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PubMed2026

A murine model of sepsis induces age- and sex-specific chromatin remodeling in myeloid-derived suppressor cells.

INTRODUCTION: Sepsis survivors frequently develop long-term immune dysfunction, but the epigenetic mechanisms underlying persistent myeloid suppression remain unclear. Myeloid-derived suppressor cells (MDSCs), whose function is shaped by host age and sex, are key contributors to post-sepsis immune dysregulation. METHODS: Here, we present a high-resolution epigenetic map targeting gene promoters of MDSCs after sepsis and daily chronic stress using MAPit-FENGC, a single-molecule assay that simultaneously profiles DNA methylation and chromatin accessibility. In a clinically relevant murine model, including young and older adult male and female mice, splenic MDSCs were isolated for MAPit-FENGC and single-cell RNA sequencing. RESULTS: Unsupervised clustering identified nine promoter classes reflecting chromatin dynamics: age- and sex-dependent sepsis-induced opening (Classes 1-4), persistent closure with varying levels of DNA methylation (Classes 5-7), and constitutive openness post-sepsis (Classes 8, 9). Transcriptomic profiling corroborated these promoter states, linking accessibility with gene expression. CONCLUSIONS: These findings define promoter-level epigenetic classes across a targeted locus panel in splenic CD11b+Gr1+ cells within this murine sepsis model and generate mechanistic hypotheses regarding age- and sex-associated chromatin states.

Animals↗

PubMed2026

GenOT: generative optimal transport enables spatiotemporal interpolation and generation in cross-platform spatial transcriptomics.

Spatial transcriptomics technologies have revolutionized the analysis of spatial gene expression, yet integrating spatial information and generating data across heterogeneous samples remain challenging. We present GenOT, a generative framework combining multi-scale graph self-supervised contrastive learning with optimal transport barycenter theory for efficient cross-slice and cross-platform spatiotemporal interpolation. The core innovation of GenOT lies in introducing an optimal transport barycenter-based interpolation algorithm, which mathematically models spatial distribution differences across heterogeneous samples to reconstruct spatiotemporal gene expression dynamics. Extensive evaluations demonstrate that GenOT consistently outperforms existing approaches in spatial domain identification, cross-platform interpolation, and developmental trajectory reconstruction.

Spatial Transcriptomics↗

PubMed2025

Stepping out of the dark: how metabolomics shed light on fungal biology.

Metabolomics, a critical tool for analyzing small-molecule metabolites, integrates with genomics, transcriptomics, and proteomics to provide a systems-level understanding of fungal biology. By mapping metabolic networks, it elucidates regulatory mechanisms driving physiological and ecological adaptations. In fungal pathogenesis, metabolomics reveals host-pathogen dynamics, identifying virulence factors like gliotoxin in Aspergillus fumigatus and metabolic shifts, such as glyoxylate cycle upregulation in Candida albicans. Ecologically, it highlights fungal responses to abiotic stressors, including osmolyte production like trehalose, enhancing survival in extreme environments. These insights highlight metabolomics' role in decoding fungal persistence and niche colonization. In drug discovery, it aids target identification by profiling biosynthetic pathways, supporting novel antifungal and nanostructured therapy development. Combined with multi-omics, metabolomics advances insights into fungal pathogenesis, ecological interactions, and therapeutic innovation, offering translational potential for addressing antifungal resistance and improving treatment outcomes for fungal infections. Its progress shed light on complex fungal molecular profiles, advancing discovery and innovation in fungal biology.

Metabolomics↗

PubMed2026

Spatial habitat radiomics predicts tertiary lymphoid structure status and identifies an IDO1+ migratory dendritic cell axis in breast cancer.

BACKGROUND: Tertiary lymphoid structures (TLS) are spatially organized immune niches associated with therapeutic response and favorable outcomes in breast cancer (BC). However, TLS assessment currently relies on invasive tissue-based analyses, and the biological mechanisms underlying imaging-based TLS prediction remain poorly understood. METHODS: We developed and validated a spatial heterogeneity-based radiomic TLS signature (shTLS) using dynamic contrast-enhanced MRI to non-invasively predict TLS status across multicenter BC cohorts. Spatial habitat radiomics were used to capture intratumoral and peritumoral immune-related heterogeneity. Integrated multi-omics analyses, including transcriptomics, pathomics, genomics, single-cell RNA sequencing, immunohistochemistry, and multiplex immunofluorescence, were performed to biologically interpret shTLS-defined subgroups. Functional drug-sensitivity assays were conducted to assess therapeutic implications. RESULTS: The shTLS model achieved robust predictive performance across independent cohorts and molecular subtypes. High shTLS scores were associated with immune-inflamed tumors characterized by spatially clustered activated T cells and dendritic cells (DCs). In contrast, shTLS-low tumors exhibited an immunosuppressive spatial niche with peripheral accumulation of CD4+ PD-1+ T cells and plasma cells, increased immune-tumor separation, and enhanced inflammatory and immunoregulatory signaling. An indoleamine 2,3-dioxygenase 1 (IDO1)-associated immunoregulatory program was observed in the shTLS-low tumors, which appeared to be preferentially expressed by LAMP3+CCR7+ migratory DCs. Pharmacologic inhibition of IDO1 enhanced chemotherapy and CDK4/6 inhibitor sensitivity in vitro. CONCLUSION: This study establishes spatial radiomics as a non-invasive approach to decode TLS-associated immune ecosystems and supports the presence of an IDO1-associated immunosuppressive phenotype, providing biological insight and translational rationale for patient stratification and future combination strategies.

Humans↗

PubMed2025

HMGA2 links morphological evolution and microenvironment dynamics to systemic therapy response in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits significant heterogeneity due to morphological changes and tumor microenvironment dynamics, influencing systemic therapy responses. While the role of high-mobility group AT-hook 2 (HMGA2) in tumor progression has been implicated in other cancers, its significance in ccRCC remains unclear. This study investigates the role of HMGA2 in these processes and its clinical impact. METHODS: Spatial transcriptomics (ST) was performed on primary ccRCC samples to investigate expression trajectories associated with HMGA2 expression and morphological evolution. In metastatic ccRCC cohorts treated with systemic therapy, immunohistochemistry and bulk RNA sequencing data were analyzed to evaluate molecular and clinical features in relation to HMGA2. Single-cell RNA sequencing (scRNA-seq) data were used to explore immune cell populations and their interactions. Based on these findings, multiplex immunohistochemistry (mIHC) assessed spatial distribution, cell-cell interactions, and pathological responses of key immune populations. RESULTS: HMGA2 expression was associated with aggressive morphological patterns, such as solid sheets and rhabdoid/sarcomatoid. ST revealed a progressive increase in HMGA2 expression along the morphological trajectory, marked by a shift from clear to eosinophilic cytoplasm, with eccentric nuclei and prominent nucleoli, and loss of vascular architecture. HMGA2-high tumors exhibited aggressive phenotypes driven by cell cycle, epithelial-mesenchymal transition, and inflammatory signaling pathways. Clinically, patients with high HMGA2 had worse progression-free survival but responded better to immune checkpoint inhibitor combination (Combo-ICI) therapy than to tyrosine kinase inhibitor monotherapy. To assess the immune landscape, scRNA-seq data revealed that HMGA2-high tumors were enriched with progenitor exhausted CD8+ T cells (Tpex), along with increased frequencies of conventional dendritic cell type 1 (cDC1) and inflammatory cDC type 2, which were found to interact with Tpex via ICAM-1. mIHC confirmed that Tpex were enriched among Combo-ICI responders in HMGA2-high tumors, with higher densities and closer proximity to ICAM-1+ cDC1. CONCLUSIONS: These findings suggest that dynamic HMGA2 expression contributes to morphological evolution and modulates immune responses through enhanced Tpex-cDCs engagement, serving as a potential marker for systemic therapy response in ccRCC. However, additional experimental studies are required to validate these mechanisms.

Humans↗

PubMed2026

Transcriptome sequencing provides novel insights into larval development and sexual dimorphism in the firefly Aquatica leii (Coleoptera: Lampyridae).

Fireflies are regarded as one of the most charismatic beetles due to their bioluminescence and ecological importance as bioindicators of freshwater quality. However, molecular mechanisms of larval development and sexual dimorphism in aquatic species remain poorly understood. Here, we performed multi-stage transcriptomic analysis of the aquatic firefly Aquatica leii across larval instars from L2 to L6, together with adult females and males, with three biological replicates per stage. Using time-series expression clustering, differential expression analysis, and weighted gene co-expression network analysis (WGCNA), we characterized the transcriptional dynamics of continuous larval development and the onset of sex-biased gene expression. We identified a critical transcriptional transition occurred at L5-L6, marked by downregulation of early morphogenetic genes and upregulation of juvenile hormone metabolism, oxidoreductase activity, and muscle contraction genes, indicating a shift from growth to metamorphic preparation. WGCNA identified a module strongly correlated with L6 (R = 0.97) enriched for the same functions, confirming a coordinated late-larval program. Notably, genes exhibiting sex-biased expression in adults were already expressed during late larval stages (L5 and L6), and 123 genes progressively upregulated from L2 to L6 showed enrichment in chitin biosynthesis, heart contraction, and ion transport; among these, six genes maintained high expression in adults with clear male-biased (Alei052192, Alei006658, and Alei087054) or female-biased (Alei003725, Alei096818, and Alei074026) patterns. These findings establish that transcriptional foundations for sexual dimorphism and adult tissue formation are laid during late larval stages, providing the first multi-stage transcriptomic resource for aquatic firefly conservation and breeding.

Animals↗

PubMed2026

Single-cell multi-omics dissects transcript isoform and immune repertoire dynamics in human immunosenescence.

Immunosenescence, a major hallmark of systemic aging, refers to the progressive functional decline of the immune system. This decline not only compromises host defense and immunological memory but also fuels chronic inflammation and tissue degeneration (collectively known as inflammaging). While single-cell RNA sequencing (scRNA-seq) has revealed transcriptomic alterations associated with immune aging, analyses restricted to transcript abundance fail to capture deeper regulatory layers, such as transcript isoform diversity and the remodeling of immune receptor repertoires. To address this limitation, we present a human peripheral immune single-cell multi-omics atlas that integrates gene expression, transcript isoform diversity, and immune receptor repertoires. By combining single-cell full-length transcriptome sequencing (scCycloneSEQ), short-read scRNA-seq, and single-cell immune receptor sequencing (scTCR/BCR-seq), we systematically profiled peripheral blood mononuclear cells (PBMCs) from healthy donors aged 30-40 and 60-70 years. Our analyses uncovered extensive age-related remodeling of immune cell composition, functional states, and TCR/BCR diversity. Notably, we found that CD4+ effector memory T cells exhibited widespread differential isoform usage (DIU), 3'UTR length variation, and a marked reshaping of cytotoxic T lymphocyte (CTL) clonotypes-all of which were closely associated with aging-related inflammation and cellular senescence. This multi-omics atlas delineates key molecular features of immunosenescence and provides a high-resolution resource for deciphering the regulatory architecture underlying immune aging.

TCR/BCR↗

PubMed2025

An RNA polymerase III tissue and tumor atlas uncovers context-specific activities linked to 3D epigenome regulatory mechanisms.

RNA polymerase III (Pol III) produces a plethora of small noncoding RNA species involved in diverse cellular processes, from transcription regulation and splicing to RNA stability, translation, and proteostasis. Though Pol III activity is broadly coupled with cellular demands for protein synthesis and growth, a more precise understanding of gene-level dynamics and context-specific expression patterns remains missing, in part due to challenges related to sequencing and mapping Pol III-derived small ncRNAs. Here, we establish a predictive multi-tissue map of human Pol III activity across 19 tissues and 23 primary cancer subtypes by comprehensively profiling the chromatin accessibility of canonical Pol III-transcribed gene classes. Our framework relies on the unique relationship between gene accessibility and Pol III transcription, inferring activity through uniform binary classification of ATAC-seq enrichment at Pol III-transcribed genes. By characterizing multi-context gene uniformity, we provide a definition of the core Pol III transcriptome, broadly active across specialized tissues, and catalog genes with varied levels of context specificity. Our genomic Pol III atlas uncovers variable levels of activity across tissues, including sharp contraction of the Pol III transcriptome in heart and brain tissues and frequent expansion across diverse cancers. We show that both tissue- and tumor-specific genes are significantly enriched within lamina-associated domains (LADs), and that aberrant expression of nuclear lamin proteins is sufficient to induce Pol III-emergent patterns at tumor-specific genes. Together, these findings link Pol III dynamics to subnuclear compartmentalization and provide a resource for better understanding Pol III expansion and small RNA biogenesis in cancer.

Journal Article↗

PubMed2025

PUS7-dependent Ψ reshapes specific synaptic gene exons to facilitate fear extinction memory formation.

RNA modifications serve as dynamic regulators of neural plasticity through their ability to fine-tune transcript stability and splicing. Pseudouridine (Ψ), an evolutionarily conserved RNA modification catalyzed by pseudouridine synthases, plays established roles in neurodevelopment, yet its functional significance in activity-dependent behavioral adaptation remains poorly defined. Here, we investigate Ψ-mediated epitranscriptomic regulation within the infralimbic prefrontal cortex (ILPFC), a brain region requiring precise synaptic remodeling for the clinically relevant form of fear extinction memory. Combining transcriptome-wide pseudouridylation profiling with behavioral analysis in mice, we identified selective Ψ enrichment at exons of synaptic regulatory genes within ILPFC during fear extinction learning. Fear extinction in the ILPFC drives concomitant exonic Ψ deposition and upregulation of synaptogenic transcripts, processes that involve pseudouridine synthase PUS7. Crucially, PUS7 knockdown in the ILPFC selectively impaired fear extinction memory formation without altering baseline fear expression, establishing a causal link between Ψ-dependent RNA processing and activity-dependent synaptic structural remodeling in this microcircuit. Our findings demonstrate that PUS7-mediated Ψ modification spatiotemporally regulates activity-dependent RNA dynamics in the ILPFC, providing the evidence that epitranscriptomic mechanisms precisely coordinate synaptic gene expression within behaviorally defined brain sub-region. This work bridges molecular RNA biology with systems neuroscience, revealing a novel mechanism for activity-dependent regulation of fear extinction in ILPFC.

Animals↗

PubMed2021

Dissecting spatial heterogeneity and the immune-evasion mechanism of CTCs by single-cell RNA-seq in hepatocellular carcinoma.

Little is known about the transcriptomic plasticity and adaptive mechanisms of circulating tumor cells (CTCs) during hematogeneous dissemination. Here we interrogate the transcriptome of 113 single CTCs from 4 different vascular sites, including hepatic vein (HV), peripheral artery (PA), peripheral vein (PV) and portal vein (PoV) using single-cell full-length RNA sequencing in hepatocellular carcinoma (HCC) patients. We reveal that the transcriptional dynamics of CTCs were associated with stress response, cell cycle and immune-evasion signaling during hematogeneous transportation. Besides, we identify chemokine CCL5 as an important mediator for CTC immune evasion. Mechanistically, overexpression of CCL5 in CTCs is transcriptionally regulated by p38-MAX signaling, which recruites regulatory T cells (Tregs) to facilitate immune escape and metastatic seeding of CTCs. Collectively, our results reveal a previously unappreciated spatial heterogeneity and an immune-escape mechanism of CTC, which may aid in designing new anti-metastasis therapeutic strategies in HCC.

Aged↗

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

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

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Comparative transcriptomics reveals hormone signaling and MADS-box genes in divergent development of inflorescences and tendrils in grapevine lateral shoots.

Hormone signaling and MADS-box genes regulate grapevine tendril and inflorescence growth divergence, offering molecular insights for managing tendril growth. Grapevine (Vitis vinifera L.) tendrils and inflorescences are homologous organs; however, their divergent development has important agronomic consequences because excessive tendril growth increases vineyard management costs. To explore the regulatory mechanisms, we compared the inflorescence-prone cultivar 'Einset Seedless' (ENT) with the tendril-prone cultivar 'Pinot Noir' (PN) using anatomical observation, transcriptome analysis of specific tendril nodes, and functional characterization of MADS-box genes. ENT exhibited a higher flowering rate at tendril nodes 1-4 than PN. Transcriptome profiling of specific tendril nodes uncovered 549 differentially expressed genes (DEGs) through an intersection/exclusion strategy, with Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment indicating that hormone and mitogen-activated protein kinase (MAPK) signaling were the primary candidates driving the divergence. To assess the spatiotemporal dynamics of these DEGs, we performed Mfuzz clustering, which revealed that multiple expression trajectories were highly consistent with the flowering gradient across different ENT and PN nodes. Plant hormone signal transduction was the predominantly enriched pathway across all dynamic clusters, highlighting the centrality of phytohormones in this process. Guided by this transcriptional evidence, we measured endogenous zeatin and gibberellin (GA₃) contents in the nodal tissues. Remarkably, the zeatin-to-GA₃ ratio not only paralleled the flowering gradient but also correlated with the cluster expression trajectories, providing physiological evidence for a cytokinin-gibberellin interaction model governing organ divergence. Additionally, we analyzed the differentially expressed transcription factors among the DEGs and identified a MADS-box gene, FRUITFULL-LIKE (VvFUL-L), which was markedly upregulated in PN tendrils. Heterologous overexpression of VvFUL-L in arabidopsis promoted early flowering and reduced inflorescence branching, suggesting its potential role in regulating lateral meristem development and affecting tendril formation. Collectively, these findings establish that Hormone Signaling, particularly cytokinin-GA crosstalk, and MADS-box regulators, such as VvFUL-L, are key regulators of inflorescence versus tendril growth in grapevines, providing a basis for future molecular and breeding studies.

Vitis↗

PubMed2026

Genome-Wide Identification and Characterization of the TBL Gene Family and Temporal Expression Dynamics During Powdery Mildew Infection in Cucumber (Cucumis sativus).

Cell-wall polysaccharide O-acetylation contributes to cell-wall assembly, organ development, and plant-pathogen interactions, but the cucumber TBL gene family remains poorly characterized. Here, 37 CsTBL genes were identified genome-wide and analyzed using phylogenetic, syntenic, conserved-motif, gene-structure, promoter, protein-structure, Gene Ontology, and transcriptome approaches, followed by RT-qPCR analysis after powdery mildew inoculation. All CsTBL proteins contained the conserved GDS and DxxH motifs, whereas accessory motifs and predicted structural features varied among clades. Intraspecific analysis identified dispersed, WGD/segmental, and tandem duplication categories, and cross-species synteny was more extensive with melon than with Arabidopsis. Homology-derived annotations associated CsTBL genes with cell-wall polysaccharide metabolism, Golgi/endomembrane compartments, and O-acetyltransferase activity, including six genes assigned to xylan O-acetyltransferase-related annotations. Expression profiling revealed tissue- and developmental-stage-dependent patterns, whereas the publicly available powdery mildew RNA-seq dataset provided descriptive temporal expression profiles in Podosphaera xanthii-inoculated samples. Independent RT-qPCR analysis using time-matched mock controls revealed distinct post-inoculation responses among six selected genes. Relative to the corresponding mock controls, CsTBL2 was consistently repressed; CsTBL15 showed transient induction at 1 dpi followed by repression; CsTBL24 exhibited a biphasic response; CsTBL25 was induced at all sampled post-inoculation time points; CsTBL26 showed progressive induction; and CsTBL30 reached its highest observed expression level at 3 dpi. Integrated functional annotation and expression evidence highlighted CsTBL26 as a priority candidate for further functional characterization, while CsTBL24 and CsTBL25 represented fruit-associated candidates with distinct powdery mildew responses; CsTBL30 remained an additional strongly infection-responsive candidate. These findings provide an evolutionary and expression-based framework for the functional characterization of the cucumber TBL gene family.

O-acetylation↗

PubMed2026

Retinoid dynamics in immune cells during age-related diseases.

Retinoids comprise vitamin A and its structurally related natural and synthetic derivatives. Retinoid dynamics involves multiple retinoid forms, carrier proteins, and enzymes that orchestrate the absorption, transport, storage and biotransformation of dietary vitamin A. Beyond their canonical metabolic functions, metabolites and proteins involved in retinoid metabolism also play distinct roles in signal transduction and transcriptome reprogramming, broadening the mechanisms that influence immune cell fate decisions. Age‑related changes in retinoid bioavailability and signaling intensity alter immune cell polarization and function, thereby contributing to the pathogenesis of chronic inflammation in neurodegenerative diseases, cardiovascular diseases, osteoarthritis, and other age-related diseases. In this review, we focus on age-related alterations in the retinoid metabolic pathway and their impact on inflammation and the progression of age-related diseases. This review highlights the pivotal role of retinoid metabolism in anti-ageing interventions and considers future directions and challenges in this field.

Humans↗

PubMed2026

Wildlife Trade and Genetic Basis of Disease Susceptibility: A Review.

The surge in the trade of wildlife and wildlife products drives several species to extinction while coinciding with the increase in several zoonotic diseases. It is therefore essential to explore the roles of wildlife trade in disease transmission, and how the knowledge of genetics and immunogenetics can help in alleviating the attending challenges. Pathogen-driven selection plays a fundamental role in maintaining immune gene diversity, as individuals with alleles conferring resistance to endemic diseases have higher survival rate. However, anthropogenic disturbances, such as wildlife exploitation, can disrupt these evolutionary processes, leading to reduced genetic diversity and increased disease vulnerability. Advanced genomic tools, such as next-generation sequencing (NGS), whole-genome sequencing (WGS), CRISPR-Cas9 gene editing, genome-wide association studies (GWAS), epigenetics and transcriptomic analysis, can help identify immune gene variations and predict disease susceptibility in both wild and captive populations. Massive research targeting wildlife markets and the interface between the wild and the market players is necessary. It would be interesting to understand dynamics of pathogens and disease susceptibility, through the application of genetics and immunogenetics, thereby enhancing efforts to address the challenges posed by wildlife trade and zoonotic disease emergence.

Animals↗

PubMed2026

A chromosome-scale genome of Capsicum pubescens provides insights into candidate terpene-associated gene clusters and pan variation of terpene synthases.

A chromosome-scale genome of Capsicum pubescens and comparative pan-TPS analysis support structural characterization and gene-level prioritization of a chromosome-9 terpene-associated candidate locus in this accession. Capsicum pubescens is one of the five domesticated Capsicum species, mainly cultivated in mid- to high-elevation regions of the Americas. Despite its distinctive morphology and fruit traits, genomic resources for C. pubescens remain less developed than those for the widely cultivated C. annuum. Here, we assembled a chromosome-scale reference genome for accession HNUCP0001, spanning 3.70 Gb with a scaffold N50 of 278.01 Mb. Comparative genomics revealed 679 significantly expanded gene families enriched in sesquiterpenoid and triterpenoid biosynthesis. Genome-wide biosynthetic gene-cluster mining identified multiple terpene-associated candidate loci, which were subsequently prioritized using genome-derived structural criteria and Capsicum pubescens-specific expression evidence. Subsequently, we curated the terpene synthase (TPS) repertoire and, across 16 Capsicum genomes, resolved 36 TPS orthogroups with pronounced presence/absence variation, highlighting dynamic lineage-specific diversification. Together, these analyses establish HNUCP0001 as an accession-specific genomic resource and provide a comparative framework for prioritizing terpene-associated TPS genes and candidate BGCs in Capsicum. These candidate loci, together with accession-level transcriptomic and metabolomic evidence, offer testable hypotheses for future functional studies of specialized terpenoid metabolism in C. pubescens.

Alkyl and Aryl Transferases↗