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Comparative transcriptomic and physiological analyses uncover key regulatory pathways associated with drought tolerance in wheat.

Drought severely limits wheat yield, yet its molecular basis remains incompletely understood. We compared a drought-tolerant line (A25) and a drought-sensitive line (A8) under water deficit across three developmental stages using physiological assays and transcriptomics. A25 exhibited stronger osmotic adjustment and antioxidant defense, with higher proline accumulation and enhanced activities of ascorbate peroxidase, catalase, and other ROS-scavenging enzymes. RNA-seq revealed distinct drought-responsive expression patterns, with differentially expressed genes enriched in MAPK signaling and ABA-dependent pathways. ABA-responsive genes were more abundant and strongly induced in A25, suggesting enhanced ABA signal transduction as a key mechanism. Weighted gene co-expression network analysis identified a drought-associated purple module positively correlated with physiological resistance, from which six hub genes (MAPKKK17, Avr9/Cf-9, RPPL1, RGA1, UBC28, AGPs5) were highlighted as potential regulators. Collectively, coordinated activation of ABA signaling and MAPK cascades, mediated by these hub genes, underlies the robust drought tolerance of A25, providing promising molecular targets for wheat breeding and improvement.

Triticum

Metabolic-cell-death gene trio predicts survival and cuproptosis sensitivity in colorectal cancer.

BACKGROUND: Metabolic cell death (MCD) modulates colorectal cancer (CRC) progression, yet its prognostic value remains unexplored. We aimed to build an MCD-centred gene signature for outcome prediction and precision therapy. METHODS: Transcriptomes of 1,174 CRC patients were integrated. Weighted gene co-expression network analysis, differential expressions and least absolute shrinkage and selection operator (LASSO) + random survival forest were successively applied to derive a three-gene (CDKN2A/MPC1/AHCY) risk model. Functional, immune-infiltration, drug-sensitivity and genomic analyses were performed, followed by validation in fresh clinical specimens and cell lines. RESULTS: Integrative metabolic-death transcriptomics identified CDKN2A, MPC1 and AHCY as the hub drivers of CRC. Their three-gene signature robustly stratified patients into high- and low-risk subsets [3-year area under the curve (AUC) 0.83-0.85, P<0.001]. High-risk tumors were enriched for extracellular matrix (ECM)-receptor-interaction pathways, displayed abundant myeloid-derived suppressor cell (MDSC) infiltration and were more vulnerable to AZD8186, AZ960 and JAK inhibitors. Guided by these in-silico findings, we functionally confirmed that CDKN2A silencing markedly repressed proliferation, invasion and migration of SW480/HCT116 cells and potentiated cuproptosis via up-regulation of lipoylated DLAT/DLST and CTR1. CONCLUSIONS: We report the first MCD-derived prognostic platform for CRC that simultaneously predicts survival and therapeutic response. Targeting CDKN2A-enhanced cuproptosis represents a promising metabolic-precision strategy for high-risk patients.

Colorectal cancer (CRC)

Gut microbiota-derived metabolites target C5AR1/KDM2A/HCAR3 axis in inflammatory bowel disease: a multi-machine learning algorithms and molecular docking study.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic recurrent disorder. Gut microbiota-derived metabolites regulate intestinal homeostasis, but their molecular mechanisms in IBD remain unclear. Current studies lack systematic "microbiota-metabolite-target" network mining with multi-method validation. This study integrates network pharmacology, three machine learning algorithms, and molecular docking to construct this regulatory network in IBD. METHODS: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using limma (p < 0.05, |log2FC| > 0.5). Weighted gene co-expression network analysis (WGCNA) with an optimal soft threshold of &#x3b2; = 7 was performed to identify key module genes. Candidate genes were obtained by intersecting DEGs, gut microbiota-associated genes from the gutMGene database, and WGCNA module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of candidate genes. Core genes were identified using three machine learning algorithms (LASSO, Boruta, and SVM-RFE), followed by protein-protein interaction (PPI) network analysis. Molecular docking was performed to assess the binding affinities between hub proteins and gut microbiota-derived metabolites. RESULTS: A total of 885 DEGs were identified between the IBD and control groups, including 463 upregulated and 422 downregulated genes. WGCNA identified 280 key module genes from the purple and yellow modules. The intersection of DEGs, gut microbiota-associated genes, and WGCNA module genes yielded 19 core candidate genes. PPI network analysis combined with three machine learning algorithms jointly identified C5AR1, KDM2A, and HCAR3 as core hub genes. ROC curve analysis demonstrated that all three hub genes achieved AUC values greater than 0.7 in both the training and validation sets, indicating excellent diagnostic performance for IBD. Enrichment analysis revealed significant associations with the TNF, NF-&#x3ba;B, and IL-17 signaling pathways. Molecular docking confirmed stable binding of C5AR1 with 1,3-Diphenylpropan-2-Ol (-7.87 &#xb1; 0.83 kcal&#xb7;mol-&#xb9;) and HCAR3 with 3-Indolepropionic Acid (-6.35 &#xb1; 0.70 kcal&#xb7;mol-&#xb9;), both below -5.0 kcal&#xb7;mol-&#xb9;. CONCLUSION: This study first constructs a "gut microbiota-metabolite-hub gene" axis in IBD, providing a computational framework for microbiota-targeted precision therapy, and identifying C5AR1/KDM2A/HCAR3 as computationally predicted diagnostic biomarkers and 1,3-Diphenylpropan-2-Ol/3-Indolepropionic Acid as candidate intervention molecules that warrant further experimental validation.

Molecular Docking Simulation

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3&#xa0;:&#xa0;1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC >&#xa0;0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans

Network based approach identifies miR-145-3p as a central regulatory hub associated to the progression from localized to metastatic medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is a neuroendocrine tumor originating from calcitonin producing C-cells and accounts for 1-5% of thyroid cancers. Total thyroidectomy is curative in localized disease (N0), whereas lymph node metastases (N1) are associated with poorer prognosis. However, the molecular mechanisms driving the metastatic shift remain poorly understood. This study aimed to identify miRNA features linked to metastatic spread in MTC, focusing on the transition from N0 to N1. Co-expression networks were constructed for N0 and N1 tumors, and differential connectivity analysis was used to identify key miRNAs acting as regulatory hubs. Functional annotation of their target genes was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Reactome pathway analyses. Validation experiments were carried out in MTC cells to evaluate the effects of selected miRNAs on cell proliferation, survival, and MAPK pathway activation. Network analysis revealed distinct miRNA co-expression patterns between N0 and N1 tumors. Differential network analysis highlighted miR-145-3p as a central regulatory hub, exhibiting 29 altered co-expression changes and a marked loss of connectivity in N1. Target enrichment identified 59 validated genes, including key oncogenic drivers such as MYC, PTEN, BCL2, PIK3CA, AKT1, and MAPK7. In MTC cells, simultaneous inhibition of miR-145-3p together with its top co-expressed miRNAs increased proliferation and survival, and enhanced ERK phosphorylation, indicating MAPK pathway activation and a shift toward a more aggressive phenotype. In conclusion, this study identifies a miRNA regulatory hub centered on miR-145-3p that is associated with metastatic progression and highlights the value of network-based approaches in uncovering mechanisms of cancer dissemination. &#xa9; 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

MAPK signaling

Unveiling the molecular basis of gonadal development: Multi-omics uncovers sex-related genes and steroid pathways in Sinonovacula constricta.

The razor clam Sinonovacula constricta is an economically important cultured mollusk in China, but the molecular mechanism of its gonadal development and sexual differentiation remains unclear. This study integrated gonadal transcriptomic, proteomic, and metabolomic analysis to identify key sex-related molecules. Transcriptome analysis identified 2795 DELs and 6497 DEGs between sexes, including the sex-related genes Fem-1b, Fem-1c, GUCY1B2 and FAT4, as well as a regulatory network of 39 lncRNA-mRNA pairs involving Tektin-4, Ropporin-1, Histone H1, and FoxN4. Proteomic analysis revealed 3217 DEPs: Tektin family members, Ropporin-1 and Tssk proteins were upregulated in the testis, while histone H1 and FAT4 were upregulated in the ovary. Metabolomic analysis detected 409 DEMs, with uridine identified as a potential sex differential marker (upregulated in the ovary), and 23 gonadal development-related DEMs showed sex-specific upregulation. Integrative transcriptome-proteome analysis identified 1543 co-expressed DEGs/DEPs enriched in nucleosome assembly, oxidative phosphorylation, and carbon metabolism, including key sex-related genes AKAP14, Tektin/Tssk families, Histone H1, and FAT4. Transcriptome-metabolome integration identified 32 shared KEGG pathways (e.g., biosynthesis of unsaturated fatty acids, pyrimidine metabolism), while proteome-metabolome integration revealed 5 (positive ion) and 6 (negative ion) co-enriched pathways, with alanine, aspartate and glutamate metabolism and oxidative phosphorylation being functionally relevant to gonadal development. Collectively, these results reveal the molecular basis of gonadal development, highlight critical sex-related genes and steroid metabolic pathways, and provide valuable resources for future reproduction and breeding in S. constricta.

Animals

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were&#xa0;shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots

Transcriptomic Association Between Poliovirus Receptor (PVR/CD155) and Claudin Signaling Pathways in Colorectal Cancer.

BACKGROUND/AIM: Enterotoxigenic Bacteroides fragilis promotes colorectal carcinogenesis through toxin-mediated cleavage of E-cadherin, a process facilitated by membrane-associated Claudin-4 (CLDN4). Separately, the poliovirus receptor (PVR/CD155) modulates tumor epithelial and immune dynamics. This study explored potential transcriptomic interactions and co-expression frameworks between PVR and claudin signaling pathways in colorectal cancer. MATERIALS AND METHODS: Transcriptomic and proteomic data from the The Cancer Genome Atlas-colon adenocarcinoma cohort (TCGA-COAD) were evaluated. An exploratory E-cadherin Cleavage Index was modeled to capture transcript-protein discordance. To control for tissue composition heterogeneity without mathematical circularity, a de-circularized, non-parametric partial rank residual model adjusted for independent CLDN4 expression was deployed within the stable microsatellite-stable (MSS) sub-cohort (N=473). RESULTS: Multivariable survival models showed no independent associations between overall survival and continuous PVR (p=0.79) or CLDN3 (p=0.56) expression. Robust linear modeling revealed no significant baseline interaction between PVR and CLDN4 regarding the exploratory Cleavage Index (p=0.82). However, de-circularized partial correlation analysis revealed a highly stable, positive co-expression between PVR and CLDN3 (rho=0.2459, p=3.23&#xd7;10-7). Both epithelial markers retained modest inverse correlations with the infiltrating lymphocytic axis (TIGIT and CD96). CONCLUSION: Baseline PVR expression is coordinated with CLDN3 tissue programs independent of general epithelial cellularity but does not interact with the CLDN4 axis or impact overall survival in an unexposed cohort. Because TCGA lacks virome or active microbial exposure tracking, these findings serve as baseline benchmarks for future context-dependent mechanistic studies.

Bacteroides fragilis toxin

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans

Single-cell analysis of the human retina reveals stage-linked microglial states and neural-immune circuit rewiring in diabetic retinopathy.

Diabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we conduct single-cell RNA sequencing of twenty human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We identify two stable microglial populations-homeostatic and inflammatory-that exist along a functional continuum, plus a neutrophil cluster within C1QA+ myeloid cells with dynamic transitions occurring throughout disease progression. Module-level analysis reveals divergent transcriptional trajectories: homeostatic microglia maintain energetic programs while selectively upregulating stress elements, whereas inflammatory microglia layer additional pro-inflammatory programs onto preserved biosynthetic foundations. Eleven co-expression modules organize into two major axes: an inflammatory-stress axis, and a regulatory/metabolic-motility axis, with a stable translation module persisting across disease stages. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.

Humans

Brachyury expression levels predict lineage potential and axis-forming ability of in vitro-derived neuromesodermal progenitors.

Neuromesodermal progenitors (NMPs) produce the spinal cord and musculoskeleton in the elongating anterior-posterior axis. In vivo, NMPs possess dual potency, coinciding with regions co-expressing SOX2 and Brachyury (TBXT). In vitro, SOX2/TBXT co-expressing cells can be produced from pluripotent cells and, like their in vivo counterparts, can produce neural tube and somitic mesoderm. However, the functional characteristics of in vitro SOX2/TBXT co-expressing cells remain unclear, confounding comparisons with in vivo data. To address this, we developed a dual Sox2/Tbxt reporter mouse ESC line. SOX2/TBXT reporter-positive cells emerge in vitro from pluripotent populations with dynamics that mirror their appearance in the embryo. Purified SOX2/TBXT co-expressing populations can differentiate towards neurectoderm or mesoderm, including lateral mesoderm upon BMP stimulation. In gastruloids, quantitative live imaging shows that WNT or NOTCH inhibition rapidly leads to downregulation of TBXT expression and diminished axial extension. We show that clonally plated SOX2/TBXT co-expressing cells are bipotent NMPs that can also self-propagate. By combining clonal analysis with mathematical inference, we identify two thresholds of TBXT and/or SOX2 expression, switching clonal output from neural- to mesoderm-biased, and from mesoderm-biased to mesoderm-specified. Image analysis of embryonic NMPs supports a model whereby SOX2 and TBXT independently influence neuromesodermal differentiation. Thus, this Sox2/Tbxt double reporter cell line highlights unsuspected heterogeneity in NMPs, and together with image analysis of embryonic SOX2/TBXT levels, challenges the assumption that neuromesodermal fate choice is primarily governed by mutual antagonism between SOX2/TBXT.

Animals

Quantum computing-assisted validation of a conserved macrophage suppression module shared by ASFV and PEDV.

BACKGROUND: African swine fever virus (ASFV) and porcine epidemic diarrhea virus (PEDV) differ in viral biology and cellular tropism, yet both pathogens suppress macrophage-mediated immune responses in pigs. OBJECTIVE: To identify a conserved macrophage suppression module shared by ASFV and PEDV and evaluate quantum computing as an independent framework for biological network validation. METHODS: Integrated analysis of publicly available GEO datasets (GSE231435 for ASFV and GSE306895) identified 471 shared downregulated genes. A network- and multi-omics-informed 20-gene core was selected and encoded as a 20-qubit modularity-based Quadratic Unconstrained Binary Optimization (QUBO) problem. Community detection was benchmarked using the Quantum Approximate Optimization Algorithm (QAOA) on both the IBM Quantum Aer simulator and the 156-qubit IBM Fez (Heron r2) quantum processor and compared with brute-force enumeration and simulated annealing. RESULTS: A conserved macrophage suppression module shared by ASFV and PEDV was identified. For the STRING protein-protein interaction network, QAOA at circuit depth p&#x2009;=&#x2009;3 reproduced the brute-force optimum with an approximation ratio of 1.000. In contrast, performance progressively declined in the denser co-expression network with increasing circuit depth, consistent with noise accumulation under current Noisy Intermediate-Scale Quantum (NISQ) conditions. Multi-run consensus analysis identified stable hub genes, including MMP9 and SLA-DOA, as well as genes exhibiting variable community assignments. CONCLUSION: These findings reveal a conserved macrophage suppression module shared between ASFV and PEDV and demonstrate that quantum computing can serve as an independent validation framework for biologically meaningful host-response networks. Network topology emerged as a key determinant of QAOA performance on real NISQ hardware.

Animals

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals

Dynamic and non-additive gene regulation shapes maize responses to simultaneous salt and cold stress.

Salt and cold stresses often occur together in nature and severely impact crop productivity, yet their transcriptional regulation remains poorly understood. Here, we conducted a time-series transcriptomic analysis of maize under salt, cold, and their combination at 0, 6, 12, and 24&#xa0;h. Differential expression analysis revealed dynamic, condition-specific gene responses grouped into eight distinct temporal patterns. Promoter motif analysis of genes within each pattern identified 5-39 significantly enriched motifs, with over 40% lacking known counterparts, suggesting the involvement of previously uncharacterized cis-regulatory elements in stress-responsive transcriptional regulation. By comparing combined stress responses to the sum of single-stress effects, we found that about 74% of DEGs showed non-additive patterns, suggesting that combined stress triggers a distinct transcriptional program. Evolutionary analysis showed that additive DEGs tend to be more recently evolved, subject to weaker purifying selection, and enriched in transposed duplications, contrasting with the stronger constraint observed in non-additive DEGs. WGCNA identified 24 co-expression modules, among which 65 hub DEGs were detected in modules significantly correlated with specific stress conditions. Furthermore, we reconstructed 228, 20, and 200 sequential transcription factor cascades spanning 6&#xa0;h, 12&#xa0;h, and 24&#xa0;h under cold, salt, and combined stress, respectively, with no cascade shared across all three conditions. Together, these results reveal that maize responses to combined salt and cold stress are largely non-additive and temporally dynamic, with distinct evolutionary patterns underlying different response types, offering insights and candidate regulators for enhancing crop stress resilience.

Zea mays

Genome-wide identification of the carotenoid cleavage dioxygenase gene family in wheat and analysis of the TaDREB-7A-TaNCED9a regulatory module conferring drought tolerance.

Carotenoid cleavage dioxygenases (CCDs) play critical roles in plant growth, development, and abiotic stress responses, yet their genome-wide identification and drought response mechanisms remain unexplored in wheat. In this study, 34 TaCCD genes were identified in wheat, distributed across 15 chromosomes and phylogenetically classified into five subfamilies. Gene structure analysis indicated that members within each subfamily shared conserved motifs and similar intron-exon arrangements. Cis-regulatory element analysis suggested the potential roles of these genes in stress adaptation, developmental processes, and hormone signaling. Moreover, prediction of tertiary structures and protein-protein interactions revealed unique structural features and potential interacting partners of the TaCCD proteins. In addition, TaNCED9a, a member of the TaCCD family, showed the highest transcript level in wheat roots among all detected TaCCD genes and was significantly induced by drought stress. Subcellular localization assay indicated that TaNCED9a was located in chloroplasts. Downregulation of TaNCED9a expression led to reduced drought resistance in wheat, accompanied by an accumulation of reactive oxygen species and a decrease in endogenous abscisic acid levels. Using yeast one-hybrid, dual-luciferase, and tobacco transient co-expression assays, the upstream regulatory factor TaDREB-7A was identified, which can regulate the expression of TaNCED9a. Additionally, a KASP molecular marker was developed to identify the superior haplotype TaNCED9a-HapI, which exhibited a significantly higher germination rate compared to TaNCED9a-HapII under drought conditions, and was predominant in wheat. These results offer valuable insights into the TaCCD gene family's response mechanisms to drought stress in wheat, simultaneously identifying promising genetic resources for enhancing drought tolerance through molecular breeding.

CCD

Atherosclerotic plaque fibroblasts derive from adventitial and medial Pdgfra-lineage-positive cells and predominantly maintain fibroblast identity.

AIMS: Fibroblasts are mesenchymal cells in the healthy vascular adventitia. In atherosclerosis, single-cell sequencing datasets suggest fibroblasts are abundant in plaques. However, their identity, origin, and fate during plaque progression remain unclear, which we aim to unravel here. APPROACH AND RESULTS: To robustly define fibroblast identity, origin, and fate, we employed meta-analyses of 54 single-cell RNA sequencing libraries, including murine smooth muscle cell (Myh11) and endothelial cell (EC) (Cdh5) lineage reporter mice with and without atherosclerosis; human control and atherosclerotic arteries; and murine adventitia and atherosclerotic plaques processed separately from low-density lipoprotein (LDL) receptor knockout (Ldlr-/-) mice. These meta-analyses showed that murine and human plaque fibroblast identity was robustly defined by Pdgfra, Pi16, Cygb, and Serpinf1 mRNA. Ninety-five percent of plaque fibroblasts do not derive from the Myh11 lineage, while no Cdh5-lineage-positive cells were present in the fibroblast cluster. We identified five murine arterial fibroblast subsets in atherosclerotic murine aorta: progenitor fibroblasts, matrix fibroblasts, inflammatory fibroblasts, an EC-like fibroblast subset, detected in both adventitia and plaques, and Col5a3+ fibroblasts, unique to the adventitia. We next studied fibroblast identity, origin, and fate using pseudotime analysis and Pdgfra-CreERT2/tdTomato lineage reporter mice (Pdgfra Lin+). Healthy Pdgfra Lin+ reporter mice showed predominant adventitial tdTomato expression, and infrequent medial and intimal Pdgfra Lin+ cells co-expressing MYH11 and PECAM1, respectively. The Pdgfra Lin+ plaque area increased with diet duration. Pdgfra Lin+ cells largely maintain fibroblast identity in the plaque, while <10% co-express SMC markers (MYH11, SM22&#x3b1;), or contribute to ACTA2+ cap cells. ECs gaining mesenchymal markers are transcriptionally distinct from Cdh5-lineage-negative fibroblasts gaining EC markers. Plaque-resident EC-like fibroblasts displayed a mesenchymal-to-endothelial transition transcriptome, which was induced in human primary fibroblasts in vitro by starvation, and dampened or reversed by IL1B, TGFB1, TGFB3, and oxidized LDL. Cross-species integration showed that all murine plaque fibroblasts were conserved in human atherosclerosis, with one additional subset partially resembling murine subsets, and three human-specific subsets. Importantly, human fibroblast subsets differentially correlated to human plaque traits, with EC-like fibroblasts correlating to plaque instability. CONCLUSION: Our results indicate that 95% of plaque-residing fibroblasts are Myh11 Lin- Plaque fibroblasts have a dual origin, predominantly adventitial Pdgfra Lin+ progenitor fibroblasts, with a minor contribution from medial Pdgfra Lin+ &#xa0;Myh11+ SMCs. Most plaque fibroblasts maintain fibroblast identity. Murine plaque fibroblast subsets were conserved in human atherosclerosis. EC-like fibroblasts are linked to human plaque instability. Intervening in progenitor-to-specific fibroblast transitions could present a new avenue to promote plaque stability in atherosclerosis.

Atherosclerosis

TMEM176B is co-expressed with TMEM176A and upregulated in peripheral blood monocytes of patients with primary Sj&#xf6;gren's syndrome.

OBJECTIVES: This study aims to determine the role of acid&#x2011;sensitive nonspecific cation channels transmembrane protein 176A (TMEM176A) and TMEM176B in autoimmune diseases, with a focus on primary Sj&#xf6;gren's Syndrome (pSS). METHODS: We examined the expression patterns of TMEM176A and TMEM176B across tissues and cells utilizing bulk RNA-seq and scRNA-seq datasets. Immunophenotyping analysis was performed by flow cytometry to compare CD62L expression between TMEM176B&#x207a; and TMEM176B&#x207b; monocytes. The proportion of TMEM176B+ cells in monocytes was interrogated in both pSS patients and healthy controls. Clinical correlations of TMEM176B with anti&#x2011;SSB antibody and complement C4 levels were also evaluated. RESULTS: TMEM176A and TMEM176B showed conserved co&#x2011;expression and were significantly upregulated in autoimmune diseases. TMEM176B&#x207a; monocytes displayed higher CD62L positivity rate than TMEM176B- monocytes. In pSS patients, the proportion of TMEM176B&#x207a; monocytes was elevated in total monocytes, classical monocytes (cMo) and intermediate monocytes (iMo). The proportion of TMEM176B+ monocytes positively correlated with anti&#x2011;SSB levels, while several TMEM176B-associated monocyte subset markers inversely correlated with C4. CONCLUSION: TMEM176A and TMEM176B are highly correlated. TMEM176B expression in monocytes is linked to pSS and may serve as a novel auxiliary diagnostic biomarker.

Humans

Construction of molecular signatures based on the co-expression network of NECSO-related gene TRPM4 and its prognostic value in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) demonstrates significant prognostic variability that is not entirely accounted for by traditional staging systems. Necrosis by sodium overload (NECSO) is an emerging programmed cell death pathway, but its clinical relevance in HCC remains undefined. Therefore, this study aimed to identify TRPM4-associated core genes, develop and validate a prognostic signature, and investigate its relationship with the tumor immune microenvironment, tumor mutational burden, and single-cell expression patterns in HCC. METHODS: We integrated transcriptomic, clinical, and mutational datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (n=421) and Gene Expression Omnibus (GEO) cohorts (n=115) to identify genes co-expressed with TRPM4-a key NECSO mediator-and those differentially expressed in HCC. A prognostic signature was developed using least absolute shrinkage and selection operator (LASSO)-Cox regression and validated through survival analysis, time-dependent receiver operating characteristic (ROC) curves, and multivariate Cox regression analysis. The immune landscape was characterized using CIBERSORT, somatic mutation data were used to calculate tumor mutational burden (TMB) and assess its correlation with the risk score, and single-cell RNA sequencing (scRNA-seq) resolved cell-type-specific expression patterns. RESULTS: From 294 TRPM4-associated core genes, we identified an 11-gene signature (BRSK1, MMP1, GRIN2D, GP6, MYOM2, N4BP3, CCDC112, TSEN54, MAP3K9, SPP1, B3GNT4) that independently predicted overall survival (OS) (hazard ratio =5.419, P<0.001) with areas under the curve (AUCs) of 0.779, 0.693, and 0.701 at 1, 3, and 5 years. These values were superior or comparable to conventional clinicopathologic variables after direct comparison. High-risk patients exhibited an immunosuppressive microenvironment, characterized by enrichment of M0 macrophage, a higher M2/M1 ratio (P<0.001) and distinct immune checkpoint profiles. When integrated with TMB, the prognostic stratification was further refined: high-TMB/high-risk patients had poorest outcomes (median OS, 15.3 months), while low-TMB/low-risk patients had the most favorable survival (median OS, 68.7 months). Single-cell analysis revealed that MMP1 was induced in cancer-associated fibroblasts (CAFs) and SPP1 was downregulated in macrophages, single-cell risk scores confirmed TAFs and macrophages as the main contributors to the prognostic model. CONCLUSIONS: The TRPM4-centered 11-gene signature provides robust and independent prognostic stratification in HCC by integrating immune, mutational, and single-cell features. This signature serves as a potential tool for prognostic evaluation and may help inform immunotherapeutic strategies for HCC.

Hepatocellular carcinoma (HCC)