HOST), acrosome integrity, phosphatidylserine externalization and intracellular ROS did not differ among the treatments. In short, the response was dose-dependent: sperm frozen with 0.5 µM UA retained the best PR and MA, the high concentrations were harmful, and an improvement over the control itself could not be demonstrated. Confirming a fertility benefit will require in vitro fertilization and in vivo insemination trials.