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PubMed2025

A complete and near-perfect rhesus macaque reference genome: lessons from subtelomeric repeats and sequencing bias.

A truly complete, telomere-to-telomere (T2T), and error-free reference genome remains a foundational resource-and long-standing goal-for unbiased comparative and functional genomics. While recent T2T assemblies of humans and other primates have made substantial progress, most still contain thousands of base-level errors, particularly within highly repetitive regions. Here, we present T2T-MMU8v2.0, a near-perfect T2T assembly of the rhesus macaque (Macaca mulatta), representing the highest base-level accuracy reported in a primate genome to date. By employing an optimized ONT-only assembly strategy, we identify subtelomeric satellite-rich regions as the principal bottleneck to improving assembly quality, owing to technological biases in long-read platforms and limitations in current hybrid assembly frameworks. We discover 268 previously unannotated repeat families and resolve ~8 Mbp of SATR satellite arrays, with over 99-fold enrichment in historically misassembled subtelomeric regions. These satellites form four distinct genomic architectures, each with unique SATR satellite composition, segmental duplication organization, and epigenetic signatures, distinct from the subtelomeric architectures observed in hominid genomes. Notably, in contrast to the largely gene-poor subtelomeric regions in African hominids, the SATR architectures in macaques harbor 58 actively transcribed genes, supported by open chromatin and expression data, suggesting gene innovation within these repetitive regions. Functionally, T2T-MMU8v2.0 improves read mappability and accuracy across sequencing platforms, and results in a 19% improvement of transcription start site enrichment scores and 5,821 additional chromatin accessibility peaks on average, thereby enhancing variant detection, regulatory annotation, and transcriptomic resolution in population genetics or single-nucleus studies. Together, this work establishes a new benchmark for genomics, offers a roadmap for resolving complex repetitive regions, and reveals previously unrecognized features of subtelomeric genome structure and evolution.

Journal Article↗
PubMed2025

Spatial genomics: Mapping the landscape of fibrosis.

Organ fibrosis causes major morbidity and mortality worldwide. Treatments for fibrosis are limited, with organ transplantation being the only cure. Here, we review how various state-of-the-art spatial genomics approaches are being deployed to interrogate fibrosis across multiple organs, providing exciting insights into fibrotic disease pathogenesis. These include the detailed topographical annotation of pathogenic cell populations and states, detection of transcriptomic perturbations in morphologically normal tissue, characterization of fibrotic and homeostatic niches and their cellular constituents, and in situ interrogation of ligand-receptor interactions within these microenvironments. Together, these powerful readouts enable detailed analysis of fibrosis evolution across time and space.

Humans↗
PubMed2025

Integrating multi-omics approaches in acute myeloid leukemia (AML): Advancements and clinical implications.

Acute myeloid leukemia (AML) is a highly heterogeneous and aggressive hematologic malignancy characterized by clonal proliferation of myeloid precursors. Despite significant advancements in genomic profiling and targeted therapies, patient outcomes remain suboptimal due to disease complexity, resistance mechanisms, and high relapse rates. The integration of multi-omics approaches-spanning genomics, epigenomics, transcriptomics, proteomics, and metabolomics-has revolutionized AML research, offering a comprehensive understanding of leukemogenesis, tumor heterogeneity, and therapeutic vulnerabilities. Recent studies leveraging high-throughput sequencing, mass spectrometry, and advanced computational tools have uncovered novel biomarkers, clonal evolution dynamics, and microenvironmental interactions that drive AML progression and resistance. For instance, single-cell multi-omics has revealed chemotherapy-resistant leukemic stem cell populations, while proteogenomic analyses have identified actionable targets such as MCL1 and metabolic dependencies like OXPHOS. Clinically, integrated omics platforms are refining risk stratification, minimal residual disease (MRD) monitoring, and personalized therapy selection. However, challenges such as data integration complexity, cost barriers, and ethical considerations remain. This review highlights the transformative potential of multi-omics in AML, emphasizing recent advancements in technology, biomarker discovery, and therapeutic innovation. By bridging the gap between molecular insights and clinical practice, multi-omics integration promises to redefine AML management, paving the way for precision oncology and improved patient outcomes.

Humans↗
PubMed2026

Genome-wide characterization of NOD-like receptor genes links NLR repertoire evolution to spleen immune responses after Aeromonas hydrophila challenge in the Chinese spiny frog (Quasipaa spinosa).

NOD-like receptors (NLRs) are cytosolic pattern-recognition receptors that detect pathogen-associated and damage-associated molecular patterns and mediate innate immune signaling in vertebrates. However, the genomic repertoire, evolutionary diversification, and infection-associated expression of NLR genes remain poorly defined in non-model amphibians. In this study, 66 NLR genes were identified from the Chinese spiny frog (Quasipaa spinosa) genome and designated as QsNLR1-QsNLR66. These genes were unevenly distributed across chromosomes and were classified into three phylogenetic groups, with most members exhibiting conserved motif architectures. Gene duplication analysis indicated that dispersed duplication was the main contributor to QsNLR expansion. Synteny analysis detected five conserved orthologous gene pairs between Q. spinosa and Pelophylax nigromaculatus, suggesting partial conservation of NLR genomic organization between the two amphibians. Ka/Ks analysis showed that several duplicated gene pairs, including NLRC3-like/QsNLR36 and NLRC3-like/QsNLR50, exhibited Ka/Ks ratios greater than one, suggesting potential sequence divergence after duplication. Spleen RNA sequencing (RNA-seq) after Aeromonas hydrophila challenge revealed enrichment of immune-related Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Weighted gene co-expression network analysis linked several QsNLRs to infection-associated modules, among which QsNLR57 was co-expressed with CYBB, ADAM17, SPI1, and HK2. RT-qPCR using time-matched phosphate-buffered saline (PBS) controls showed distinct temporal patterns, with stronger induction of QsNLR29, QsNLR57, and QsNLR66 and weaker or delayed responses of QsNLR50 and QsNLR56. These results characterize the NLR repertoire of Q. spinosa and identify infection-associated QsNLR candidates for future studies of antibacterial immunity in amphibians.

Animals↗
PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗
PubMed2025

Genome-wide identification and analysis of paclobutrazol-resistance gene family in cotton and the positive role of GhPRE3 in salt stress and drought stress resistance.

Compared with other transcription factors, much less studies have been performed on paclobutrazol-resistance (PRE), a subgroup of the extensive bHLH transcription factor gene family, and the research in cotton was also limited. By utilizing the PRE genes and their conserved domains identified in Arabidopsis, a total of 23, 22, 11, and 12 PRE genes were identified from two major cultivated cotton species and their two ancestors, respectively. The cotton PRE gene family was categorized into three subgroups based on evolutionary tree analysis. Motif and intron analyses indicated that the PRE gene has remained highly conserved throughout evolution. Collinearity analysis indicated that gene duplication, particularly through fragment replication, has significantly contributed to the expansion of the cotton PRE family. An exploration of the conserved elements within the PRE gene family uncovered numerous elements associated with plant stress resistance. Additionally, cotton transcriptome and qRT-PCR analysis showed that PRE genes were associated with a variety of abiotic stresses, including salt, drought, and cold treatments. Subcellular localization experiments indicated that the GhPRE3 gene is associated with membrane proteins. Finally, we selected the GhPRE3 gene for a VIGS experiment, which revealed that under salt stress and drought stress conditions, the wilting of leaves in the GhPRE3-silenced plants was significantly more severe than that observed in the control group, with T-AOC levels notably lower and MDA levels significantly higher. Overexpression of GhPRE3 enhanced seed germination and root development in transgenic Arabidopsis thaliana under salt stress and drought stresses. This suggests that GhPRE3 plays a positive regulatory role in cotton tolerance to salt and drought stressed, providing a reference for molecular genetic breeding of cotton with salt and drought tolerance.

Gossypium↗
PubMed2026

Genome-Wide Identification of the PAL Gene Family in Idesia polycarpa and Transcriptomic Responses to Botryosphaeria dothidea Infection.

Idesia polycarpa is a woody oil tree threatened by stem canker caused by Botryosphaeria dothidea, yet the organization and infection-responsive behavior of its phenylalanine ammonia-lyase (PAL) gene family remain poorly understood. Here, we identified five IpPAL genes and characterized their phylogenetic relationships, conserved features, duplication patterns, promoter cis-elements, and infection-associated expression profiles. Segmental and tandem duplication contributed to IpPAL family evolution, and all duplicated pairs showed Ka/Ks ratios below 1, consistent with purifying selection. RNA sequencing (RNA-seq) of contrasting Chengdu and Zhangjiajie provenances revealed distinct temporal responses. In Chengdu, IpPAL2-IpPAL4 were significantly upregulated at 24 h after inoculation, whereas all five genes were upregulated at 96 h. In Zhangjiajie, all five IpPAL genes were significantly upregulated at 24 h, while IpPAL2-IpPAL5 remained upregulated at 96 h. No IpPAL gene met the differential-expression criteria between provenances under mock conditions or at 24 h; at 96 h, IpPAL1 and IpPAL3 were lower and IpPAL5 was higher in Zhangjiajie than in Chengdu. Scanning electron microscopy (SEM) provided complementary qualitative evidence of provenance-associated tissue responses. These findings demonstrate time- and gene-specific IpPAL responses to B. dothidea and identify candidate genes for further functional analysis.

Ascomycota↗
PubMed2025

The release of sexual conflict after sex loss is associated with evolutionary changes in gene expression.

Sexual conflict can arise because males and females, while sharing most of their genome, can have different phenotypic optima. Sexually dimorphic gene expression may help reduce conflict, but the expression of many genes may remain sub-optimal owing to unresolved tensions between the sexes. Asexual lineages lack such conflict, making them relevant models for understanding the extent to which sexual conflict influences gene expression. We investigate the evolution of sexual conflict subsequent to sex loss by contrasting the gene expression patterns of sexual and asexual lineages in the pea aphid Acyrthosiphon pisum. Although asexual lineages of this aphid produce a small number of males in autumn, their mating opportunities are limited because of geographic isolation between sexual and asexual lineages. Therefore, gene expression in parthenogenetic females of asexual lineages is no longer constrained by that of other morphs. We found that the expression of genes in males from asexual lineages tended towards the parthenogenetic female optimum, in agreement with theoretical predictions. Surprisingly, males and parthenogenetic females of asexual lineages overexpressed genes normally found in the ovaries and testes of sexual morphs. These changes in gene expression in asexual lineages may arise from the relaxation of selection or the dysregulation of gene networks otherwise used in sexual lineages.

Animals↗
PubMed2025

Spatiotemporal diversity in molecular and functional abnormalities in the mdx dystrophic brain.

Duchenne muscular dystrophy (DMD) is characterized by progressive muscle degeneration and neuropsychiatric abnormalities. Loss of full-length dystrophins is both necessary and sufficient to initiate DMD. These isoforms are expressed in the hippocampus, cerebral cortex (Dp427c), and cerebellar Purkinje cells (Dp427p). However, our understanding of the consequences of their absence, which is crucial for developing targeted interventions, remains inadequate. We combined RNA sequencing with genome-scale metabolic modelling (GSMM), immunodetection, and mitochondrial assays to investigate dystrophic alterations in the brains of the mdx mouse model of DMD. The cerebra and cerebella were analysed separately to discern the roles of Dp427c and Dp427p, respectively. Investigating these regions at 10 days (10d) and 10 weeks (10w) followed the evolution of abnormalities from development to early adulthood. These time points also encompass periods before onset and during muscle inflammation, enabling assessment of the potential damage caused by inflammatory mediators crossing the dystrophic blood-brain barrier. For the first time, we demonstrated that transcriptomic and functional dystrophic alterations are unique to the cerebra and cerebella and vary substantially between 10d and 10w. The common anomalies involved altered numbers of retained introns and spliced exons across mdx transcripts, corresponding with alterations in the mRNA processing pathways. Abnormalities in the cerebra were significantly more pronounced in younger mice. The top enriched pathways included those related to metabolism, mRNA processing, and neuronal development. GSMM indicated dysregulation of glucose metabolism, which corresponded with GLUT1 protein downregulation. The cerebellar dystrophic transcriptome, while significantly altered, showed an opposite trajectory to that of the cerebra, with few changes identified at 10 days. These late defects are specific and indicate an impact on the functional maturation of the cerebella that occurs postnatally. Although no classical neuroinflammation markers or microglial activation were detected at 10 weeks, specific differences indicate that inflammation impacts DMD brains. Importantly, some dystrophic alterations occur late and may therefore be amenable to therapeutic intervention, offering potential avenues for mitigating DMD-related neuropsychiatric defects.

Animals↗
PubMed2026

Uncovering the early and conserved molecular mechanisms of root nitrogen foraging in model and crops.

BACKGROUND: Nitrogen (N) foraging, the ability of plants to promote preferential root growth in N-rich patches of soil, is fundamental to the competitiveness and wellbeing of plants. A unique “split-root” system, where a heterogenous N environment stimulates root foraging, provides a powerful experimental model to study the mechanisms underlying root foraging in model (Arabidopsis) and/or crop plants. RESULTS: We used the split-root set up to capture early molecular events involved in systemic N-signaling after exposure to a heterogeneous N signal, through time-course transcriptomic analysis across shoots and roots of Arabidopsis. We found that a histone methyltransferase, SET DOMAIN GROUP 8 (SDG8), is necessary for root N-foraging, suggesting a previously unknown role for chromatin regulation in mediating the preferential root growth response to colonize N-rich patches. To determine if the underlying molecular mechanism is conserved in evolution, we compared the root foraging behavior from model-to-crop (Arabidopsis, tomato and maize). Our analysis showed the model and crop species shared a root N-foraging growth response, with some variation among specific genotypes. Interestingly, we observed both shared and distinct transcriptional responses to heterogenous N environments among these three species. CONCLUSIONS: Our study has generated insights into the molecular basis of root N-foraging, with the potential to improve nutrient use efficiency in crop plants in a heterogeneous field environment.

Crops, Agricultural↗
PubMed2026

Cancer of unknown primary: the evolution of tissue of origin identification in the artificial intelligence era.

Cancer of Unknown Primary (CUP) presents substantial diagnostic and therapeutic challenges owing to its heterogeneous nature and the absence of an identifiable primary tumor site. This review provides a structured search of the pathogenesis, epidemiological characteristics, and limitations of traditional diagnostic and therapeutic approaches for CUP, with an emphasis on the evolution of Tissue of Origin (TOO) identification techniques. Recent advances in precision medicine have accelerated the development of machine learning-based TOO identification tools, representing a paradigm shift in CUP diagnostics. Deep learning (DL) algorithms that integrate multi-omics data (such as genomics and transcriptomics) with clinical features have markedly enhanced the accuracy of tracing tumor origin, and artificial intelligence (AI) driven TOO models are increasingly being incorporated into clinical practice, offering new insights for pathological diagnosis, treatment selection, and prognostic evaluation. Nevertheless, several challenges remain, including issues of data standardization, model generalizability, and interpretability. Ethical considerations related to data privacy, algorithmic fairness, and clinical implementation also warrant careful attention. Future research should focus on establishing standardized multi-center databases, developing more interpretable AI models, and fostering multidisciplinary collaborative strategies for CUP management. Through continued refinement of technical solutions and regulatory guidelines, TOO identification is anticipated to progress from research to routine clinical application, ultimately supporting precise and personalized care for patients with CUP.

Artificial intelligence↗
PubMed2026

Systematic mining and characterization of metal transporter families regulating zinc homeostasis provide insights into metal homeostasis in Camellia sinensis.

BACKGROUND AND AIMS: Zinc is essential for tea plant growth and quality formation, yet its homeostatic mechanisms remain poorly understood. This study identified metal transporter families regulating zinc homeostasis, analyzed their evolution, structure, and expression, and clarified zinc uptake, transport, detoxification networks, and their links to metabolism. METHODS: This study identified zinc homeostasis-related metal transporter families in the tea plant genome, characterized their structural features and expression profiles across tissues and developmental stages through integrative bioinformatics and transcriptomic analyses, and delineated the molecular mechanisms underlying zinc uptake, translocation, and detoxification by systematically integrating published evidence. RESULTS: This study identified 74 metal transporter genes from six families: 13 CsZIPs, 12 CsNRAMPs, 10 CsHMAs, 10 CsYSLs, 14 CsMTPs, and 15 CsCAXs in the 'Shuchazao2' genome, revealing closer affinity to woody species than to Arabidopsis. These proteins exhibit conserved domains, diverse subcellular localizations (cell membrane, vacuole, chloroplast, and Golgi apparatus), and tissue-specific expression with abundant stress/hormone-responsive cis-elements. At the plant-soil interface, tea plants mobilize rhizospheric zinc via proton and organic acid secretion; CsYSLs, CsNRAMPs, and CsZIPs mediate zinc uptake, aided by arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) that expand root absorption zones. Xylem CsHMAs and phloem CsYSLs coordinate root-to-shoot zinc translocation, and vacuolar transporters (CsMTPs, CsCAXs), cell wall immobilization, and antioxidant systems alleviate high-zinc stress injury. CONCLUSIONS: These findings collectively delineate an integrated zinc "acquisition-distribution-buffering" network in tea plants, offering a repertoire of candidate genes with potential utility in zinc biofortification breeding and improving acid soil adaptation. Further experimental validation, including tea transgenesis, zinc-stress qRT-PCR, and heterologous functional complementation, is essential to substantiate their biological roles.

Camellia sinensis↗
PubMed2026

Integrative single-cell and genomic analysis reveals NMB as a driver of metastatic adaptation in esophageal squamous cell carcinoma via metabolic rewiring and immune evasion.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) has high mortality, and metastasis is the leading cause of patient death. Neuromedin B (NMB) promotes tumor development in various cancers, yet its role in ESCC metastasis remains unclear. METHODS: We integrated single-cell transcriptomic data from matched primary and metastatic ESCC lesions (GSE309392) with bulk transcriptomic cohorts from TCGA and GSE53624. In silico gene perturbation, ligand-receptor communication analysis, and single-cell prognostic model construction were performed, followed by functional validation through siRNA-mediated NMB knockdown in TE-1 and KYSE30 cell lines. RESULTS: NMB was identified as a key gene enriched in metastatic ESCC lesions, and its high expression was associated with coordinated upregulation of oxidative phosphorylation pathway genes and aldo-keto reductase family antioxidant enzymes (AKR1C1, AKR1C2, AKR1B10). Genomic analysis revealed that NMB-high tumors carried a higher clonal mutation burden and a markedly increased frequency of NFE2L2 activating mutations (23% vs. 8%, P = 0.04). In silico knockout and correlation analysis identified AKR1C1 as a downstream effector of NMB. NMB expression was negatively correlated with CD8+ T cell and activated NK cell infiltration. CellChat analysis revealed communication between NMB-positive cells and monocytes via the TGM2-ADGRG1 axis, and specifically detected IFNG signaling. In the single-cell prognostic model, NMB-positive cells accounted for 50% of the high-risk group but only 20% of the low-risk group. TCGA-based survival analysis demonstrated that high NMB expression was associated with shorter overall survival (HR = 2.98, P = 0.03). In vitro NMB-targeted RNA interference markedly inhibited proliferation, colony formation, and migration in TE-1 and KYSE30 cells. CMap screening identified the endothelin-PDE5-cGMP axis as a potential therapeutic target. CONCLUSION: NMB serves as a key driver of metastatic adaptation in ESCC, conferring a survival advantage to tumor cells during metastatic colonization through genomic evolution and immune remodeling, with metabolic adaptation as a downstream consequence of genomic alterations.

NMB↗
PubMed2025

MEANtools integrates multi-omics data to identify metabolites and predict biosynthetic pathways.

During evolution, plants have developed the ability to produce a vast array of specialized metabolites, which play crucial roles in helping plants adapt to different environmental niches. However, their biosynthetic pathways remain largely elusive. In the past decades, increasing numbers of plant biosynthetic pathways have been elucidated based on approaches utilizing genomics, transcriptomics, and metabolomics. These efforts, however, are limited by the fact that they typically adopt a target-based approach, requiring prior knowledge. Here, we present MEANtools, a systematic and unsupervised computational integrative omics workflow to predict candidate metabolic pathways de novo by leveraging knowledge of general reaction rules and metabolic structures stored in public databases. In our approach, possible connections between metabolites and transcripts that show correlated abundance across samples are identified using reaction rules linked to the transcript-encoded enzyme families. MEANtools thus assesses whether these reactions can connect transcript-correlated mass features within a candidate metabolic pathway. We validate MEANtools using a paired transcriptomic-metabolomic dataset recently generated to reconstruct the falcarindiol biosynthetic pathway in tomato. MEANtools correctly anticipated five out of seven steps of the characterized pathway and also identified other candidate pathways involved in specialized metabolism, which demonstrates its potential for hypothesis generation. Altogether, MEANtools represents a significant advancement to integrate multi-omics data for the elucidation of biochemical pathways in plants and beyond.

Metabolomics↗
PubMed2026

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans↗
PubMed2026

Amaryllidaceae Alkaloids and Isoquinoline Alkaloids: A Perspective on Historical Approaches to Pathway Elucidation.

Alkaloid biosynthesis is a central topic in plant specialized metabolism because many alkaloids have ecological, pharmacological, and biotechnological relevance. Isoquinoline alkaloids (IAs) and Amaryllidaceae alkaloids (AAs) are both connected to aromatic amino acid metabolism, but they differ in taxonomic distribution, scaffold-forming chemistry, pathway resolution, and biotechnological development. This review compares the historical and methodological trajectories that have shaped IA and AA pathway elucidation, from compound isolation, radiotracer experiments, and biochemical inference to transcriptomics, metabolomics, functional enzymology, isotope-guided active-tissue identification, regulatory studies, and heterologous pathway reconstruction. In IAs, especially benzylisoquinoline alkaloids, broad genomic and transcriptomic resources have supported candidate gene discovery and functional characterization of several branches, including morphinan, protoberberine, benzophenanthridine, and aporphine-related pathways. In contrast, AA biosynthesis has advanced more recently through function-driven approaches that clarified key steps such as N4OMT-mediated 4'-O-methylation, NBS/NR-mediated norbelladine formation, CYP96T-dependent regioselective oxidative coupling, and transient reconstruction of major scaffold-forming branches. Remaining gaps include the unresolved enzymatic formation of 3,4-dihydroxybenzaldehyde in AAs and incomplete functional validation across less-studied IA scaffold classes. By integrating biochemical logic, omics-guided discovery, enzyme evolution, tissue specificity, regulation, and synthetic biology, this review identifies priorities for future alkaloid pathway discovery and sustainable production.

3,4-dihydroxybenzaldehyde↗
PubMed2025

Candida glabrata replicating within macrophages experiences amino acid deprivation, DNA damage, and chromosome instability.

Macrophages, the central players of innate immunity, control invading microbes by encapsulating them inside the phagosome, a nutrient-poor, reactive oxidant species-rich organelle. Nevertheless, some microbes, including the opportunistic yeast pathogen Candida glabrata, noted for its karyotype diversity, rapid evolution of antifungal drug resistance, and lack of meiosis, can survive and even replicate inside macrophages. However, it is not fully understood how C. glabrata responds to macrophage engulfment, and it is unknown how this presumably DNA-damaging environment influences the pathogen's genome stability. In this study, we used comparative transcriptomics to identify amino acid starvation and DNA damage as conditions eliciting C. glabrata responses most similar to macrophage engulfment. Consistent with this, we found that C. glabrata intra-macrophage survival and replication require master regulator of amino acid biosynthesis GCN4 and functional DNA double-strand break repair. Furthermore, comet assays provided the first direct evidence for increased DNA breaks in intra-macrophage yeast, and pulse-field gel electrophoresis showed that chromosomal alterations occur frequently in macrophage-passaged C. glabrata. Interestingly, these alterations could not be resolved by long read DNA sequencing, suggesting that they involved highly complex repetitive regions. Finally, we identified several point mutations emerging during macrophage passaging and showed that among them, a frameshift in RME1 (repressor of meiosis in Saccharomyces cerevisiae), increased C. glabrata intra-macrophage fitness. Together, these analyses point to amino acid deprivation, reveal elevated DNA breakage and chromosome instability, and raise intriguing questions about the role of meiotic gene orthologs in C. glabrata persisting and replicating within macrophages.

Journal Article↗
PubMed2026

Phylogenetic Constraints and Environmental Filtering Jointly Drive Adaptive Evolution in Phragmites australis: From Genetic Structure to Trait Decoupling on the Mongolian Plateau.

The Mongolian Plateau, a typical arid and semi-arid zone in Eurasia, is characterized by highly heterogeneous and fragmented wetland habitats. Phragmites australis, a common wetland species in this region, exhibits remarkable adaptability. Unraveling the coordination between phylogenetic history and local environmental filtering is crucial for elucidating its adaptive mechanisms. Integrating landscape genomics and trait-based phylogenetic analyses, we analyzed transcriptome-wide SNPs, multidimensional functional traits, and environmental variables across 90 individuals from 30 natural P. australis populations. This study aims to reveal the genetic and phenotypic variation patterns underlying population genetic structure and trait variation, specifically distinguishing the roles of geographic isolation, environmental filtering, and phylogenetic history. Results reveal a significant drainage-dependent pattern in genetic structure. Populations in hydrologically connected basins show extensive admixture, whereas those in isolated endorheic basins form distinct lineages. While geographic isolation underpins genetic differentiation, environmental filtering independently explains ~33.84% of the genetic variation, driven primarily by moisture heterogeneity (precipitation seasonality and soil moisture). Crucially, we observed differentiated evolutionary trajectories across functional traits. Structural traits (e.g., plant height, leaf thickness) are phylogenetically conserved; in contrast, physiological traits (e.g., water use efficiency) are decoupled from phylogeny, showing patterns consistent with high plasticity regulated by local environments. This evolutionary decoupling strategy enables P. australis to flexibly adapt to heterogeneous habitats while maintaining structural stability. This study uncovers the synergistic mechanisms by which geographic isolation and environmental filtering jointly shape the genetic patterns of this cosmopolitan species at a regional scale, clarifies that its evolutionary responses may depend heavily on the differentiated plasticity of trait types, and provides valuable regional insights into how widespread wetland species adapt to heterogeneous environments under global change.

Mongolia Plateau↗