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PubMed2026

Full-length single-cell spatial transcriptomics reveals spatial and cell-type-specific transcript isoforms in the primate brain.

The primate brain exhibits complex RNA alternative splicing heterogeneity crucial for functional complexity, yet systematic spatial isoform characterization has been lacking. We developed Fullscope-seq, a full-length single-molecule large field-of-view spatial transcriptomics sequencing method at single-cell resolution, based on programmed concatenation cDNA for multiple long-read sequencing platforms. Applying Fullscope-seq to the macaque brain, we uncovered thousands of genes exhibiting differential transcript usage (DTU) across cortical layers, cell types and brain regions. Fullscope-seq resolved hundreds of major isoform switches across distinct brain regions and identified DTUs between superficial and deep cortical layers. Cortical layer-specific DTUs showed cell-composition dependence, whereas regional DTUs were regulated according to both cellular composition and spatial contexts. These isoform variations showed substantial enrichment for neuropsychiatric disorder-associated genes and were conserved across platforms and species. Our study establishes a scalable framework for spatial isoform analysis and provides a resource for understanding transcriptomic diversity in complex tissues.

Animals↗

PubMed2026

Volumetric DNA microscopy for mapping spatial transcriptomes in three dimensions.

The architecture and function of biological systems are inherently three-dimensional, yet most existing spatial transcriptomic technologies remain restricted to thin tissue sections, limiting their capacity to resolve cellular organization and microenvironments within intact tissue volumes. To address this limitation, we developed volumetric DNA microscopy, a scalable, optics-free approach for spatial transcriptome profiling directly within intact biological specimens. The method encodes spatial information into DNA molecules that form a dense intermolecular network in situ, enabling the reconstruction of three-dimensional spatial relationships through short-read sequencing and computational analysis. Here we detail the complete workflow including in situ cDNA synthesis, spatial encoding through DNA nanoball formation, dual-scale proximity bridging between neighboring nanoballs and spatial reconstruction via geodesic spectral embedding. Sequencing libraries can be generated within 7-8 d by a competent graduate-level molecular biologist, followed by standardized downstream computational analysis. Because the workflow requires only routine molecular biology reagents and a benchtop sequencer, volumetric DNA microscopy provides a versatile platform for exploring genetic and morphological features in intact tissues.

Spatial Transcriptomics↗

PubMed2025

Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE). METHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE. RESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively. CONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.

Humans↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Representation learning for multi-modal spatially resolved transcriptomics data.

MOTIVATION: Spatial transcriptomics enables in-depth molecular characterization of samples on a morphology and RNA level while preserving spatial location. Integrating the resulting multi-modal data is an unsolved problem, and developing new solutions in precision medicine depends on improved methodologies. RESULTS: We introduce AESTETIK, a convolutional deep learning model that jointly integrates spatial, transcriptomics, and morphology information to learn accurate spot representations. AESTETIK yielded substantially improved cluster assignments on widely adopted technology platforms (e.g. 10x Genomics™, NanoString™) across multiple datasets. We achieved performance enhancement on structured tissues (e.g. brain) with a 21% increase in median ARI over previous state-of-the-art methods. Notably, AESTETIK also demonstrated superior performance on cancer tissues with heterogeneous cell populations, showing a 2-fold increase in breast cancer, 79% in melanoma, and 21% in liver cancer. We expect that these advances will enable a multi-modal understanding of key biological processes. AVAILABILITY AND IMPLEMENTATION: AESTETIK is implemented in Python 3 and is available as open source software at http://www.github.com/ratschlab/aestetik. The Snakemake pipeline for reproducing the results is available at http://www.github.com/ratschlab/st-rep.

Spatial Transcriptomics↗

PubMed2025

Influence of Gonadal and Chromosomal Sex on the Brain Transcriptome in a Mouse Species with Natural Sex Reversal.

Sex chromosomes are expected to play a role in shaping the transcriptional architecture of sexual dimorphism, through the direct expression of sex-linked genes, by regulating autosomal genes, or in interactions with hormones. Yet, their degree of involvement remains elusive partly because chromosomal sex (e.g. XX/XY) and gonadal sex (ovaries or testes) are usually inextricably intertwined. They are, however, dissociated in the African pygmy mouse, Mus minutoides, in which a feminizing X (X*) has evolved, resulting in three female genotypes (XX, XX*, and X*Y) and one male genotype (XY). Furthermore, all sex chromosomes are fused to autosomes (neo-sex chromosomes: neo-X, neo-X* and neo-Y). Despite complete sex reversal, X*Y females show distinctive phenotypes with greater fertility, divergent maternal care strategies, and the masculinization of some traits (e.g. enhanced aggressiveness). By comparing the brain transcriptome of the four sexual genotypes, we show that differential gene expression is mainly linked to gonadal sex but also, and significantly, to chromosomal sex. Genes influenced by chromosomal sex are overrepresented on sex-linked genomic regions, and some are strong candidates to explain X*Y-specific behavioral and reproductive traits. Our results also suggest the preferential inactivation of the X* chromosome in XX* females, only in the brain, which could explain their trait similarities with XX females. Overall, we show that sex and neo-sex chromosomes have profoundly impacted the brain transcriptome in ways that reflect their new transmission modes, evolutionary trajectories, and resulting genomic conflicts.

Animals↗

PubMed2026

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES: Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS: We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS: We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS: Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Female↗

PubMed2026

Identification of potential key genes involved in iron deficiency for sepsis: A retrospective cohort and transcriptomic study.

Iron overload has been associated with sepsis, but the role of iron deficiency and its molecular links remain unclear. We investigated the association between iron deficiency and sepsis and identified candidate genes potentially linking these conditions. MIMIC-IV data were used to assess the association between serum iron and sepsis status. Transcriptomic datasets from dietary iron-deficient mice (GSE10421), LPS-induced septic mice (GSE267388), and a human blood sepsis cohort (GSE137340) were sequentially analyzed to identify and externally evaluate candidate genes. IEU Open GWAS summary statistics were used for exploratory Mendelian randomization (MR). Exploratory drug prediction was performed using L1000FWD, followed by molecular docking analysis. Patients with sepsis had significantly lower serum iron levels, and restricted cubic spline analysis showed a nonlinear association between serum iron and the odds of sepsis. Cross-tissue transcriptomic analysis identified Sqle, Lss, and Rdh11 as candidate genes. In the human blood cohort, SQLE and RDH11 were significantly increased, whereas LSS was not significantly altered. Exploratory MR showed that genetically proxied SQLE expression was associated with higher odds of sepsis (odds ratio [OR] = 1.23, P = 1.67 × 10-3), whereas LSS expression was associated with lower odds (OR = 0.97, P = 8.90 × 10-4); RDH11 showed no significant association (OR = 1.01, P = .90). Drug prediction identified ML106 as the top-ranked candidate drug, and molecular docking predicted potential binding poses with SQLE and LSS. Serum iron showed a nonlinear association with sepsis status. SQLE, LSS, and RDH11 emerged as candidate genes, with concordant expression changes of SQLE and RDH11 observed in human blood. MR findings for SQLE and LSS were exploratory and require further validation. ML106 was identified through exploratory drug prediction and requires experimental validation before its therapeutic relevance can be established.

Sepsis↗

PubMed2026

Transcriptomic and proteomic signatures underlying nymphal adaptation and foam production in the forage pest Mahanarva spectabilis.

The spittlebug Mahanarva spectabilis (Distant, 1909) (Hemiptera: Cercopidae) is an important pest of forage grasses in South America, where its nymphs cause pasture damage by feeding on xylem sap and producing a characteristic foam that protects them against environmental stressors. To investigate the molecular basis of this adaptation, we integrated RNA-seq analysis of nymphs with LC-MS/MS proteomics of the Batelli gland, the primary source of foam secretion. De novo assembly of 100,666 unigenes revealed broad functional diversity, with strong representation of detoxification enzymes (CYP450s, GSTs, UGTs, carboxylesterases), transporters and ion pumps, cuticle proteins, and stress- and immunity-related genes. Nearly 16% of loci exhibited alternative splicing, particularly within detoxification, chemosensory and osmoregulatory gene families, highlighting evidence of transcriptomic variability. Signal peptide and secreted protein predictions identified 168 high-confidence candidate secreted proteins, including detoxification enzymes, proteases, structural proteins and immune-related factors, several of which are consistent with antimicrobial and surfactant-related functions. Proteomic profiling of the Batelli gland confirmed 500 proteins, enriched in chaperones, metabolic enzymes, detoxification pathways and osmoregulatory components, with the most abundant proteins corresponding to Hsp70 chaperones, ATP synthases, cuticle proteins and carbonic anhydrases. Together, these results provide an integrative transcriptomic and proteomic overview for M. spectabilis nymphs, highlighting genes and proteins associated with xylem feeding, foam production and responses potentially related to environmental stress tolerance. This comprehensive dataset not only advances the understanding of spittlebug biology but also identifies candidate molecular targets that may inform innovative strategies for controlling nymphal stages and mitigating spittlebug damage in forage systems.

Animals↗

PubMed2025

Integrative spatial transcriptomic analysis pinpoints the role of the ferroxidase, TaMCO3, in wheat root tip iron mobilization.

Roots play a critical role in the sensing and absorption of essential minerals from the rhizosphere. Iron (Fe) deficiency, for example, triggers a well-known series of physiological and molecular responses within roots that facilitate uptake, which differs between monocots and dicots. In monocots, little is known about the molecular responses that occur within specific root development zones in response to iron deprivation, and how these differences result in overall nutrient uptake. Here, we conducted a transcriptome analysis of wheat root tips under Fe deficiency (-Fe) and performed a comparative transcriptome analysis with the previous datasets generated from the whole root. Gene ontology analysis of differentially expressed genes highlighted the significance of oxidoreductase activity and metal/ion transport in the root tip, which are critical for Fe mobilization. Interestingly, wheat, an allohexaploid species consisting of three different genomes (A, B, and D) displayed varying gene expression levels arising from the three genomes that contributed to similar molecular functions. Detailed analysis of oxidoreductase function at the root tip revealed multiple multicopper oxidase (MCO) proteins, such as Fe-responsive TaMCO3, that likely contribute to the overall ferroxidase activity. Further characterization of TaMCO3 shows that it complements the yeast FET3 mutant and rescues the -Fe sensitivity phenotype of Arabidopsis atmco3 mutants by enhancing vascular Fe loading. Transgenic wheat lines overexpressing TaMCO3 exhibited increased root Fe accumulation and improved tolerance to -Fe by augmenting the expression of Fe-mobilizing genes. Our findings highlight the role of spatially resolved gene expression in -Fe responses, suggesting strategies to reprogram cells for improved nutrient stress tolerance.

Triticum↗

PubMed2026

An integrated proteomics and transcriptomics analysis highlights concordance between protein turnover and carbohydrate transport and metabolism as key functional categories during the growth of Trichophyton rubrum.

Dermatophytes are a class of keratinophilic skin fungi that invade host skin, hair, and nails to acquire nutrients. An integrated multi-omics approach utilizing liquid chromatography-tandem mass spectrometry and RNA-seq after growth in a protein-rich soy medium was employed to capture the major subset of secreted protein families of Trichophyton rubrum. The secretome consisted mainly of proteases and cell wall-degrading enzymes, with subtilisins (Sub6 and Sub7), metallopeptidase (LAP2), and chitinase having the most abundant peptides. Transcriptional profiling indicated fungal adaptation in protein-rich media to process the protein nutrients through modulation of metabolism and general cellular function pathways. Correlation analysis between proteomics and transcriptomics data using functional KOG categories shows high concordance of KOG categories O (posttranslational modification, protein turnover, and chaperones), P (inorganic ion transport and metabolism), and G (carbohydrate transport and metabolism), as per cosine similarity analysis.IMPORTANCEDermatophytes are keratinophilic skin fungal pathogens that invade host skin, hair, and nails to acquire nutrients. There is an epidemic-like increase in infections, as well as an increase in antimicrobial resistance among dermatophytes, as witnessed over the last decade. There is hence a need to understand the key pathways and virulence factors required during growth and infection. We present an integrated multi-omics analysis (proteomics and transcriptomics data) using a vector-based similarity approach to show high concordance of KOG functional categories belonging to posttranslational modification, protein turnover, carbohydrate transport, and metabolism.

Proteomics↗

PubMed2026

CAGNet: a structure-aware clustering-alternated graph network for cell-cell interaction inference in spatial transcriptomics.

MOTIVATION: Understanding cell-cell interactions (CCIs) in spatial transcriptomics is crucial for uncovering the spatial organization and functional heterogeneity of tissues. However, existing graph-based models typically rely on static clustering or fixed adjacency structures, which limits their ability to capture dynamic cellular relationships. RESULTS: We propose CAGNet, a two-stage framework for CCI inference from spatial transcriptomics data. In Stage 1, a Graph Attention Network encoder with joint feature and graph reconstruction learns structure-aware node embeddings from spatial gene expression profiles. In Stage 2, an alternating optimization mechanism iteratively updates cluster centers via KL-guided soft assignment and refines node embeddings through spatial graph reconstruction, establishing a closed-loop between representation learning and clustering. Experiments on three 10x Genomics Visium datasets demonstrate that CAGNet consistently outperforms six CCI inference baselines across ACC, AUC, AP, Precision, Recall, and F1. CAGNet also achieves the highest Adjusted Rand Index on all three datasets against six spatial domain identification methods, confirming that the learned embeddings capture biologically relevant spatial organization. Information-theoretic analysis further shows that CAGNet retains the highest mutual information between input features and learned embeddings among all compared methods. Ablation studies and 5-fold cross-validation confirm the contribution of each component and the reproducibility of the results. AVAILABILITY: The proposed method is implemented in the CAGNet package available at http://github.com/mahan1233333-maker/CAGNet .

Spatial Transcriptomics↗

PubMed2026

Integrated Transcriptomic and Proteomic Analysis Elucidates the Mechanisms of Huperzine A Injection Against Cerebral Ischemia/Reperfusion Injury.

BACKGROUND: After recanalization in acute ischemic stroke, cerebral ischemia/reperfusion injury (CI/RI) drives a cascade of pathophysiological events that worsen clinical outcomes, yet effective therapeutic options remain limited. Given the neuroprotective potential of Huperzine A (HupA), the efficacy of HupA injection (HAI, a major clinical formulation of HupA) against CI/RI and its underlying molecular basis warrant investigation. METHODS: In a mouse model of CI/RI, neurological performance, locomotor ability, cerebral infarction, histopathological alterations, and apoptotic neurons were jointly used to assess the anti-CI/RI effect of HAI at two different doses. An integrated transcriptomic and proteomic strategy was adopted to decipher the key anti-CI/RI mechanisms of HAI and then validated experimentally. RESULTS: Compared with vehicle‑treated CI/RI mice, HAI intervention significantly alleviated neurobehavioral deficits, decreased infarct size, mitigated histopathological damage, and suppressed neuronal apoptosis (P < 0.01). Both separate and combined transcriptomic and proteomic analyses highlighted that the complement and coagulation cascades, together with inflammation, were strongly correlated with HAI's beneficial action in preventing CI/RI. Indeed, HAI treatment effectively normalized the dysregulated mRNA and protein levels of pivotal targets within the complement and coagulation cascades, including C3, C5, C9, CFB, MASP2, F7, F10, F12, and SERPINE1, in the damaged cortical tissues of CI/RI mice (P < 0.05). Moreover, this intervention markedly attenuated the abnormally elevated expression of multiple inflammatory mediators, including TLR2, TLR4, TNF-α, IL-1β, IL-6, CCL2, CCL5, CXCL1, ICAM1, S100A9, LCN2, MMP8, and MMP9, at both the mRNA and protein levels (P < 0.01). CONCLUSION: Collectively, our data suggest that HAI may confer efficacy against CI/RI by modulating the complement and coagulation cascades and orchestrating the inflammatory response. Although further investigation is warranted, these preliminary findings provide a foundation for accelerating the clinical translation of HAI as a novel neuroprotectant against CI/RI in ischemic stroke.

Animals↗

PubMed2026

Morphological, Physiological and Transcriptomic Changes in Response to Water Deficit Stress in Brassica napus L.

Yield losses due to water-deficit (WD) conditions, especially during the reproductive stages of plant development, pose a significant threat to global canola (Brassica napus L.) production. Therefore, it is critical to investigate traits contributing to improved productivity under increased WD conditions. Here we present phenotypic, physiological and transcriptomic changes in response to WD across contrasting canola accessions exhibiting variation in drought resistance-related traits. WD significantly reduced shoot biomass, plant height, harvest index, leaf water content, photosynthetic CO2 assimilation rate, intrinsic water-use efficiency and carbon isotope discrimination. WD caused 49 to 100% of the seed yield reduction: the minimum seed yield reduction (49.66%) was observed in a doubled-haploid (DH) line, 06-5101.137, while the maximum yield reduction (94.1 to 100%) occurred in the late-flowering DH lines (06.5101.088 and 06-5101.306). Seed yield showed a positive correlation (r = 0.29 to 0.95) with shoot biomass and harvest index, leaf water content, photosynthetic CO2 assimilation rate, intrinsic water use efficiency and carbon isotope discrimination. However, it showed negative correlations with days to flower, leaf specific weight, root length, root biomass (r = -0.04 to -0.79) across water treatments. The specific leaf transcriptome analysis of the two parental lines of DH population that exhibit variation for effective water use under well-watered and water-deficient conditions revealed different categories of differentially expressed genes (DEGs): WD-responsive DEGs in BC1329 parental line (1116) and BC9102 (1205) with 754 and 853 DEGs unique to BC1329 and BC9102, respectively, WD-responsive DEGs (906), genotype-dependent DEGs (8465) and genotype × treatment interaction DEGs (353). DEG annotations revealed that the WD-treatment-affected genes were involved in stress responses and growth and development. We further located 235 DEGs within the QTL regions underlying agronomic and physiological performance. Our study provides a conceptual framework for the morphological, physiological and molecular determinants involved in water-use efficiency. Seedlings' traits with high heritability values, such as shoot biomass, leaf weight, leaf water content and Δ13C, serve as proxies for trait-based selection for improved seed yield under both water-limited and non-water-limited conditions.

Brassica napus↗

PubMed2024

A Strong Dysregulated Myeloid Component in the Epigenetic Landscape of Systemic Sclerosis: An Integrated DNA Methylome and Transcriptome Analysis.

OBJECTIVE: Nongenetic factors influence systemic sclerosis (SSc) pathogenesis, underscoring epigenetics as a relevant contributor to the disease. We aimed to unravel DNA methylation abnormalities associated with SSc through an epigenome-wide association study. METHODS: We analyzed DNA methylation data from whole-blood samples in 179 patients with SSc and 241 unaffected individuals to identify differentially methylated positions (DMPs) with a false discovery rate (FDR) <0.05. These results were further integrated with RNA sequencing data from the same patients to assess their functional consequence. Additionally, we examined the impact of DNA methylation changes on transcription factors and analyzed the relationship between alterations of the methylation and gene expression profile and serum proteins levels. RESULTS: This analysis yielded 525 DMPs enriched in immune-related pathways, with leukocyte cell-cell adhesion being the most significant (FDR = 4.91 × 10-9), prioritizing integrins as they were exposed by integrating methylome and transcriptome data. Furthermore, through this integrative approach, we observed an enrichment of neutrophil-related pathways, highlighting this myeloid cell type as a relevant contributor in SSc pathogenesis. In addition, we uncovered novel profibrotic and proinflammatory mechanisms involved in the disease. Finally, the altered epigenetic and transcriptomic signature revealed an increased activity of CCAAT/enhancer-binding protein transcription factor family in SSc, which is crucial in the myeloid lineage development. CONCLUSION: Our findings uncover the impaired epigenetic regulation of the disease and its impact on gene expression, identifying new molecules for potential clinical applications and improving our understanding of SSc pathogenesis.

Humans↗

PubMed2026

Transcriptomic insights into exogenous fatty acid-enhanced halotolerance in Zygosaccharomyces rouxii.

BACKGROUND: High salinity restricts microbial growth during brine-based food fermentation. Although exogenous unsaturated fatty acids improve the salt tolerance of Zygosaccharomyces rouxii, the associated transcriptional mechanisms remain unclear. This study investigated the transcriptomic response of Z. rouxii CGMCC 3791 to palmitoleic acid (C16:1) under high salt conditions. RESULTS: Cells were cultured in yeast extract peptone dextrose (YPD) containing 120 g L-1 NaCl, with or without 20 μg mL-1 C16:1. They were analyzed by RNA sequencing. Principal component analysis clearly separated the two treatments. Using q < 0.05 and |log2 fold change| > 1, 23 differentially expressed genes were identified - three upregulated and 20 downregulated. INO1, MLS1, POX1, MEP2, and SOD5 were among the major responsive genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that peroxisome-associated functions, lipid metabolism, oxidative stress responses, nitrogen utilization, and mitogen-activated protein kinase (MAPK) signaling were the principal C16:1-responsive processes. CONCLUSION: Exogenous C16:1 elicited a focused transcriptional adjustment rather than broad transcriptome-wide reprogramming in salt-stressed Z. rouxii. The results indicated that peroxisome-linked lipid processes and redox regulation were candidate mechanisms underlying fatty-acid-associated halotolerance and provided targets for improving the robustness of high-salt food fermentation. © 2026 Society of Chemical Industry.

Zygosaccharomyces rouxii↗

PubMed2026

Single-cell transcriptomic landscape of the southern green stink bug (Nezara viridula) midgut.

BACKGROUND: The southern green stink bug (SGSB), Nezara viridula, is a globally distributed hemipteran pest that damages many economically important crops. Its midgut supports digestion, defense, symbiosis, and interactions with orally delivered control agents, yet the cellular composition of this tissue remains poorly characterized. We therefore developed a single-cell transcriptomic atlas of the N. viridula midgut. RESULTS: Single-cell RNA sequencing of two biological replicates yielded a quality-filtered data set of 13,763 cells. Unsupervised clustering identified 12 transcriptionally distinct populations with putative annotations, including a stem cell/enteroblast (SC/EB)-like population, seven enterocyte-related populations, goblet-like cells, enteroendocrine cells, visceral muscle cells, and an extracellular-matrix-associated epithelial population. Enterocyte-related populations accounted for more than 77% of recovered cells. Putative annotations were assigned primarily from marker gene enrichment and homology to markers reported in other insects. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses identified population-associated functional enrichment patterns, and pseudotime analysis suggested transcriptional relationships between the SC/EB-like population and several enterocyte- and secretory-associated populations without establishing developmental lineages. Immune- and defense-associated transcripts were preferentially enriched in the pEC2 population, and genes associated with symbiont recognition, insecticide action, xenobiotic transport, and orally delivered double-stranded RNA showed population-biased expression. Descriptive comparisons with published insect midgut data sets identified shared and data-set-specific patterns among annotated populations. CONCLUSION: This atlas provides the first single-cell transcriptomic resource for a stink bug midgut and establishes a descriptive cellular framework for SGSB midgut biology. The dataset prioritizes candidate genes and cell populations for future spatial validation, functional testing, and studies of hemipteran midgut physiology, symbiosis, immunity, and pest-management-relevant traits. © 2026 Society of Chemical Industry.

Nezara viridula↗

PubMed2025

CD40 transcriptomic expression patterns across malignancies: implications for clinical trials of CD40 agonists.

BACKGROUND: CD40 is a T-cell co-stimulatory receptor targeted by next-generation immunotherapies. We conducted a pan-cancer transcriptome analysis of CD40, its ligand, and related immune markers to evaluate co-expression patterns and clinical outcomes. METHODS: We analyzed transcriptome data for CD40, its ligand, and other common checkpoints and co-stimulators (PD-1, PD-L1, PD-L2, CTLA-4, LAG-3, ICOS, CD27, CD28, OX40, and GITR). RNA expression was classified as high (75-100th percentile), moderate (25-74th), or low (0-24th) against a reference population of 735 previously tested solid tumors. RESULTS: Of 514 patients, 114 (22%) showed high, 247 (48%) moderate, and 153 (30%) low CD40 RNA expression. High CD40 expression was most frequent in liver and bile duct (42%), pancreatic (42%), and ovarian (40%) cancers. Both high CD40 and low-moderate CD40 ligand expression-potentially conducive to CD40 agonist therapy-was most frequent in ovarian (33%) and pancreatic (24%) cancer. In both UCSD (N = 514) and TCGA (N = 10,953) cohorts, high CD40 expression significantly correlated with high CD28 and GITR. High CD40 RNA levels were not prognostic for overall survival (OS) from metastatic disease (P = 0.2) (n = 272 immune checkpoint inhibitor (ICI)-naïve patients). High CD40 expression correlated with longer OS from immunotherapy initiation (n = 217 ICI-treated patients; P = 0.04, univariable analysis), but not multivariable analysis, suggesting it may not be an independent predictive biomarker. CONCLUSION: High CD40 expression correlated with liver and bile duct, pancreatic, and ovarian cancers, as well as with CD28 and GITR transcripts. Immune marker co-expression in individual patients merits further exploration for the development of CD40-based and other immunotherapy interventions.

Humans↗