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At least 19 recordsLinked to original sources

PubMed2026

Eco-evolutionary dynamics sustain a potent yet rare antibiotic gene cluster in Streptomyces.

Microbial secondary metabolites have been recognized and utilized for nearly a century. Nevertheless, the eco-evolutionary mechanisms governing their distribution among microorganisms remain largely unresolved. In this study, we examined intraspecific interactions within Streptomyces albidoflavus and identified a strain exhibiting potent antagonistic activity against conspecifics. This "killer" phenotype was attributed to the production of kosinostatin, a hybrid aromatic polyketide antibiotic. Evolutionary genomic analyses provided strong evidence that the kosinostatin biosynthetic gene cluster was horizontally acquired in S. albidoflavus over a relatively short evolutionary timescale, a finding consistent with its sparse distribution within this species, across the genus Streptomyces, and even throughout the phylum Actinomycetota. Using microcosm assays, we demonstrated that the kosinostatin producer outcompeted sensitive conspecifics in liquid culture but not in soil, indicating that environmental context plays a key role in altering the fitness benefits of this cluster. Moreover, the competitive advantage was observed only in the presence of sensitive strains, revealing a trade-off between fitness benefits and metabolic costs. These results highlight the role of context-dependent selection in shaping the evolutionary persistence of the kosinostatin cluster. The current distribution pattern of this cluster in S. albidoflavus likely results from a dynamic interplay of intraspecific horizontal gene transfer, vertical inheritance, and recurrent gene loss. Overall, our findings establish an eco-evolutionary framework that explains the rarity of a potent antibiotic gene cluster in Streptomyces, illustrating how environmental constraints, fitness trade-offs, and gene flux collectively orchestrate the biosynthetic architecture of Streptomyces species.

Streptomyces↗

PubMed2026

Mutations in filamentous bacteriophages spark eco-evolutionary feedbacks in Pseudomonas aeruginosa.

Microbial populations strongly shape their environment, which can re-route adaptation toward organism-generated fitness optima. However, the conditions that promote these eco-evolutionary feedbacks are unclear. Here, we used experimental evolution to test whether high population density, by strengthening niche construction, drives eco-evolutionary feedbacks in the bacterial pathogen Pseudomonas aeruginosa (Pa) MPAO1. We tested for adaptation to organism-modified environments by measuring the relative performance of ancestral and endpoint populations in filtrate generated by each evolutionary line sampled across generations. Contrary to expectations, we found that endpoint populations had higher performance than the ancestral strain in filtrate across nearly all evolutionary lines regardless of population density. This was caused by the emergence of hyperactive filamentous bacterio(phage) mutants during experimental passaging that inhibited the ancestral strain but not endpoint populations in modified media. Hyperactive phages emerged from one of two avirulent prophages in MPAO1's genome (Pf4 or Pf6). Hyperactive phages drove the evolution of phage resistance in bacterial populations via mutations in the type IV pilus (TIVP), the phage's binding receptor. In a follow-up experiment, we showed that these TIVP mutations pleiotropically reduced motility and conferred resistance to a TIVP-targeting virulent phage, both of which are important traits for Pa infection and treatment. Overall, this work suggests that filamentous phage evolution can drive eco-evolutionary feedbacks in bacterial populations, causing phenotypic and genetic changes that would not be anticipated from adaptation to the extrinsic environment alone.

Pseudomonas aeruginosa↗

PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗

PubMed2026

Interpreting cancer genetics through a two-step "evolutionary cascade hypothesis": bridging neutral and selective perspectives.

BACKGROUND: DNA mutations are the fundamental engines of cancer, driving its initiation and progression. The forces that fuel malignancy are also the architects of evolution, shaping life through genetic variations. Mutations, in fact, can emerge naturally from endogenous processes, such as oxidative DNA damage or errors in replication, as well as induced by external factors, including cosmic radiation and chemical carcinogens. MAIN BODY: A key question in cancer research is whether tumor evolution is primarily governed by selective bottlenecks, neutral evolution, or dynamic genetic plasticity. In this work, we examine cancer as a disease driven by evolutionary processes rooted in fundamental biological requirements, including sustained proliferation and nutrient utilization. We hypothesize that the accumulation of mutations activates an evolutionary switch, enabling tumor cells to acquire an enhanced capacity for survival, adaptation, and growth at rates far exceeding typical evolutionary timescales. We propose the "evolutionary cascade hypothesis," a unifying framework that integrates these models into a coherent sequence. At its core lies the failure of DNA repair mechanisms, representing a critical transition in cancer progression. This shift marks the transition from an initial non-Darwinian, neutral phase to a Darwinian, more deterministic phase. CONCLUSIONS: As predictive models of tumor evolution advance through genomic big data and artificial intelligence-driven analysis, the future of cancer treatment may extend beyond targeting individual mutations to disrupting the underlying evolutionary mechanisms that sustain malignancy. This paradigm shift could redefine therapeutic strategies and ultimately improve patient outcomes.

Humans↗

PubMed2025

Distinct evolutionary trajectories of subgenomic centromeres in polyploid wheat.

BACKGROUND: Centromeres are crucial for precise chromosome segregation and maintaining genome stability during cell division. However, their evolutionary dynamics, particularly in polyploid organisms with complex genomic architectures, remain largely enigmatic. Allopolyploid wheat, with its well-defined hierarchical ploidy series and recent polyploidization history, serves as an excellent model to explore centromere evolution. RESULTS: In this study, we perform a systematic comparative analysis of centromeres in common wheat and its corresponding ancestral species, utilizing the latest comprehensive reference genome assembly available. Our findings reveal that wheat centromeres predominantly consist of five types of centromeric-specific retrotransposon elements (CRWs), with CRW1 and CRW2 being the most prevalent. We identify distinct evolutionary trajectories in the functional centromeres of each subgenome, characterized by variations in copy number, insertion age, and CRW composition. By utilizing CENH3-ChIP data across various ploidy levels, we uncover a series of CRW invasion events that have shaped the evolution of AA subgenome centromeres. Conversely, the evolutionary process of the DD subgenome centromeres involves their expansion from diploid to hexaploid wheat, facilitating adaptation to a larger genomic context. Integration of complete einkorn centromere assemblies and Aegilops tauschii pan-genomes further revealed subgenome-specific centromere evolutionary trajectories. By inclusion of synthetic hexaploid from S2-S3 generations, alongside 2x/6 × natural accessions, we demonstrate that DD subgenome centromere expansion represents a gradual evolutionary process rather than an immediate response to polyploidization. CONCLUSIONS: Our study provides a comprehensive landscape of centromere adaptation, evolution, and maturation, along with insights into how retrotransposon invasions drive centromere evolution in polyploid wheat.

Centromere↗

PubMed2026

Polygenic and monogenic adaptation drive evolutionary rescue at different magnitudes of environmental change.

Understanding the genetic basis of rapid adaptation is key to predicting species' evolutionary responses to environmental change. However, it is still debatable whether many small-effect mutations or a few large-effect mutations underlie rapid adaptation, and how this knowledge can predict population survival or extinction. To address this question, we performed a series of ecologically grounded forward-in-time genetic simulations to study rapid adaptation and extinction with increasing magnitudes of environmental change. These simulations were seeded with genomic variation of the plant Arabidopsis thaliana to have a realistic genomic structure, with one (monogenic) to 1,000 (polygenic) variants with varying heritabilities contributing to an environmental adaptive trait. Our results revealed two distinct scenarios of rapid adaptation and population rescue. Under small-to-moderate environmental shifts, high polygenic traits increased evolutionary rescue probability. Under extreme environmental shifts, high polygenic traits lead predictably to extinction, yet monogenic traits sometimes produce one-off winning adaptive genotypes. We interpret our rapid evolutionary rescue findings in terms of the fundamental theorem of natural selection, where trait polygenicity shapes the distribution of genetic variance in fitness across replicates and, in turn, the probability of population survival, with polygenic architectures producing more stable and predictable fitness variance and monogenic architectures generating highly skewed and variable outcomes. These results highlight the insights genomics gives us into the (un)predictability of species' evolutionary responses to global change, with management implications for assisted adaptation and conservation.

Arabidopsis↗

PubMed2023

Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava.

INTRODUCTION: Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication ~10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression. METHODS: To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava. RESULTS: Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by<100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction. CONCLUSION: We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.

cassava (Manihot esculenta)↗

PubMed2026

MaizeGDB Phylostrata Tool: exploring evolutionary origins of maize proteins.

MOTIVATION: Phylostratigraphic analysis identifies the evolutionary origins and level of conservation of proteins, facilitating research in evolutionary biology and comparative genomics. RESULTS: We developed the MaizeGDB Phylostrata Tool, a custom web application that enables users to explore the evolutionary origins of proteins in maize (Zea mays), a globally important crop and model organism. This tool features interactive visualizations and detailed gene pages incorporating subcellular localization, Gene Ontology (GO) terms, and links to resources for homologs, facilitating comparison of gene functions across evolutionary time. The tool also provides downloadable links for full-proteome phylostratigraphic results for 26 maize inbreds (B73 and the NAM founders). From these, we identified genome- and subgenome-wide trends, finding that more conserved proteins tended to be longer and more highly expressed. Finally, we provide code including updates to the "phylostratr" R package to make it more robust against taxonomic updates, as well as example scripts for phylostratigraphic analysis and web tool development for researchers and curators of other species. AVAILABILITY AND IMPLEMENTATION: The MaizeGDB Phylostrata Tool is freely available at https://phylostrata.maizegdb.org. Scripts used for the analysis and web tool are available at https://github.com/LTibbs/PhylostrataWebtool.

Journal Article↗

PubMed2025

Recurrent Evolutionary Innovations in Rodent and Primate Schlafen Genes.

SCHLAFEN proteins are a large family of RNase-related enzymes carrying essential immune and developmental functions. Despite these important roles, Schlafen genes display varying degrees of evolutionary conservation in mammals. While this appears to influence their molecular activities, a detailed understanding of these evolutionary innovations is still lacking. Here, we used in-depth phylogenomic approaches to characterize the evolutionary trajectories and selective forces shaping mammalian Schlafen genes. We traced lineage-specific Schlafen amplifications and found that recent duplicates evolved under distinct selective forces, supporting repeated subfunctionalization cycles. Codon-level natural selection analyses in primates and rodents identified recurrent positive selection over Schlafen protein domains engaged in viral interactions. Combining known crystal structures and predicted protein structures, we discovered a novel class of rapidly evolving residues enriched at the contact interface of SCHLAFEN protein dimers. Our results suggest that inter-SCHLAFEN compatibilities are under strong selective pressures and are likely to impact their molecular functions. We posit that cycles of genetic conflicts with pathogens and between paralogs drove Schlafens' recurrent evolutionary innovations in mammals.

Animals↗

PubMed2025

Distinct Evolutionary Signatures of Human Parainfluenza Viruses 2 and 4 Reveal Host Antagonism Divergence and Phylogenetic Discordance.

Human parainfluenza virus 2 (HPIV-2) and human parainfluenza virus 4 (HPIV-4) are significant but underappreciated respiratory pathogens, particularly among high-risk populations including children, the elderly, and immunocompromised individuals. In this study, we sequenced 101 HPIV-2 and HPIV-4 genomes from respiratory samples collected in western Washington State and performed comprehensive evolutionary analyses using both new and publicly available sequences. Phylogenetic and phylodynamic analyses revealed that both HPIV-2 and HPIV-4 evolve at significantly faster rates compared to the mumps virus, a reference human orthorubulavirus. Notably, while HPIV-2 demonstrated the highest evolutionary rates in the surface glycoprotein HN, consistent with humoral immune-driven selection, the innate immune antagonist V/P gene evolved fastest in HPIV-4. We identified a hypervariable region within the HPIV-4V/P protein (residues 35 to 75), which structural modeling placed in a loop overlapping a known interferon antagonism domain in other paramyxovirus V proteins, though HPIV-4 is functionally incompetent in this activity. Expanded phylogenetic analysis across the Paramyxoviridae family uncovered a striking evolutionary discordance: while the HN glycoprotein and L polymerase of HPIV-4 and its 2 closest bat-derived viruses clustered within the Orthorubulavirus genus, their nucleoprotein (N), phosphoprotein (P), matrix (M), and fusion (F) proteins formed a distinct lineage outside the Rubulavirinae subfamily. Together, these findings highlight the distinct evolutionary trajectories of HPIV-2 and HPIV-4, raise hypotheses around complex Paramyxoviridae zoonotic events including recombination-like patterns, and demonstrate limitations of current L protein-based taxonomic classification schemes.

Humans↗

PubMed2025

MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.

Evolutionary sparse learning uses supervised machine learning to build evolutionary models where genomic sites loci are parameters. It uses the Least Absolute Shrinkage and Selection Operator with bi-level sparsity to connect a specific phylogenetic hypothesis with sequence variation across genomic loci. The MyESL software addresses the need for open-source tools to perform evolutionary sparse learning analyses, offering features to preprocess input phylogenomic alignments, post-process output models to generate molecular evolutionary metrics, and make Least Absolute Shrinkage and Selection Operator regression adaptable and efficient for phylogenetic trees and alignments. The core of MyESL, which constructs models with logistic regressions using bi-level sparsity, is written in C++. Its input data preprocessing and result post-processing tools are developed in Python. Compared to other tools, MyESL is more computationally efficient and provides evolution-friendly inputs and outputs. These features have already enabled the use of MyESL in two phylogenomic applications, one to identify outlier sequences and fragile clades in inferred phylogenies and another to build genetic models of convergent traits. In addition to the use in a Python environment, MyESL is available as a standalone executable compatible across multiple platforms, which can be directly integrated into scripts and third-party software. The source code, executable, and documentation for MyESL are openly accessible at https://github.com/kumarlabgit/MyESL.

Phylogeny↗

PubMed2025

Integrative genomics elucidates the evolutionary, temporal, and developmental origins of a hydrocephalus risk gene.

INTRODUCTION: A prior integrative, multi-omics human genetics and functional genomics study identified maelstrom (MAEL), a gene involved in regulation of DNA transposon activity and genome structure, as a transcriptome-wide predictor of hydrocephalus (HC) in the brain cortex. Here we expand on this discovery and further characterize the evolutionary origin and expression of MAEL across developmental timescales and cell-lineages in the neonatal human brain towards a mechanistic understanding how variation in MAEL expression may cause HC. OBJECTIVE: To characterize the evolutionary, temporal, developmental, and lineages of MAEL expression in HC and the developing human brain. METHODS: Ensembl was used to delineate the evolution and taxonomy of MAEL across species. Analysis of single-cell RNA sequencing (scRNA-seq) of 49 brain regions across pre- and post-natal timescales from the Developing Human Brain Atlas (Allen Institute) identified temporal and spatial MAEL expression patterns. We quantified MAEL expression in primary cortical brain tissue obtained during the surgical treatment of HC. RESULTS: We performed taxonomic gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in vitro and in vivo across species. We find that MAEL is among the top 0.01% human-specific genes and < 50% sequence homology among commonly used model organisms with highly divergent functions, necessitating mechanistic validation in human tissue. scRNA-seq of the non-disease prenatal human brain identified MAEL expression enriched in cortical excitatory neurons, which was recapitulated in primary HC brain tissue obtained during surgery. Finally, using scRNA-seq of primary HC brain tissue, we functionally validated reduced MAEL expression, consistent with a prior human TWAS analysis. CONCLUSIONS: We identify the evolutionary, temporal, and developmental expression pattern of MAEL in the neonatal human brain. We also provide direct evidence for reduced MAEL expression in human HC brain tissue. These data, at least in part, implicate reduced MAEL expression underlying human HC across etiologies.

Journal Article↗

PubMed2025

Diversity and evolutionary history of endogenous retroviruses in the genome of Manis pentadactyla.

Endogenous retroviruses (ERVs), remnants of ancient viral infections integrated into host genomes, serve as invaluable molecular fossils for studying viral evolution. In this study, we performed a genomic analysis of the Chinese pangolin (Manis pentadactyla), identifying novel full-length endogenous retroviruses, designated as Manis pentadactyla ERVs (MPERVs). MPERVs span three retroviral genera: Alpha-, Beta-, and Gamma-retroviruses. Using genomic screening and phylogenetic analysis, we classified MPERVs and reconstructed their evolutionary history, uncovering evidence of complex recombination events and cross-species transmission. Estimated insertion times for MPERVs range from very recent to 18.38 million years ago. MPERVs exhibit diverse structural features, notably including conserved retroviral domains and functional motifs and highlighting their preservation across extensive evolutionary periods. These findings shed light on the evolutionary dynamics of ERVs in Chinese pangolin and suggest the potential for expanded host ranges among certain retrovirus genera.IMPORTANCEEndogenous retroviruses are unique viruses distinguished by the fact that they are retained as part of the host genome after an exogenous retrovirus infects the host. The Chinese pangolin, as a host with a long independent evolutionary history, likely holds valuable insights in its genome regarding retrovirus endogenization and transmission. In this study, we identified the footprints of exogenous retroviruses from three different genera in the pangolin genome: Alpharetrovirus, Betaretrovirus, and Gammaretrovirus. Additionally, by calculating the integration times of the pangolin's endogenous retroviruses and analyzing the domains of the three main functional proteins (GAG, POL, and ENV), we found that the insertions are relatively young. This suggests that these endogenous retroviruses infected the Chinese pangolin long before their endogenization. This study represents the exploration of endogenous retroviruses in the Chinese pangolin genome, expanding our understanding of endogenous retroviruses in mammals. Furthermore, our findings provide new evidence for the phenomenon of the cross-species transmission of retroviruses prior to endogenization.

Endogenous Retroviruses↗

PubMed2026

Genome-wide identification and evolutionary analysis of the ERF-VII gene family in the tea plant (Camellia sinensis) and functional characterization of CsRAP2.2 in response to cold stress.

The ERF-VII gene family, a critical branch of the AP2/ERF superfamily, is central to plant stress adaptation. However, its evolutionary history and function in tea plant (Camellia sinensis) remain unclear. Here, we performed integrated evolutionary, genomic, and functional analyses of ERF-VII genes across 14 plant lineages and 20 tea plant cultivars. The phylogenetic analysis revealed that ERF-VII proteins originated after vascular plant divergence, coinciding with the emergence of the N-terminal MCGGA/I motif linked to the oxygen-dependent N-degron pathway. Gymnosperms retained few conserved members, whereas angiosperms exhibited lineage-specific expansion-extensive in monocots via whole-genome duplication, moderate in eudicots with functional diversification. Pan-genome analysis across 20 tea plant cultivars further revealed varietal differences in ERF-VII gene distribution. Transcriptome profiling via the Tea Plant Information Archive identified CsRAP2.2 as a cold-inducible ERF-VII member with sustained expression under low-temperature stress. Functional assays demonstrated that silencing CsRAP2.2 reduced cold tolerance, while overexpression in tea leaves and heterologous expression in Arabidopsis thaliana enhanced cold tolerance by maintaining photosystem II efficiency, reducing membrane lipid peroxidation, and improving antioxidant capacity. Weighted gene co-expression network analysis positioned CsRAP2.2 as a regulatory hub integrating cold, hormone, and oxygen-sensing pathways. These results clarify the evolutionary trajectory of ERF-VII genes and establish CsRAP2.2 as a core cold-tolerance regulator in tea plant. These findings may inform future breeding of cold-resilient tea cultivars.

Camellia sinensis↗

PubMed2024

Comparative genomic analysis and functional investigations for MCs catabolism mechanisms and evolutionary dynamics of MCs-degrading bacteria in ecology.

Microcystins (MCs) significantly threaten the ecosystem and public health. Biodegradation has emerged as a promising technology for removing MCs. Many MCs-degrading bacteria have been identified, including an indigenous bacterium Sphingopyxis sp. YF1 that could degrade MC-LR and Adda completely. Herein, we gained insight into the MCs biodegradation mechanisms and evolutionary dynamics of MCs-degrading bacteria, and revealed the toxic risks of the MCs degradation products. The biochemical characteristics and genetic repertoires of strain YF1 were explored. A comparative genomic analysis was performed on strain YF1 and six other MCs-degrading bacteria to investigate their functions. The degradation products were investigated, and the toxicity of the intermediates was analyzed through rigorous theoretical calculation. Strain YF1 might be a novel species that exhibited versatile substrate utilization capabilities. Many common genes and metabolic pathways were identified, shedding light on shared functions and catabolism in the MCs-degrading bacteria. The crucial genes involved in MCs catabolism mechanisms, including mlr and paa gene clusters, were identified successfully. These functional genes might experience horizontal gene transfer events, suggesting the evolutionary dynamics of these MCs-degrading bacteria in ecology. Moreover, the degradation products for MCs and Adda were summarized, and we found most of the intermediates exhibited lower toxicity to different organisms than the parent compound. These findings systematically revealed the MCs catabolism mechanisms and evolutionary dynamics of MCs-degrading bacteria. Consequently, this research contributed to the advancement of green biodegradation technology in aquatic ecology, which might protect human health from MCs.

Humans↗

PubMed2025

Evolutionary dynamics and genetic diversity of transposable elements revealed by resequencing data in maize population.

Zea mays (maize) is a globally significant crop with a complex genome enriched with transposable elements (TEs), which are crucial drivers of genomic diversity and plant evolution. In this study, we identified the TE insertion loci (TILs) from resequencing data of 103 maize accessions with the developed pipeline, and 64 293 non-redundant unique TILs were obtained in 82 maize accessions after filtering; approximately 80% (51 361) of loci showed insertion polymorphisms within the population. All TE superfamilies have low frequency in the maize population except for short interspersed nuclear elements, while some TE families have high fixed TE insertions, revealing distinct evolutionary dynamics among TE superfamilies and families. Genetic analysis using the transposon insertion polymorphism information from the maize population showed that the TE polymorphism loci can reflect their geographical origin and evolutionary relationships. Furthermore, TE insertions could also significantly impact gene expression, implying functional consequences for maize phenotypes and adaptation. These findings provide valuable insights into the evolutionary dynamics and genetic diversity of maize genomes, offering a valuable resource for molecular markers and association studies.

Zea mays↗

PubMed2026

Genetic and metabolite diversity of Sundaland Heptapleurum (Araliaceae) insight into evolutionary and specialized metabolite.

BACKGROUND: The genus Heptapleurum Gaertn (previously treated as Schefflera J.R.Forst. & G.Forst.) within the Araliaceae family is recognized for its significant medicinal value and complex taxonomy. However, an integrated understanding of its evolutionary and metabolite diversity remains unexplored, especially in the Sundaland region (i.e., Java and Sumatra). Here, we integrate genomics and metabolomics to unravel the evolutionary relationships and metabolite diversity of 10 Heptapleurum species from Sundaland. RESULTS: We assembled 10 new complete plastid genomes (plastomes) and 45S nuclear ribosomal DNA (nrDNA) sequences, identifying significant variation and potential key molecular markers. Metabolomics identified 152 metabolites, mainly phenolics and terpenoids. Metabolite profiles of H. rhynchocarpum and H. capituliferum were more correlated with phylogeny than with geography; these two species were separate from the main Heptapleurum clade. Four species, H. farinosum, H. longifolium, H. rigidum, and H. fastigiatum, have almost identical plastomes and 45S nrDNA structures, suggesting they may represent closely related species with different phenotypes, as evidenced by distinctive metabolite compositions. CONCLUSIONS: Crucially, there is an incongruence between the genetic and chemical phylogenies, underscoring that while chemotaxonomy reflects functional diversity, genetic data remains the definitive standard for evolutionary inference, with the potential for reclassifying H. rhynchocarpum and H. capituliferum. This study provides a foundation for future taxonomic revisions, conservation, and drug discovery of Heptapleurum.

Phylogeny↗

PubMed2026

Untangling the Arisaema enigma: Investigating the complex evolutionary history and species relationships in North American Arisaema.

PREMISE: The evolutionary history of morphologically variable plant groups is often obscured by cryptic diversity, morphological convergence, and limited genetic data. Arisaema, a diverse genus within Araceae, exemplifies these challenges. Although some taxonomic treatments recognize only two species of North American Arisaema (A. dracontium and A. triphyllum), other studies have identified morphologically distinct groups within both taxa. Here, we reconstructed evolutionary relationships in North American Arisaema, assessed genetic structure and admixture, and tested the monophyly of proposed species. METHODS: We used 2b-RAD sequencing to generate genome-wide SNP data for 146 samples from 31 populations across the eastern United States. Phylogenetic relationships were inferred using maximum-likelihood and Bayesian approaches. Population structure and admixture were assessed using the program structure and principal component analysis (PCA). RESULTS: Both the Arisaema triphyllum and A. dracontium complexes formed well-supported monophyletic groups. Within the A. dracontium complex, we recovered three monophyletic lineages: A. dracontium, A. calciphilum, and A. macrospathum. In the A. triphyllum complex, A. quinatum, A. stewardsonii, and A. allegheniense consistently formed distinct groups. Relationships between A. pusillum and A. acuminatum, and among A. triphyllum s.s., A. purpurascens, and A. striatum were less clearly resolved, likely due to recent or incomplete divergence, gene flow, or polyploidy. CONCLUSIONS: The results support the monophyly of multiple newly proposed taxa within North American Arisaema, but additional sampling across the species' ranges is needed to fully resolve species boundaries. Our study provides the first evolutionary framework for this group, providing a foundation for future ecological, taxonomic, and conservation research in the genus.

Araceae↗