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PubMed2025

HERV Modulation in Colorectal Carcinoma Patients: A Snapshot of Endogenous Retroviral Transcriptome.

Human endogenous retroviruses (HERVs) are proviral relics of infections that affected primates' germ line. Many HERV elements retain a residual capacity to encode transcripts and proteins that have been occasionally domesticated for the host physiology. In addition, HERV transcriptional modulation is of great interest to clarify the etiology of complex disorders such as cancer, even if a few studies assessed the specific HERV loci modulated in tumor tissues. In the present work, we used a transcriptomic approach to investigate the specific expression of ~3300 HERV loci in paired tumor and normal tissues of 7 colorectal cancer (CRC) patients. A total of 102 HERVs were significantly modulated in CRC, with a general tendency towards downregulation. Of note, among the 42 upregulated HERVs 23 belonged to the HERV-H group, that is the most investigated in CRC. De novo transcriptome reconstruction and qPCR validation allowed to identify a transcript from a HERV-H locus on chromosome Xp22.3 with high specific expression in CRC samples, potentially encoding for a partial Pol protein. These results provide a detailed description of HERV transcriptional variations in CRC and its interindividual variability, identifying a HERV-H transcript that deserves further investigation for its possible impact on tumor progression.

Endogenous Retroviruses↗

PubMed2025

Identification of Novel Wraparound Transcripts in JC Polyomavirus.

JC polyomavirus (JCPyV) is a ubiquitous pathogen that causes progressive multifocal leukoencephalopathy (PML). Although a recent study using next-generation sequencing (NGS) provided detailed transcriptome atlases for polyomaviruses (PyVs) such as BK polyomavirus and simian virus 40, the transcriptome of JCPyV remains poorly characterized. Here, we conducted a comprehensive analysis using both short-read and long-read NGS technologies to construct a transcriptome atlas of JCPyV. RNA extracted from IMR-32 and HEK293 cells transfected with the circular JCPyV genome was analyzed, leading to the identification of 39 previously uncharacterized viral transcripts in addition to 12 known ones. Among the novel transcripts, we identified wraparound transcripts, conserved across PyVs, which are generated through continuous, multicyclic transcription of the circular viral genome. These included both late transcripts containing leader-to-leader repeated sequences and SuperT transcripts with multiple LxCxE motifs. Notably, wraparound transcripts, including SuperT transcripts, were also detected in brain tissues from PML patients. Collectively, this study significantly expands our understanding of the JCPyV transcriptome, revealing the expression of wraparound transcripts in PML lesions. These findings provide valuable insights into the molecular basis of JCPyV gene expression and PML pathogenesis, potentially facilitating the development of effective countermeasures against PML.

JC Virus↗

PubMed2025

Parabacteroides goldsteinii mitigates parkinsonism in LRRK2 mutant mice by reducing neuroinflammation through Gut-Brain axis.

INTRODUCTION: Alterations in the gut microbiota accompanied by intestinal inflammation are early features of Parkinson's disease (PD). Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene represent a common genetic risk factor for PD and inflammatory bowel disease. Parabacteroides goldsteinii has been reported to alleviate intestinal and systemic inflammation. However, whether modulation of the gut microenvironment at early disease stage can attenuate PD progression remains unclear. OBJECTIVE: To investigate the impact of P. goldsteinii colonization prior to the onset of motor dysfunction on PD progression. METHODS: We established a germ-free PD mouse model carrying the LRRK2 G2019S mutation and administered P. goldsteinii orally at the pre-symptomatic stage to evaluate its effects on motor performance and PD-related neuropathology. Spatial and bulk RNA transcriptomic analyses of brain tissue, together with cytokine profiling, were conducted to assess central changes. To investigate gut immunomodulatory mechanisms, we performed intestinal bulk and single-cell RNA sequencing, spectral flow cytometry as well as cellular bioenergetic analyses. RESULTS: Germ-free conditions partially alleviated PD-like phenotypes in LRRK2 G2019S mice. Colonization with P. goldsteinii at 5-months of age, prior to motor symptom onset, further improved locomotor performance, reduced neuronal α-synuclein aggregations, and mitigated microglial activation and dopaminergic neurodegeneration. Neuroprotection was mediated through enhanced noncanonical neuronal IL-12 receptor-dependent neurotrophic support without activating the canonical STAT4 phosphorylation pathway, along with suppression of microglial activation and downregulation of LRRK2 kinase activity. At the intestinal level, P. goldsteinii suppressed TLR4-driven inflammation, expanded anti-inflammatory intraepithelial CD4+CD8αα+ T cells, promoted dendritic cell and macrophage differentiation, upregulated epithelial tight-junction genes, and improved mitochondrial bioenergetics in intestinal cells. CONCLUSION: P. goldsteinii colonization attenuates the progression of LRRK2-associated parkinsonism by restoring intestinal homeostasis and reducing neuroinflammation. These findings underscore the therapeutic potential of modulating the gut-immune-brain axis during the prodromal stage of PD.

Animals↗

PubMed2024

Organ-delimited gene regulatory networks provide high accuracy in candidate transcription factor selection across diverse processes.

Organ-specific gene expression datasets that include hundreds to thousands of experiments allow the reconstruction of organ-level gene regulatory networks (GRNs). However, creating such datasets is greatly hampered by the requirements of extensive and tedious manual curation. Here, we trained a supervised classification model that can accurately classify the organ-of-origin for a plant transcriptome. This K-Nearest Neighbor-based multiclass classifier was used to create organ-specific gene expression datasets for the leaf, root, shoot, flower, and seed in Arabidopsis thaliana. A GRN inference approach was used to determine the: i. influential transcription factors (TFs) in each organ and, ii. most influential TFs for specific biological processes in that organ. These genome-wide, organ-delimited GRNs (OD-GRNs), recalled many known regulators of organ development and processes operating in those organs. Importantly, many previously unknown TF regulators were uncovered as potential regulators of these processes. As a proof-of-concept, we focused on experimentally validating the predicted TF regulators of lipid biosynthesis in seeds, an important food and biofuel trait. Of the top 20 predicted TFs, eight are known regulators of seed oil content, e.g., WRI1, LEC1, FUS3. Importantly, we validated our prediction of MybS2, TGA4, SPL12, AGL18, and DiV2 as regulators of seed lipid biosynthesis. We elucidated the molecular mechanism of MybS2 and show that it induces purple acid phosphatase family genes and lipid synthesis genes to enhance seed lipid content. This general approach has the potential to be extended to any species with sufficiently large gene expression datasets to find unique regulators of any trait-of-interest.

Arabidopsis↗

PubMed2026

The multilayered cuticle underlying structural coloration in red algae shares features with the metazoan extracellular matrix.

Structural coloration, a physical phenomenon observed in many living organisms, may arise from the interference of light with highly organized surface nanostructures. In some seaweeds, these nanostructures consist of cuticular lamellae in the outer part of the extracellular matrix (ECM) of the epidermis. However, the chemical composition of seaweed cuticles is poorly understood and the molecular components of lamellae remain unidentified. Here, we use integrated genomic, transcriptomic, proteomic, and metabolomic approaches together with analytical profiling of carbohydrates to determine the composition of the multilayered cuticle in the red alga Chondrus crispus and assess its evolutionary conservation. The structural assembly reveals common features with the ECM of animals. The carbohydrate fraction includes a complex mixture of carrageenans and glycosaminoglycan-like compositions. A major von Willebrand factor A domain protein, Lamellae Cohesive Protein, plays a critical role in protein-protein interactions and binding to sulfated polysaccharides. We have further identified the major proteins of the algal cuticle, providing a framework for addressing the evolutionary origins of the cuticle and raising important questions regarding its role, particularly across the red algal life cycle marked by major structural differences in its ECM.

Extracellular Matrix↗

PubMed2026

Perineuronal net degradation in aggressive glioblastomas with KANK1::NTRK2 fusions.

BACKGROUND: Approximately 10% of glioblastomas harbor targetable genomic fusions. NTRK2 participates in a variety of fusion events that drive tumorigenesis. Two previous reports have described KANK1::NTRK2 fusions in adult glioblastoma patients with poor survival. METHODS: We performed a retrospective analysis of glioblastoma patients treated at Dartmouth-Hitchcock Medical Center (DHMC) from 2020 to 2025 to identify cases harboring KANK1::NTRK2 fusions. Clinical presentation, treatment, histopathologic features, and outcomes were reviewed. In addition, we conducted GeoMx whole-transcriptome and high-plex proteomic digital spatial profiling of a KANK1::NTRK2-positive glioblastoma and a comparator tumor from a long-term survivor. Candidate biomarkers were orthogonally validated using immunohistochemistry and/or immunofluorescence. RESULTS: Two patients with KANK1::NTRK2 fusion glioblastoma were identified, both demonstrating rapid progression, therapeutic resistance, and survival of less than 7 months. Proteomic profiling showed increased expression and activation of canonical NTRK2 downstream signaling pathways, particularly MEK1/2 and ERK1/2. This was accompanied by upregulation of extracellular matrix remodeling enzymes, including MMP3, MMP14, and ADAM15, along with reduced expression of extracellular matrix-associated transcripts and perineuronal net components in particular compared to a non-fusion glioblastoma. CONCLUSIONS: These limited, hypothesis-generating findings suggest constitutive NTRK2 signaling may promote coordinated extracellular matrix degradation and remodeling, potentially facilitating rapid and aggressive tumor growth and invasion in a subset of glioblastomas.

NTRK gene fusion↗

PubMed2025

Exploring Potential Causality and Molecular Mechanisms between Heart Failure and Renal Failure: Insights from Mendelian Randomization Studies, the MIMIC-IV Database and the Gene Expression Omnibus Database.

UNLABELLED: Introduction: Heart failure (HF) and renal failure (RF) frequently coexist as cardiorenal syndrome, but their underlying causal mechanisms remain poorly defined. METHODS: This study applied Mendelian randomization (MR) using genome-wide association study (GWAS) datasets to investigate the causal effect of HF on RF. The inverse variance weighted method assessed causality, and summary-data-based MR (SMR) was used to identify therapeutic targets. Additional analyses included 211 gut microbiota traits and 1,400 serum metabolites. Validation was performed using the MIMIC-IV database. Transcriptomic data were analyzed to identify differentially expressed genes (DEGs) and key transcription factors (TFs). RESULTS: This study found that HF significantly increases the risk of RF (OR = 1.54, 95% CI: 1.07-2.23, p = 0.020). SMR analysis identified SURF1 and MAP3K11 as potential therapeutic targets for HF and RF. One gut microbiota genus and one serum metabolite showed causal associations with both diseases. MIMIC-IV data supported the HF-RF association (OR = 2.94, 95% CI: 2.81-3.07, p < 0.001). A total of 11 overlapping DEGs were enriched in the MAPK cascade, with RELA identified as a key TF. CONCLUSION: This study provides genetic and molecular evidence supporting a causal role of HF in RF, highlighting microbial, metabolic, and immune mechanisms as potential therapeutic targets. .

Humans↗

PubMed2025

Methylation patterns of the nasal epigenome of hospitalized SARS-CoV-2 positive patients reveal insights into molecular mechanisms of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has varied presentations from asymptomatic to death. Efforts to identify factors responsible for differential COVID-19 severity include but are not limited to genome wide association studies (GWAS) and transcriptomic analysis. More recently, variability in host epigenomic profiles have garnered attention, providing links to disease severity. However, whole epigenome analysis of the respiratory tract, the target tissue of SARS-CoV-2, remains ill-defined. RESULTS: We interrogated the nasal methylome to identify pathophysiologic drivers in COVID-19 severity through whole genome bisulfite sequencing (WGBS) of nasal samples from COVID-19 positive individuals with severe and mild presentation of disease. We noted differential DNA methylation in intergenic regions and low methylated regions (LMRs), demonstrating the importance of distal regulatory elements in gene regulation in COVID-19 illness. Additionally, we demonstrated differential methylation of pathways implicated in immune cell recruitment and function, and the inflammatory response. We found significant hypermethylation of the FUT4 promoter implicating impaired neutrophil adhesion in severe disease. We also identified hypermethylation of ELF5 binding sites suggesting downregulation of ELF5 targets in the nasal cavity as a factor in COVID-19 phenotypic variability. CONCLUSIONS: This study demonstrated DNA methylation as a marker of the immune response to SARS-CoV-2 infection, with enhancer-like elements playing significant roles. It is difficult to discern whether this differential methylation is a predisposing factor to severe COVID-19, or if methylation differences occur in response to disease severity. These differences in the nasal methylome may contribute to disease severity, or conversely, the nasal immune system may respond to severe infection through differential immune cell recruitment and immune function, and through differential regulation of the inflammatory response.

Humans↗

PubMed2026

Transcriptome-based epigenetic screening identifies DNA hypermethylation signatures as prognostic biomarkers in oral squamous cell carcinoma.

Promoter DNA hypermethylation is a key epigenetic mechanism of gene silencing in cancer, yet the DNA hypermethylome of oral squamous cell carcinoma (OSCC) and its prognostic relevance remain poorly characterized. Here, we systematically identified and validated novel hypermethylated genes with prognostic significance in OSCC using a genome-wide discovery and multi-platform validation strategy. Candidate genes were first identified by pharmacologic demethylation combined with RNA sequencing across OSCC cell lines, then validated by quantitative RT-PCR, methylation-specific PCR, and bisulfite sequencing in OSCC cell lines, normal oral mucosa, and primary OSCC tumors, with independent confirmation in the TCGA-HNSC dataset. Immunohistochemistry confirmed protein-level silencing, and Kaplan-Meier survival analysis assessed prognostic significance across both cohorts. This pipeline identified five candidate genes, GPX3, ANG, CTGF, GPRC5B, and BAMBI, exhibiting cancer-specific promoter hypermethylation associated with transcriptional and protein silencing in OSCC. Validation in oral cavity tumor samples extracted from the TCGA-HNSC dataset confirmed tumor-specific hypermethylation and revealed significant inverse correlations between methylation and expression for GPX3, GPRC5B, and CTGF. Notably, CTGF hypermethylation was independently associated with poor overall survival in both cohorts (institutional cohort, p=0.03; oral tumor subset from TCGA-HNSC, p=0.01), and a combined ANG+CTGF methylation signature showed superior and reproducible prognostic performance across both platforms. Pathway analysis linked these genes to epithelial-mesenchymal transition and interferon response signaling. This study establishes the first validated DNA methylation biomarker panel for OSCC prognosis, identifying CTGF hypermethylation as a robust prognostic driver with translational potential for clinical risk stratification.

Humans↗

PubMed2026

transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics.

MOTIVATION: Understanding spatial organization, intercellular interactions, and regulatory networks within the spatial context of tissues is crucial for uncovering complex biological processes and disease mechanisms. Spatial transcriptomics technologies have revolutionized this field by enabling the spatially resolved profiling of gene expression. 10× Visium has emerged as the predominant spatial technology, but its low resolution and the complexity of integrating multimodal datasets present significant analytical challenges, particularly for researchers with limited computational and statistical expertise. Current spatial transcriptomics analysis platforms generally fall short of effectively integrating multimodal data and maximizing the utility of spatial information-such as uncovering complex cellular spatial dependencies, multimodal gradient patterns, and spatial coexpression of ligand-receptor pairs and regulatory networks related to disease or biological states-thereby limiting their ability to provide comprehensive end-to-end analytical workflows when analyzing 10× Visium data. RESULTS: To address these limitations, we developed transFusion, a novel, advanced web-based platform specializing in the most comprehensive and effective integration analysis of scRNA-seq and 10× Visium spatial transcriptomics data. transFusion offers 12 key functions, from basic visualization to advanced analyses, including intercellular dependency analysis, ligand-receptor coexpression identification and visualization, and spatial multimodal gradient variation patterns. Two case studies were used to demonstrate transFusion's capabilities in exploring tissue architecture, intercellular communication, dependency networks, and multimodal gradient variation patterns with minimal computational skills and statistical expertise. transFusion provides a flexible and powerful framework for multimodal data integration analysis. AVAILABILITY AND IMPLEMENTATION: transFusion is freely available at https://github.com/WQLin8/transFusion.

Spatial Transcriptomics↗

PubMed2026

Integrating histology and spatial transcriptomics via multimodal transformers and contrastive representation learning for accurate gene expression prediction.

Predicting spatial gene expression from Histological images is a fundamental task in understanding tissue organization and molecular phenotypes. However, existing methods often rely on single-model representations or lack effective alignment between image and transcriptomic features. To address these limitations, we propose a unified multimodal learning framework that integrates histological imaging and spatial transcriptomics through a shared latent representation space. Specifically, histological H&E images are encoded by a ResNet50-based convolutional stem and a MobileViT Transformer backbone to extract hierarchical visual representations. Both modalities are projected into a shared latent space via linear-GELU-dropout transformation blocks, enabling cross-modal alignment through a contrastive learning objective that maximizes agreement between the corresponding image and the spot embeddings. Experimental results on the 10x Genomics Visium dataset of human liver tissue demonstrate that MViTGene achieves significantly higher prediction accuracy than existing methods across multiple gene subsets, with improvements of 20%, 33%, and 12% in predicting marker genes, highly expressed genes, and highly variable genes, respectively. The significant improvement in relevance indicates that the model can more accurately capture the true correspondence between tissue morphology and gene expression, therefore enabling more reliable biological interpretation. It provides a computational tool for high-throughput spatial gene expression prediction that balances performance and interpretability.

Humans↗

PubMed2026

Integrated transcriptomic and metabolomic analyses provide new insights into the response of black rockfish (Sebastes schlegelii) larvae to temperature fluctuations.

Sebastes schlegelii usually encounter elevated and fluctuating water temperatures near its upper thermal limit in summer, yet the hepatic responses of larvae to repeated temperature fluctuation regimes remain unclear. To address this question, S. schlegelii larvae were exposed for 8 days to four thermal regimes: constant 18 °C (CT), constant 28 °C (HT), intermittent cooling from 18 to 8 °C followed by recovery to 18 °C (FL), and intermittent warming from 18 to 28 °C followed by recovery to 18 °C (FH). Survival rate was evaluated, and integrated liver transcriptomic and metabolomic analyses were performed. Final survival rates were 96.67% in the CT group, 97.78% in the FL group, and 77.78% in the FH group. Survival rate in the HT group (38.89%) was significantly lower than that in the other three groups (P < 0.05). HTvsCT, FLvsCT, FHvsCT, and FHvsHT comparisons identified 2598, 1207, 622, and 2404 differentially expressed genes and 627, 606, 690, and 610 differential metabolites, respectively. KEGG enrichment analyses of DEGs and SDMs in HTvsCT highlighted HSP-mediated proteostasis, endoplasmic-reticulum protein processing, branched-chain and sulfur amino acid metabolism, glutathione metabolism, and central carbon metabolism, with upregulated hsp90aa1, bckdha, gclc, and pfkp and reduced levels of branched-chain amino acids and methionine. Compared with HT, FH showed attenuated disturbances in proteostasis, amino acid and redox regulation, and central carbon metabolism, together with recovery-associated glycerophospholipid turnover. FL primarily induced polyunsaturated fatty acid (PUFA)-related membrane lipid remodeling. These findings indicate that hepatic responses differed between continuous high-temperature exposure and temperature fluctuations and between fluctuation regimes.

Animals↗

PubMed2026

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes remain unclear. METHODS: Transcriptomic data from human PAH and control lung tissue were obtained from the Gene Expression Omnibus (GEO) database, whereas ferroptosis-related genes (FRGs) were sourced from the MsigDb and FerrDb databases. Differentially expressed FRGs (DE-FRGs) were identified through the intersection of FRGs with differentially expressed genes (DEGs). Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Key hub genes were identified through Least Absolute Shrinkage and Selection Operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and weighted correlation network analysis (WGCNA). Gene set enrichment analysis (GSEA) was conducted to explore the functional roles and associated pathways of hub genes. The relationship between hub genes and immune infiltration was investigated. Expression levels of potential biomarkers were validated via Quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) in two PAH animal models (monocrotaline-induced and Sugen5416 plus hypoxia-induced PAH). Finally, molecular docking was employed to screen potential therapeutic compounds. RESULTS: A total of 133 DE-FRGs were identified, with KEGG and GO analyses highlighting their involvement in intracellular iron homeostasis and ferroptosis. Hub genes, notably FZD7 and NFE2, were identified using LASSO, SVM-RFE, and WGCNA. Immune infiltration analysis suggested that monocytes and neutrophils play key roles in PAH pathogenesis. Validation in PAH animal models showed significant upregulation of Fzd7 and downregulation of Nfe2 in lung tissues of both MCT- and SuHx-induced PAH models. Molecular docking identified tetrachlorodibenzodioxin (TCDD) has good binding affinity. CONCLUSION: In summary, we investigated two ferroptosis-related biomarkers, FZD7 and NFE2, in PAH using transcriptomics, offering new insights into molecular mechanisms and potential targeted therapies for the disease.

Ferroptosis↗

PubMed2024

Haplotype-resolved genome assembly and implementation of VitExpress, an open interactive transcriptomic platform for grapevine.

Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous Vitis vinifera cultivars by combining high-fidelity long-read sequencing and high-throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar. The deletions/insertions, inversions, translocations, and duplications provide insight into the evolutionary history and parental relationship among grape varieties. Integration of de novo single long-read sequencing of full-length transcript isoforms (Iso-Seq) yielded a highly improved genome annotation. Given its higher contiguity, and the robustness of the IsoSeq-based annotation, the Chasselas assembly meets the standard to become the annotated reference genome for V. vinifera. Building on these resources, we developed VitExpress, an open interactive transcriptomic platform, that provides a genome browser and integrated web tools for expression profiling, and a set of statistical tools (StatTools) for the identification of highly correlated genes. Implementation of the correlation finder tool for MybA1, a major regulator of the anthocyanin pathway, identified candidate genes associated with anthocyanin metabolism, whose expression patterns were experimentally validated as discriminating between black and white grapes. These resources and innovative tools for mining genome-related data are anticipated to foster advances in several areas of grapevine research.

Vitis↗

PubMed2025

BISON: bi-clustering of spatial omics data with feature selection.

MOTIVATION: The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profiling while preserving spatial and morphological context. Understanding gene functions and interactions in different spatial domains is crucial, as it can enhance our comprehension of biological mechanisms, such as cancer-immune interactions and cell differentiation in various regions. It is necessary to cluster tissue regions into distinct spatial domains and identify discriminating genes (DGs) that elucidate the clustering result, referred to as spatial domain-specific DGs. Existing methods for identifying these genes typically rely on a two-stage approach, which can lead to the phenomenon known as double-dipping. RESULTS: To address the challenge, we propose a unified Bayesian latent block model that simultaneously detects a list of DGs contributing to spatial domain identification while clustering these DGs and spatial locations. The efficacy of our proposed method is validated through a series of simulation experiments, and its capability to identify DGs is demonstrated through applications to benchmark SRT datasets. AVAILABILITY AND IMPLEMENTATION: The R/C++ implementation of BISON is available at https://github.com/new-zbc/BISON.

Software↗

PubMed2026

Identification of tomato leaf miner secretory proteins and their roles in influencing plant defenses.

The tomato leaf miner (Tuta absoluta) is a globally destructive pest that cause extensive damage to tomato crops by chewing mouthparts, leading to severe necrosis, fruit abortion, and substantial yield losses. To date, the elicitors/effectors of T. absoluta have not been characterized. In this study, we combined proteomic profiling of T. absoluta-infested tomato leaves with transcriptomic analysis of salivary glands to identify candidate molecules involved in herbivory-driven plant responses. Bioinformatics analyses predicted 40 candidate elicitors and effectors, which were subsequently assessed through transient expression assays in Nicotiana benthamiana. The results demonstrated that the candidate number 33 (T. absoluta 33, Ta33) induced cell death in both the intracellular space and the apoplast, while Ta21 triggered a strong apoplastic reactive oxygen species (ROS) burst. Conversely, Ta38 effectively suppressed INF1-induced cell death. Quantitative real-time PCR analysis further showed that these genes were highly expressed during the feeding stage, supporting their involvement in plant-insect molecular dialogue. This study systematically identified and characterized elicitors and effectors of T. absoluta, providing a foundational framework for elucidating its herbivory mechanisms and developing targeted management strategies.

Moths↗

PubMed2026

Integrating transcriptomics and metabolomics reveals the molecular landscape of sperm maturation driven by regional differentiation in the epididymis of Guizhou-Guiqian semi-fine wool sheep.

Epididymal regionalized differentiation is crucial for sperm maturation. However, little is known about the synergistic remodeling mechanisms of different epididymal segments at the transcriptional and metabolic levels during sexual maturation in ruminants (especially sheep). We investigated the caput, corpus, and cauda epididymidis of pre-pubertal (2-month-old) and post-pubertal (7-month-old) Guizhou-Guiqian semi-fine wool sheep using histology, RNA sequencing, and metabolomics. Post-pubertal tissues exhibited increased luminal diameters, cilia lengths, and abundant cauda spermatozoa. Transcriptomic analysis revealed increasing differentially expressed genes (DEGs) along the caput-corpus-cauda axis (4642, 6103, and 7698 DEGs, respectively). Metabolomics detected 786 unique differentially accumulated metabolites (DAMs). Region-specific analysis showed that in the caput, up-regulated pathways (fructose/mannose metabolism; HK2, ALDOA, HKDC1) provide energy and substrates for initial sperm motility. In the corpus, down-regulated genes associated with extracellular matrix and tight junctions suggested epithelial barrier remodeling to establish an immune-tolerant microenvironment. The cauda specifically up-regulated the pentose phosphate pathway (FBP1, GPI) and glutathione metabolism, maintaining redox homeostasis for long-term sperm storage. Additionally, glycerophospholipid metabolism was enriched across all segments, where PEMT, AGPAT5, and LCAT likely regulate sperm plasma membrane fluidity. In conclusion, during sexual maturation, the caput drives energy metabolism and glycosylation, the corpus establishes immune tolerance, and the cauda maintains antioxidant homeostasis. The glycerophospholipid network throughout the across all epididymal segments synergistically remodels sperm membrane. This study reveals the underlying multi-omics regulatory mechanisms of epididymal functional differentiation, providing a theoretical basis for elucidating the molecular mechanisms of sperm maturation in this breed and for the molecular breeding of early reproductive performance in rams.

Animals↗

PubMed2026

Comprehensive analysis of metabolomics and transcriptomics of radiation-induced rectal injury.

Radiation-induced rectal injury (RRI) significantly affects the quality of life in patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy (NCRT). Non-targeted liquid chromatography-mass spectrometry metabolomics analysis and transcriptomic analysis were conducted to explore RRI characteristics. Hematoxylin-eosin and Masson staining confirmed radiation-induced injury in rectal tissue within the radiotherapy target region. Orthogonal partial least squares discriminant analysis identified 823 differentially expressed metabolites (DEMs). Transcriptomic analysis revealed 400 differentially expressed genes (DEGs). Enrichment analysis revealed that DEMs and DEGs were primarily involved in metabolic, immune, and signal transduction pathways. Integrated analysis demonstrated significant enrichment of DEMs and DEGs in the arachidonic acid metabolism pathway. Pearson's correlation and canonical correlation analyses were used to assess the association between DEMs and DEGs within this pathway. In conclusion, this study identified key biological regulatory pathways involved in RRI through a multi-omics approach, offering potential targets for its diagnosis and treatment.

Humans↗