Search Results (940)

Soil salinization is a major constraint to global crop productivity, highlighting the need to identify salt tolerance genes and their molecular mechanisms. Here, we integrated mRNA and miRNA profile analyses to investigate the molecular basis of salt tolerance of an elite Brassica napus cultivar S268. Time-course RNA-seq analysis revealed dynamic transcriptional reprogramming under 215 mM NaCl stress, with 212 core genes significantly enriched in organic acid degradation and glyoxylate/dicarboxylate metabolism pathways. Combined with weighted gene co-expression network analysis (WGCNA) and RT-qPCR validation, five candidate genes (WRKY6, WRKY70, NHX1, AVP1, and NAC072) were identified as the regulators of salt tolerance in rapeseed. Haplotype analysis based on association mapping showed that NAC072, ABI5, and NHX1 exhibited two major haplotypes that were significantly associated with salt tolerance variation under salt stress in rapeseed. Integrated miRNA-mRNA analysis and RT-qPCR identified three regulatory miRNA-mRNA pairs (bna-miR160a/BnaA03.BAG1, novel-miR-126/BnaA08.TPS9, and novel-miR-70/BnaA07.AHA1) that might be involved in S268 salt tolerance. These results provide novel insights into the post-transcriptional regulation of salt tolerance in B. napus, offering potential targets for genetic improvement. Full article

Background/Objectives: Different risk factors are involved in the initiation and progression of melanoma. In particular, genetic and epigenetic pathways are involved in all stages of melanoma and are exploited in therapeutic approaches. This study investigated the role of circular RNA circ_0001591 in melanoma cell migration. Methods: Three different melanoma cell lines were transfected with siRNA targeting circ_0001591 and with mimic or inhibitor molecules for miR-20a-3p and miR-34a-5p. Gene and protein expression levels were analyzed by RT-qPCR and Western blot, respectively. Dual luciferase reporter assays were performed to confirm the direct interaction of miR-20a-3p and miR-34a-5p with circ_0001591, as well as with the 3’UTRs of AXL (for both miRNAs) and FOSL1 (miR-34a-5p only). Wound healing assays were conducted to assess cell migration velocity. Results: The silencing of circ_0001591 significantly reduces the migration ability of melanoma cell lines. This downregulation was associated with an increased expression of miR-20a-3p and miR-34a-5p. Dual luciferase reporter assays confirmed the direct binding of both miRNAs to circ_0001591, supporting its role as a molecular sponge. The same assays also verified that miR-20a-3p directly targets the 3’UTR of AXL, while miR-34a-5p binds the 3’UTRs of both AXL and FOSL1. Western blot analysis showed that the modulation of this axis affects the expression levels of the AXL and FRA1 oncoproteins. Conclusions: Our findings demonstrate that circ_0001591 promotes melanoma migration by sponging miR-20a-3p and miR-34a-5p, thereby indirectly modulating the expression of AXL and FRA1 oncoprotein. Further investigations of this new regulatory network are needed to better understand its role in melanoma progression and to support the development of targeted therapies. Full article

Prognostic markers such as overall survival (OS) and tertiary lymphoid structure (TLS) ratios, alongside diagnostic signatures like primary cancer-type classification, provide critical information for treatment selection, risk stratification, and longitudinal care planning across the oncology continuum. However, extracting these signals solely from sparse, high-dimensional multi-omics data remains a major challenge due to heterogeneity and frequent missingness in patient profiles. To address this challenge, we present SeNMo, a self-normalizing deep neural network trained on five heterogeneous omics layers—gene expression, DNA methylation, miRNA abundance, somatic mutations, and protein expression—along with the clinical variables, that learns a unified representation robust to missing modalities. Trained on more than 10,000 patient profiles across 32 tumor types from The Cancer Genome Atlas (TCGA), SeNMo provides a baseline that can be readily fine-tuned for diverse downstream tasks. On a held-out TCGA test set, the model achieved a concordance index of 0.758 for OS prediction, while external evaluation yielded 0.73 on the CPTAC lung squamous cell carcinoma cohort and 0.66 on an independent 108-patient Moffitt Cancer Center cohort. Furthermore, on Moffitt’s cohort, baseline SeNMo fine-tuned for TLS ratio prediction aligned with expert annotations (p < 0.05) and sharply separated high- versus low-TLS groups, reflecting distinct survival outcomes. Without altering the backbone, a single linear head classified primary cancer type with 99.8% accuracy across the 33 classes. By unifying diagnostic and prognostic predictions in a modality-robust architecture, SeNMo demonstrated strong performance across multiple clinically relevant tasks, including survival estimation, cancer classification, and TLS ratio prediction, highlighting its translational potential for multi-omics oncology applications. Full article

Nuclear receptors (NRs) are ligand-activated transcription factors that regulate gene expression and are involved in diverse physiological and pathological processes, including carcinogenesis. In bladder cancer (BCa), dysregulation of NR signaling pathways has been linked to tumor initiation, progression, therapy resistance, and immune evasion. Recent evidence highlights the intricate crosstalk between NRs and microRNAs (miRNAs), which are small non-coding RNAs that posttranscriptionally modulate gene expression. This review provides an integrated overview of the molecular interactions between key NRs and miRNAs in BCa. We investigated how miRNAs regulate NR expression and function and, conversely, how NRs influence miRNA biogenesis, thereby forming regulatory feedback loops that shape tumor behavior. Specific miRNA–NR interactions affecting epithelial-to-mesenchymal transition, metabolic reprogramming, angiogenesis, and chemoresistance are discussed in detail. Additionally, we highlight therapeutic strategies targeting NR–miRNA networks, including selective NR modulators, miRNA mimics and inhibitors, as well as RNA-based combinatorial approaches focusing on their utility as diagnostic biomarkers and personalized treatment targets. Understanding the molecular complexity of NR–miRNA regulation in BCa may open new avenues for improving therapeutic outcomes and advancing precision oncology in urological cancers. Full article

Background: Preeclampsia (PE) is a pregnancy-specific disease and hypertensive disorder with a multifactorial pathogenesis involving complex molecular regulatory networks. Recent studies highlight the critical role of non-coding RNAs, particularly miRNAs and lncRNAs, in PE development. This study investigates the molecular interaction between miR-7151-5p and the lncRNA KCNQ1OT1 and their functional contributions to PE pathogenesis. Methods: An integrative approach combining RNAhybrid-based bioinformatics, dual-luciferase reporter assays, qRT-PCR, Transwell migration and invasion assays, and RNA sequencing was employed to characterize the binding between miR-7151-5p and KCNQ1OT1 and assess their influence on trophoblast cell function and gene expression. Results: A bioinformatic analysis predicted a stable binding site between miR-7151-5p and KCNQ1OT1 (minimum free energy: –37.3 kcal/mol). The dual-luciferase reporter assay demonstrated that miR-7151-5p directly targets KCNQ1OT1, leading to suppressed transcriptional activity. In HTR8/SVneo cells, miR-7151-5p overexpression significantly downregulated both KCNQ1OT1 and Notch1 mRNA, whereas its inhibition showed no significant changes, suggesting additional regulatory mechanisms of Notch1 expression. Transwell assays indicated that miR-7151-5p overexpression suppressed trophoblast cell migration and invasion, whereas its inhibition enhanced these cellular behaviors. RNA-seq analysis further revealed that miR-7151-5p overexpression altered key signaling pathways, notably the TGF-β pathway, and significantly modulates PE-associated genes, including PLAC1, ANGPTL6, HIRA, GLA, HSF1, and BAG6. Conclusions: The regulatory effect of miR-7151-5p on KCNQ1OT1, along with its influence on trophoblast cell dynamics via Notch1 and TGF-β signaling pathways, highlights its role in PE pathogenesis and supports its potential as a biomarker in early PE screening. Full article

Background: Neurodevelopmental disorders, including autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), are increasingly recognized as conditions arising from multifaceted interactions among genetic predisposition, environmental exposures, and epigenetic modifications. Among epigenetic mechanisms, non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and PIWI-interacting RNAs (piRNAs), have gained attention as pivotal regulators of gene expression during neurodevelopment. These RNA species do not encode proteins but modulate gene expression at transcriptional and post-transcriptional levels, thereby influencing neuronal differentiation, synaptogenesis, and plasticity. Objectives: This systematic review critically examines and synthesizes the most recent findings, particularly in the post-COVID transcriptomic research era, regarding the role of ncRNAs in the pathogenesis, diagnosis, and potential treatment of neurodevelopmental disorders. Methods: A comprehensive literature search was conducted to identify studies reporting on the expression profiles, functional implications, and clinical relevance of ncRNAs in neurodevelopmental disorders, across both human and animal models. Results: Here, we highlight that multiple classes of ncRNAs are differentially expressed in individuals with ASD and ADHD. Notably, specific miRNAs and lncRNAs demonstrate potential as diagnostic biomarkers with high sensitivity and specificity. Functional studies further reveal that ncRNAs actively contribute to pathogenic mechanisms by modulating neuronal gene networks. Conclusions: Emerging experimental data indicate that the exogenous administration of certain ncRNAs may reverse molecular and behavioral phenotypes, supporting their therapeutic promise. These findings broaden our understanding of neurodevelopmental regulation and open new avenues for personalized diagnostics and targeted interventions in clinical neuropsychiatry. Full article

Circular RNAs (circRNAs) are covalently closed RNA molecules generated through a non-canonical splicing event known as back-splicing. This particular class of non-coding RNAs has attracted growing interest due to its evolutionary conservation across eukaryotes, high expression in the central nervous system, and frequent dysregulation in various pathological conditions, including cancer. Traditionally, circRNAs have been characterised by their ability to function as microRNA (miRNA) and protein sponges. However, recent discoveries from multiple research groups have uncovered a novel and potentially transformative mechanism of action: the direct interaction of circRNAs with messenger RNAs (mRNAs) to regulate their fate. These interactions can influence mRNA stability and translation, revealing a new layer of post-transcriptional gene regulation. In this review, we present and analyse the latest evidence supporting the emerging role of circRNAs in diverse biological contexts. We highlight the growing body of research demonstrating circRNA-mRNA interactions as a functional regulatory mechanism and explore their involvement in key physiological and pathophysiological processes. Understanding this novel mechanism expands our knowledge of RNA-based regulation and opens new opportunities for therapeutic strategies targeting circRNA-mRNA networks in human disease. Full article

Herpesviruses are DNA viruses that evade the immune response and persist as lifelong infections. Human gamma-herpesviruses Epstein–Barr virus (EBV) and Kaposi’s sarcoma herpesvirus (KSHV) are oncogenic; they can lead to cancer. Oncogenic viruses are responsible for 10–15% of human cancer development, which can have poor prognoses. Non-coding RNAs (ncRNAs) are RNAs that regulate gene expression without encoding proteins, and are being studied for their roles in viral immune evasion, infection, and oncogenesis. ncRNAs are classified by their size, and include long non-coding RNAs, microRNAs, and circular RNAs. EBV and KSHV manipulate host ncRNAs, and encode their own ncRNAs, regulating host processes and immune responses. Viral ncRNAs regulate host functions by post-transcriptionally modifying host RNAs, and by serving as mimics of other host RNAs, promoting immune evasion. ncRNAs in gamma-herpesvirus infection are also important for tumorigenesis, as dampening immune responses via ncRNAs can upregulate pro-tumorigenic pathways. Emerging topics such as RNA modifications, target-directed miRNA degradation, competing endogenous RNA networks, and lncRNA/circRNA–miRNA interactions provide new insights into ncRNA functions. This review compares ncRNAs and the mechanisms of viral immune evasion in EBV and KSHV, while also expanding on recent developments in the roles of ncRNAs in immune evasion, viral infection, and oncogenesis. Full article

Background: Dendritic cells (DCs) play an important role as a bridge between innate and adaptive immunity, and changes in gene expression of DCs during the immune response to Mycobacterium tuberculosis (M.tb) may affect the development of tuberculosis. Methods: Using systems biology methods, mRNA and miRNA expression profile data of DCs infected with M.tb were obtained. A total of 1398 differentially expressed mRNAs and 79 differentially expressed miRNAs were identified, and a corresponding miRNA–mRNA regulatory network was constructed using Cytoscape 3.9.1 software. The functional annotations and pathway classifications of the miRNA–mRNA network were identified using the DAVID tool. Then, the key pathway modules in the miRNA–mRNA network were screened and subjected to PPI network analysis to identify hub nodes. Subsequently the miRNA/mRNA axis was determined, validated by qRT-PCR, and evaluated through ROC curve analysis. Results: The TNF signaling pathway and the Tuberculosis pathway were key pathway modules, with miR-34a-3p/TNF and miR-190a-3p/IL1B being the greatest correlations with the two pathway modules. qRT-PCR results showed that IL1B and miR-190a-3p exhibited significant differences in both the H37Ra and BCG infection groups. The AUC of two factors (IL1B and miR-190a-3p) was 0.9561 and 0.9625, respectively, showing high sensitivity and specificity. Conclusions: Consequently, miR-190a-3p/IL1B might be a good candidate marker to characterize the immune response of DCs to M.tb and a transition signal from innate to adaptive immunity. Full article

Lead (Pb) exposure poses a significant public health concern due to its neurotoxic effects. While mitochondrial dysfunction is implicated in lead neurotoxicity, the precise molecular mechanisms, particularly the role of non-coding RNA-mediated competing endogenous RNA networks, remain underexplored. SH-SY5Y neuroblastoma cells were treated with 10 μM lead acetate. Cell viability was assessed by Cell Counting Kit-8 (CCK-8). Mitochondrial ultrastructure and quantity were analyzed via transmission electron microscopy (TEM). Key mitochondrial dynamics proteins were examined by Western blot. Comprehensive transcriptome sequencing, including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs) and mRNAs, was performed followed by functional enrichment and ceRNA network construction. Selected RNAs and hub genes were validated using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Lead exposure significantly reduced SH-SY5Y cell viability and induced mitochondrial damage (decreased quantity, swelling, fragmentation). Western blot confirmed an imbalance in mitochondrial dynamics, as indicated by decreased mitofusin 2 (MFN2), increased total and phosphorylated dynamin-related protein 1 (DRP1). Transcriptomic analysis revealed widespread differential expression of lncRNAs, circRNAs, miRNAs, and mRNAs. Enrichment analysis highlighted mitochondrial function and oxidative stress pathways. A ceRNA network identified five key hub genes: SLC7A11, FOS, HMOX1, HGF, and NR4A1. All validated RNA and hub gene expression patterns were consistent with sequencing results. Our study demonstrates that lead exposure significantly impairs mitochondrial quantity and morphology in SH-SY5Y cells, likely via disrupted mitochondrial dynamics. We reveal the potential regulatory mechanisms of lead-induced neurotoxicity involving ceRNA networks, identifying hub genes crucial for cellular stress response. This research provides a foundational framework for developing therapeutic strategies against lead-induced neurotoxicity. Full article

Background and Objectives: VPS26A, a core component of the retromer complex, is pivotal to endosomal trafficking and membrane protein recycling. However, its expression profile, prognostic significance, and clinical relevance in liver hepatocellular carcinoma (LIHC) remain unexplored. This study investigates the prognostic potential of VPS26A by extensively analyzing publicly available LIHC-related databases. Materials and Methods: Multiple databases, including TIMER, UALCAN, HPA, GSCA, KM Plotter, OSlihc, MethSurv, miRNet, OncomiR, LinkedOmics, GeneMANIA, and STRING, were used to evaluate VPS26A expression patterns, prognostic implications, correlations with tumor-infiltrating immune cells (TIICs), epigenetic modifications, drug sensitivity, co-expression networks, and protein–protein interactions in LIHC. Results: VPS26A was significantly overexpressed at both the mRNA and protein levels in LIHC tissues compared to that in normal tissues. This upregulation was strongly associated with a poor prognosis. Furthermore, VPS26A expression was both positively and negatively correlated with various TIICs. Epigenetic analysis indicated that VPS26A is regulated by promoter and regional DNA methylation. Additionally, VPS26A influences the sensitivity of LIHC cells to a broad range of anticancer agents. Functional enrichment and co-expression analyses revealed that VPS26A serves as a central regulator of the LIHC transcriptomic landscape, with positively correlated gene sets linked to poor prognosis. Additionally, VPS26A contributes to the molecular architecture governing vesicular trafficking, with potential relevance to diseases involving defects in endosomal transport and autophagy. Notably, miRNAs targeting VPS26A-associated gene networks have emerged as potential prognostic biomarkers for LIHC. VPS26A was found to be integrated into a highly interconnected signaling network comprising proteins in cancer progression, immune regulation, and cellular metabolism. Conclusions: Overall, VPS26A may serve as a potential prognostic biomarker and therapeutic target in LIHC. This study provides novel insights into the molecular mechanisms underlying LIHC progression, and highlights the multifaceted role of VPS26A in tumor biology. Full article

Kazakh mares have drawn significant attention for their outstanding lactation traits. Lactation, a complex physiological activity, is modulated by multiple factors. This study utilized high-throughput sequencing to conduct whole-transcriptome sequencing analysis on the mammary gland tissue of eight Kazakh mares, of which four were pregnant and four were non-pregnant, to systematically reveal the molecular regulatory mechanisms. The results showed differential expression in 2136 mRNAs, 180 lncRNAs, 104 miRNAs, and 1162 circRNAs. Gene ontology functional annotation indicates that these differentially expressed genes are involved in multiple key biological processes, such as the cellular process (BP), metabolic process, and biological regulation. Kyoto Encyclopedia of Genes and Genomes analysis suggests that the differentially expressed genes are significantly enriched in essential pathways such as cytokine–cytokine receptor interaction, the chemokine signaling pathway, and the PI3K-Akt signaling pathway. Additionally, this study constructed a competing endogenous RNA (ceRNA) regulatory network based on the differentially expressed genes (|log₂FC| > 1, FDR < 0.05), offering a novel perspective for revealing the functional regulation of the mammary gland. This study compared genomic differences in mammary gland tissue of pregnant and non-pregnant Kazakh mares and identified candidate genes that are closely related to lactation regulation. It found that various genes, such as PIK3CG, IL7R, and SOD2, play central regulatory roles in activating mammary gland functions. These findings provide theoretical support for explaining the molecular mechanisms underlying the mammary gland development of Kazakh mares. Full article

Background: Diabetic foot ulcers (DFUs) are a severe complication of diabetes and are characterized by impaired wound healing and a high amputation risk. Exosomes—which are nanovesicles carrying proteins, RNAs, and lipids—mediate intercellular communication in wound microenvironments, yet their biomarker potential in DFUs remains underexplored. Methods: We analyzed transcriptomic data from GSE134431 (13 DFU vs. 8 controls) as a training set and validated findings in GSE80178 (6 DFU vs. 3 controls). A sum of 7901 differentially expressed genes (DEGs) of DFUs were detected and intersected with 125 literature-curated exosome-related genes (ERGs) to yield 51 candidates. This was followed by GO/KEGG analyses and a PPI network construction. Support vector machine–recursive feature elimination (SVM-RFE) and the Boruta random forest algorithm distilled five biomarkers (DIS3L, EXOSC7, SDC1, STX11, SYT17). Expression trends were confirmed in both datasets. Analyses included nomogram construction, functional and correlation analyses, immune infiltration, GSEA, gene co-expression and regulatory network construction, drug prediction, molecular docking, and RT-qPCR validation in clinical samples. Results: A nomogram combining these markers achieved an acceptable calibration (Hosmer–Lemeshow p = 0.0718, MAE = 0.044). Immune cell infiltration (CIBERSORT) revealed associations between biomarker levels and NK cell and neutrophil subsets. Gene set enrichment analysis (GSEA) implicated IL-17 signaling, proteasome function, and microbial infection pathways. A GeneMANIA network highlighted RNA processing and vesicle trafficking. Transcription factor and miRNA predictions uncovered regulatory circuits, and DGIdb-driven drug repurposing followed by molecular docking identified Indatuximab ravtansine and heparin as high-affinity SDC1 binders. Finally, RT-qPCR validation in clinical DFU tissues (n = 5) recapitulated the bioinformatic expression patterns. Conclusions: We present five exosome-associated genes as novel DFU biomarkers with diagnostic potential and mechanistic links to immune modulation and vesicular transport. These findings lay the groundwork for exosome-based diagnostics and therapeutic targeting in DFU management. Full article

The selection of appropriate biomarkers in clinical practice aids in the early detection, treatment, and prevention of disease while also assisting in the development of targeted therapeutics. Recently, multi-omics data generated from advanced technology platforms has become available for disease studies. Therefore, the integration of this data with associated clinical data provides a unique opportunity to gain a deeper understanding of disease. However, the effective integration of large-scale multi-omics data remains a major challenge. To address this, we propose a novel deep learning model—the Multi-Omics Graph Attention biomarker Discovery network (MOGAD). MOGAD aims to efficiently classify diseases and discover biomarkers by integrating various omics data such as DNA methylation, gene expression, and miRNA expression. The model consists of three main modules: Multi-head GAT network (MGAT), Multi-Graph Attention Fusion (MGAF), and Attention Fusion (AF), which work together to dynamically model the complex relationships among different omics layers. We incorporate clinical data (e.g., APOE genotype) which enables a systematic investigation of the influence of non-omics factors on disease classification. The experimental results demonstrate that MOGAD achieves a superior performance compared to existing single-omics and multi-omics integration methods in classification tasks for Alzheimer’s disease (AD). In the comparative experiment on the ROSMAP dataset, our model achieved the highest ACC (0.773), F1-score (0.787), and MCC (0.551). The biomarkers identified by MOGAD show strong associations with the underlying pathogenesis of AD. We also apply a Hi-C dataset to validate the biological rationality of the identified biomarkers. Furthermore, the incorporation of clinical data enhances the model’s robustness and uncovers synergistic interactions between omics and non-omics features. Thus, our deep learning model is able to successfully integrate multi-omics data to efficiently classify disease and discover novel biomarkers. Full article

Recent findings have identified high-density lipoprotein (HDL) as a carrier of microRNAs, small non-coding RNAs that regulate gene expression, suggesting a potential novel functional and biochemical role for HDL-microRNA cargo. Here, we conduct an in-depth bioinformatics analysis of unique HDL-microRNA cargo to uncover their molecular mechanisms and potential applications as clinical biomarkers. First, using the Gene Expression Omnibus (GEO), we performed computational analysis on public human microRNA array datasets (GSE 25425; platform GPL11162) obtained from highly purified fractions of HDL in human plasma in order to identify their unique miRNA cargo. This led to the identification of eleven miRNAs present only in HDL, herein listed: hsa-miR-210, hsa-miR-26a-1, hsa-miR-628-3p, hsa-miR-31, hsa-miR-501-5p, hsa-miR-100-3p, hsa-miR-571, hsa-miR-100-5p, hsa-miR-23a, hsa-miR-550, and hsa-miR-432. Then, these unique miRNAs present in HDL were analyzed using a bioinformatics approach to recognize their validated target genes. The ClusterProfiler R package applied gene ontology and KEGG enrichment analysis. The key genes mainly enriched in the biological process of cellular regulation were identified and linked to neurodegeneration. Finally, the protein–protein interaction and co-expression network were analyzed using the STRING and GeneMANIA Cytoscape plugins. Full article