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PubMed2025

Measuring FOXO Activity by Using qPCR-Based Expression Analysis of FOXO Target Genes.

FOXO transcription factors belong to the forkhead protein family and are distinguished by their unique forkhead (FKH) DNA-binding domain. In the realm of mammals, four FOXO paralogs are recognized: FOXO1, FOXO3, FOXO4, and FOXO6. These paralogs are evolutionary counterparts of the daf-16 gene discovered in the nematode C. elegans. A key feature shared by these paralogs is a consensus binding site known as the DAF-16 family protein-binding site (DBE: 5'-TTGTTTAC-3'). The functional outcome of FOXO transcription factors primarily hinges on their affinity for these specific binding sites within the promoters of their target genes. Nevertheless, it is worth noting that many of these target genes exhibit tissue-specific expression patterns. Consequently, there is not a single FOXO target gene whose expression can reliably serve as a universal indicator of FOXO activity across all cell types and tissues or in response to all stimuli. In light of these considerations, we present a collection of target genes that, when collectively assessed, can accurately gauge FOXO activation. In this chapter, we outline a specific protocol for utilizing quantitative reverse transcription polymerase chain reaction (qRT-PCR) to measure the expression levels of these genes.

Forkhead Transcription Factors↗

PubMed2026

Optimized Hot Phenol-Based RNA Extraction from Mycobacteria: A Robust Approach for Reliable Gene Expression Analysis.

Mycobacterium tuberculosis (Mtb) remains a major global health threat, underscoring the need for reliable transcriptomic studies to understand its biology and drug resistance mechanisms. Such analyses depend on obtaining high-quality, high-yield RNA. Although several RNA extraction methods are available, many require expensive reagents, large culture volumes, or specialized equipment, limiting their suitability for large-scale studies, particularly in resource-constrained settings. Here, an optimized Hot Phenol based RNA extraction method specifically tailored for mycobacteria is presented. The method uses minimal culture volume and commonly available reagents to consistently yield high-quality RNA suitable for high-throughput transcriptomic applications. RNA quantity and integrity were assessed by gel electrophoresis and RNA integrity analysis (RIN), and its suitability for downstream applications was confirmed by qPCR and Qubit 4. To benchmark the performance of the optimized method, a parallel RNA extraction using TRIzol and RNeasy under identical experimental conditions was carried out, including the same Mycobacterium species, culture volume, growth phase (logarithmic and stationary), and lysis conditions. This allowed a direct comparison of yield, quality, feasibility, and cost. The optimized Hot Phenol method demonstrated comparable or improved RNA yield and quality while significantly reducing reagent cost and dependence on specialized equipment. Owing to its efficiency, reproducibility, and affordability, this protocol provides a practical alternative for large-scale gene expression and transcriptomic studies in Mtb and other mycobacterial species.

RNA, Bacterial↗

PubMed2026

Biogenic Silver Nanoparticles from the Cell-Free Supernatant of Mychonastes sp. B1: Antibacterial and Antibiofilm Effects, and Wound Healing Activity Supported by Gene and Protein Expression Analysis.

The biogenic synthesis of silver nanoparticles (AgNPs) using microalgae provides a sustainable alternative to conventional physicochemical methods. In this study, AgNPs were synthesized from the cell-free supernatant of the freshwater microalga Mychonastes sp. B1 and characterized by ultraviolet-visible spectroscopy (UV-Vis), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR), and field-emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FE-SEM/EDS). The nanoparticles were predominantly spherical (15-55 nm), highly stable (ζ =  - 42.8 mV), and appeared to be capped by extracellular polymeric substances. The biogenic AgNPs (GS-AgNPs) exhibited potent antibacterial activity, with minimum inhibitory concentrations (MICs) of 2.0 µg/mL against Staphylococcus aureus and 2.5 µg/mL against Pseudomonas aeruginosa, and significantly (p < 0.05) inhibited biofilm formation. Fibroblast viability remained at or above 80% at AgNP concentrations up to 1.5 µg/mL, which promoted cell migration and increased wound closure by 8.1% at 24 h (p < 0.05). Exposure to 1.5 µg/mL AgNPs significantly upregulated extracellular matrix markers (Col1a1 2.3-fold, Fn1 3.3-fold at mRNA level; COL1A1 2.1-fold, FN1 2.7-fold at the protein level). These findings indicate that GS-AgNPs possess antimicrobial and wound healing properties, highlighting their potential as biocompatible nanomaterials for biomedical applications.

Silver↗

PubMed2026

Identification of ultrasound-associated gene candidates in myeloid cells and construction of a prognostic risk model for acute myeloid leukemia.

BACKGROUND: Incorporating ultrasound (US) treatment sensitivity analysis may improve the treatment of acute myeloid leukemia (AML). METHODS: This study integrated single-cell and bulk datasets for analysis. Differential expression analysis between US-treated and control samples was performed using limma package. The AUCell package was used to calculate US-associated scores in the single-cell dataset. Differentially expressed genes (DEGs) between the specific groups were identified, followed by intersection analysis with previously identified DEGs. Univariate regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis (using the glmnet package), and stepwise multivariate regression (using the MASS package) were used to refine the candidate genes and to construct a risk model. The model genes were validated using in vitro experiments. Enrichment analysis was conducted using gene set enrichment analysis (GSEA), and immune infiltration was evaluate by single-sample GSEA (ssGSEA) and ESTIMATE algorithms. The correlations between RiskScores and drug sensitivity were analyzed by oncoPredict package. Finally, tumor mutational burden (TMB) and genomic mutations were compared between the risk groups. RESULTS: Nine prognostic signatures (SPINK2, HNRNPAB, SH3BGRL3, CLEC11A, ITGA4, RPL39L, MX1, HEXIM1, and MAP4K4) were identified. Particularly, low expression of SPINK2 attenuated the activity and invasion of AML cells. High-risk group had higher immune cell infiltration. Eight drugs were predicted to be correlated with the RiskScore model. DNMT3A and RUNX1 showed higher mutation frequencies in the high-risk group, whereas KIT and MUC16 showed higher mutation frequencies in the low-risk group. CONCLUSION: The RiskScore model established in this study provides a theoretical basis for clinically screening responsive populations and optimizing treatment strategies.

Humans↗

PubMed2026

Transcriptomic responses to developmental temperature in two field-collected Spodoptera exigua populations from Korea.

The beet armyworm, Spodoptera exigua, is a polyphagous insect whose development and seasonal occurrence are strongly influenced by temperature. However, transcriptomic responses to developmental thermal regimes remain insufficiently characterized in field-collected populations. In this study, we compared two Korean field-collected populations of S. exigua: a Haenam population collected in May and initially maintained at 15 ± 1 °C (HN), and a Jeju population collected in July and initially maintained at 27 ± 1 °C (JJ). F1 larvae from each population were reared under three fluctuating developmental temperature regimes: low (15-21 °C), middle (21-27 °C), and high (27-33 °C), followed by RNA-seq analysis. Differential expression analysis revealed population-associated variation in transcriptomic responses across developmental temperatures. HN exhibited a larger number of differentially expressed genes under the high-temperature regime, suggesting stronger transcriptomic sensitivity to elevated developmental temperature. Functional enrichment analyses identified population-associated differences in pathways related to heat response, oxidative metabolism, cytoskeletal organization, cuticle-associated processes, lipid metabolism, and immune-related functions. In JJ, heat-response and cuticle-related expression patterns were more prominent under warmer developmental conditions, whereas HN showed broader changes in stress- and metabolism-associated pathways under high temperature. Overall, this study provides a comparative transcriptomic analysis of two field-collected S. exigua populations under different developmental temperature regimes and identifies RNA-seq-based molecular response patterns associated with population-specific thermal response profiles.

Animals↗

PubMed2025

Genome-wide identification, characterization, and expression pattern analysis of the glyoxalase gene family in Phyllostachys pubescens during abiotic stresses.

BACKGROUND: The glyoxalase pathway comprising of three enzymes i.e., glyoxalase I (GLYI), glyoxalase II (GLYII), and glyoxalase III (GLYIII), which play vital role in mitigating abiotic stresses by detoxifying the stress induced cytotoxic metabolite methylglyoxal (MG). Phyllostachys pubescens an ecologically and economically important forest species, plays vital roles in carbon sequestration and climate change mitigation. A genome-wide study was conducted to identify and characterize GLYI, GLYII, and unique DJ-1/GLYIII gene candidates in P. pubescens. The identified members were evaluated based on phylogenetic analysis, gene structure, chromosomal distribution, gene duplication, presence of conserved domain(s) and cis regulatory region. RESULTS: A total of 19 GLYI, 18 GLYII, and 15 GLYIII members were identified, each featuring characteristic domains: glyoxalase, metallo-β-lactamase, and DJ-1/PfpI, respectively. The presence of different cis-elements in the promoter region of the glyoxalase genes gives insights into their role and regulation under hormonal response, developmental processes and stress adaptation. Besides this, stress responsive transcription factors binding sites also dominated the promoter regions of glyoxalase genes. Expression analysis of various glyoxalase genes demonstrated significant variability under different stress conditions, underscoring their potential roles in stress modulation. Significant upregulation of all of the PhGLYI, PhGLYII, and PhGLYIII were observed under cold, drought, heavy metal and salinity stress suggesting their involvement in oxidative stress management, osmotic regulation and remodelling cellular redox homeostasis. Among the glyoxalase genes, PhGLYI-15, PhGLYII-9, and PhGLYIII-3 showed consistent upregulation under various abiotic stresses. CONCLUSIONS: Our findings reveal that glyoxalase genes crucially contribute towards the improvement of cellular osmotic potential in moso bamboo under different abiotic stresses. This study enhances our understanding of glyoxalase genes' evolution and functional roles in plants and opens new avenues for developing stress resilient crop varieties for sustainable agriculture.

Lactoylglutathione Lyase↗

PubMed2025

Exploring prognostic genes in the immune microenvironment of acute myeloid leukemia via weighted gene co-expression network analysis.

BACKGROUND: Acute myeloid leukemia (AML) is a heterogeneous blood cancer that arises from transformed myeloid precursor cells in a compromised bone marrow microenvironment. This environment is essential for AML initiation, progression, and relapse. Alongside oncogenic changes in hematopoietic cells, immunological dysregulation also contributes to leukemogenesis. The present study is aimed to identify prognostic genes in stromal and immune cells associated with AML using the weighted gene co-expression network analysis (WGCNA). METHODS: Gene expression profiles were retrieved from The Cancer Genome Atlas database, and immune and stromal cell scores were calculated using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) method. These scores helped identify differentially expressed genes (DEGs), which were then used to create gene clusters through WGCNA. To explore the functions of genes linked to AML subtypes, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. A protein-protein interaction network was developed to identify hub genes. The top 18 hub genes were identified using the cytoHubba plug-in in Cytoscape software, and survival analysis was conducted with the Gene Expression Profiling Interactive Analysis 2 online tool. RESULTS: A total of 1097 DEGs were identified, with 601 being upregulated and 496 downregulated. WGCNA analysis indicated that the gray module, comprising 165 genes, had the strongest association with AML subtypes (Cor > 0.3; P < .05). Gene Ontology enrichment analysis demonstrated that the 18 identified hub genes were predominantly associated with neutrophil activation, immune response, secretory granule membrane, and pattern recognition receptor activity. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the DEGs were mainly involved in pathways related to phagosome, lysosome, tuberculosis, leishmaniasis, and neutrophil extracellular trap formation. Kaplan-Meier survival analysis of the top 18 hub genes indicated that ITGAM, IL10, and CD163 were significantly correlated with survival outcomes in AML. CONCLUSION: Key stromal and immune-related genes influencing AML patient outcomes were identified, highlighting their potential as therapeutic targets. These discoveries provide deeper insights into the molecular mechanisms driving AML pathogenesis and subtype differentiation.

Leukemia, Myeloid, Acute↗

PubMed2024

Differential expression and regulation of ADAD1, DMRTC2, PRSS54, SYCE1, SYCP1, TEX101, TEX48, and TMPRSS12 gene profiles in colon cancer tissues and their in vitro response to epigenetic drugs.

Colon cancer (CC) is a significant cause of death worldwide, particularly in Saudi Arabia. To increase the accuracy of diagnosis and treatment, it is important to discover new specific biomarkers for CC. The main objectives of this research are to identify potential specific biomarkers for the early diagnosis of CC by analyzing the expressions of eight cancer testis (CT) genes, as well as to analyze how epigenetic mechanisms control the expression of these genes in CC cell lines. Tissue samples were collected from 15 male patients with CC tissues and matched NC tissues for gene expression analysis. The expression levels of specific CT genes, including ADAD1, DMRTC2, PRSS54, SYCE1, SYCP1, TEX101, TEX48, and TMPRSS12, were assessed using quantitative techniques. To validate the gene expression patterns, we used publicly available CC statistics. To investigate the effect of inhibition of DNA methylation and histone deacetylation on CT gene expression, in vitro experiments were performed using HCT116 and Caco-2 cell lines. There was no detected expression of the genes neither in the patient samples nor in NC tissues, except for TEX48, which exhibited upregulation in CC samples compared to NC tissues in online datasets. Notably, CT genes showed expression in testis samples. In vitro, experiments demonstrated significant enhancement in mRNA expression levels of ADAD1, DMRTC2, PRSS54, SYCE1, SYCP1, TEX101, TEX48, and TMPRSS12 following treatment with 5-aza-2'-deoxycytidine and trichostatin A in HCT116 and Caco-2 cell lines. Epigenetic treatments modify the expression of CT genes, indicating that these genes can potentially be used as biomarkers for CC. The importance of conducting further research to understand and target epigenetic mechanisms to improve CC treatment cannot be overemphasized.

Humans↗

PubMed1978

X-linked and autosomal genes controlling mouse alpha-galactosidase expression.

Analysis of F2 and backcross animals has confirmed the X-chromosome linkage of Ags, the structural locus for mouse alpha-galactosidase. The position of Ags has been located in the X chromosome, 9 centimorgans from Mo, and the gene order is centromere-Hq-Bn-Ta-Mo-Ags. A variation in the developmental expression of alpha-galactosidase activity, inherited as an autosomal trait, has been characterized using recombinant inbred lines of mice. Among certain recombinant inbred lines, the variation appears to segregate as a single major locus.

Animals↗

PubMed2026

Analysis of genetic polymorphisms and mRNA expression of DRD3 and HTR2A in bruxism.

BACKGROUND: Bruxism, characterized by the involuntary grinding or clenching of teeth, is influenced by genetic, psychological, and environmental factors. This study aimed to evaluate the role of DRD3 (rs6280) and HTR2A (rs6313) polymorphisms in bruxism and to investigate the expression of these genes to better understand their biological significance. METHODS: This case-control study included 82 bruxism patients and 87 controls. Diagnosis was based on clinical examination and non-instrumental criteria from the 2018 international consensus. Genotyping of HTR2A rs6313 and DRD3 rs6280 was performed using PCR-RFLP, and gene expression in peripheral blood was assessed by qPCR. Statistical analyses included chi-square tests, logistic regression, and mRNA expression analysis using the ΔΔCt method. RESULTS: A significant association was identified between bruxism and the rs6313 polymorphism of the HTR2A gene (p = 0.004; OR = 1.89 [1.23-2.92]), with the C allele associated with increased risk. Moreover, HTR2A mRNA expression was upregulated in individuals with bruxism. While no significant differences were observed in DRD3 rs6280 genotype distribution between cases and controls, the presence of the C allele appeared to increase susceptibility to sleep bruxism. In addition, DRD3 mRNA expression was downregulated in bruxism patients. CONCLUSIONS: These findings highlight a significant association between bruxism and the rs6313 polymorphism of the HTR2A gene. Furthermore, increased HTR2A and decreased DRD3 expression support the involvement of serotonin and dopamine pathways in bruxism etiology, underscoring its multifactorial and complex nature. CLINICAL SIGNIFICANCE: This study elucidates the genetic basis of bruxism, indicating a potential role of serotonin and dopamine signaling in its pathogenesis. Understanding genetic predisposition could aid in early detection, risk assessment, and targeted treatment development. TRIAL REGISTRATION: Clinicaltrials.gov ; trial registration number: NCT06457646 (13/06/2024).

Adult↗

PubMed2026

Genome-wide identification, characterization, evolutionary analysis, and expression profiling of the FCS-like zinc finger (FLZ) gene family in soybean (Glycine max L.) under abiotic stresses.

Drought and salinity limit soybean yield. Despite their role in the SnRK1 energy-sensing complex, a systematic study of FCS-Like Zinc Finger (FLZ) proteins in soybean has not been reported. We performed a genome-wide identification of the GmFLZ gene family, identifying 40 members distributed across 18 of the 20 soybean chromosomes. Phylogenetic analysis of 87 FLZ proteins from Glycine max, Arabidopsis thaliana, and Oryza sativa revealed four major evolutionary clades, suggesting that diversification predates the separation of monocots and dicots. Structural analysis identified ten conserved motifs, with Motifs 1 and 2 present in all family members. Gene duplication analysis identified 304 paralogous pairs, most arising from segmental duplication. Ka/Ks analysis indicated localized positive selection in six gene pairs and purifying selection in 97.9% of pairs. Tissue-specific expression profiling across nine tissues showed that GmFLZ5, GmFLZ15, GmFLZ25, and GmFLZ34 had the highest expression levels detected across the GmFLZ family, with GmFLZ5 the most highly expressed member in leaves, nodules, and stem and showing moderate expression in pod, root, and root hairs, whereas GmFLZ18, GmFLZ23, and GmFLZ37 showed root-preferential expression. RT-qPCR validation under drought (20% PEG-6000) and salt (200 mM NaCl) treatments in the Giza 5 cultivar showed that 36 and 34 of the 40 GmFLZ genes, respectively, exhibited at least a two-fold change in expression, with GmFLZ21 and GmFLZ35 among the most strongly induced under salt stress. These findings provide an evolutionary and functional framework for the GmFLZ family and identify candidate genes for future functional studies in soybean stress tolerance.

Glycine max↗

PubMed2026

LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.

Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.

Humans↗

PubMed2026

ZBTB16-associated NK cell alterations reveal shared immunometabolic signatures linking primary Sjögren's syndrome and type 1 diabetes mellitus.

BACKGROUND: Primary Sjögren's syndrome (pSS) and type 1 diabetes mellitus (T1DM) share immune-inflammatory features, yet conserved pathogenic signatures linking these autoimmune disorders remain incompletely understood. The present research sought to uncover common molecular markers and dissect the underlying immune-metabolic cross-talk underlying pSS and T1DM. METHODS: Gene expression profiles of patients with pSS and T1DM were retrieved from the Gene Expression Omnibus database, normalized, and corrected for batch effects prior to downstream analyses. Overlapping potential biomarkers were screened by integrating differential expression analysis, weighted gene co-expression network analysis and least absolute shrinkage and selection operator regression. Functional enrichment based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases was implemented to interpret gene biological properties, and a protein-protein interaction network was further established afterwards. Diagnostic performance was evaluated using receiver operating characteristic analysis. Experimental validation was conducted in non-obese diabetic (NOD) mice using quantitative PCR, immunohistochemistry, and flow cytometry. The CIBERSORT algorithm was adopted to quantify immune cell infiltration levels. RESULTS: ZBTB16 was identified as a shared hub biomarker in both pSS and T1DM and exhibited favorable diagnostic performance. Experimental validation confirmed significantly reduced ZBTB16 expression in peripheral blood mononuclear cells, salivary gland tissues, and pancreatic tissues of NOD mice. Gene Set Enrichment Analysis indicated that ZBTB16-associated signatures were enriched in mitochondrial-related processes, neuroactive ligand-receptor interactions, and ribosome-related pathways. Immune infiltration analysis revealed that resting natural killer (NK) cells were positively correlated with ZBTB16 expression in both diseases. Flow cytometric analysis further confirmed a reduced proportion of resting NK cells in peripheral blood of NOD mice, consistent with the CIBERSORT-based prediction. CONCLUSION: This study identifies ZBTB16 as a shared biomarker linking pSS and T1DM. Reduced resting NK-cell abundance was consistently observed in both computational and experimental analyses, and bioinformatic correlation analysis suggested a positive association with ZBTB16 expression. These findings provide evidence for shared molecular and immunological signatures underlying the two autoimmune disorders and support further investigation of the biological role and diagnostic value of ZBTB16 in pSS and T1DM.

Sjogren's Syndrome↗

PubMed2026

MS4A3 as a potential prognostic biomarker for colon cancer: integrated analysis of expression patterns and immune cell infiltration.

BACKGROUND: Membrane Spanning 4-Domains A3 (MS4A3) has been confirmed to possess significant tumor-suppressive potential in various malignancies. However, its expression characteristics and clinical prognostic value in colon cancer (CC) still lack systematic and in-depth investigation. This study aimed to systematically investigate the expression pattern, prognostic value, immune microenvironment association, and biological function of MS4A3 in CC through integrated bioinformatics analyses and experimental validation. METHODS: This study utilized The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COAD) cohort to screen for genes significantly associated with CC and combined multiple independent Gene Expression Omnibus (GEO) datasets to validate the expression patterns and prognostic significance of MS4A3. Key biological pathways were identified through gene set enrichment analysis (GSEA), and tumor immune infiltration characteristics were evaluated using the CIBERSORT algorithm. Additionally, the expression of MS4A3 and its impacts on cellular functions were validated at the cellular level through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8), EdU, Transwell, and TUNEL assays. RESULTS: Analysis of public datasets revealed that MS4A3 is significantly downregulated in CC tissues, and its low expression is an independent risk factor for shortened overall survival (OS). GSEA indicated that MS4A3 downregulation is closely associated with the aberrant activation of the pentose phosphate pathway. Immune infiltration analysis showed that low MS4A3 expression is closely linked to the enrichment of M2 macrophages and neutrophils, as well as the upregulation of multiple immune checkpoint genes. In vitro experiments further confirmed that MS4A3 was lowly expressed in CC cell lines. Its overexpression significantly inhibited CC cell viability, proliferation, migration, and invasion, while simultaneously promoting cell apoptosis. CONCLUSIONS: MS4A3 expression is significantly decreased in CC tissues and is significantly correlated with poor prognosis, suggesting that this gene may serve as a potential prognostic biomarker.

MS4A3↗

PubMed2026

Nested co-expression network analysis identifies compact gene clusters in a black box.

MOTIVATION: Digital analysis of biological systems requires methods capable of identifying both broad and nested gene modules reflecting complex biological processes. Existing transcriptomic methods often miss compact gene sets corresponding to subprocesses in specialized cell types, limiting insights into functional heterogeneity. RESULTS: We present Nested-WGCNA, a two-stage unsupervised network analysis algorithm designed to identify coarse-grained and fine-grained gene modules. Applied to bulk RNA-Seq data, Nested-WGCNA reveals stable modules reproducible across datasets. When validated against scRNA-Seq data, these modules correspond to both major and minor immune cell subtypes. Application to immunotherapy response datasets uncovers predictive and prognostic biomarkers, highlighting its utility in treatment stratification and biomarker discovery. AVAILABILITY: The NestedWGCNA source code and analysis pipeline are available on GitHub (https://github.com/ilyada/NestedWGCNA) and archived on Zenodo (https://doi.org/10.5281/zenodo.18959244).

Algorithms↗

PubMed2025

RNAcare: integrating clinical data with transcriptomic evidence using rheumatoid arthritis as a case study.

BACKGROUND: Gene expression analysis is a crucial tool for uncovering the biological mechanisms that underlie differences between patient subgroups, offering insights that can inform clinical decisions. However, despite its potential, gene expression analysis remains challenging for clinicians due to the specialised skills required to access, integrate, and analyse large datasets. Existing tools primarily focus on RNA-Seq data analysis, providing user-friendly interfaces but often falling short in several critical areas: they typically do not integrate clinical data, lack support for patient-specific analyses, and offer limited flexibility in exploring relationships between gene expression and clinical outcomes in disease cohorts. Users, including clinicians with a general knowledge of transcriptomics, however, who may have limited programming experience, are increasingly seeking tools that go beyond traditional analysis. To overcome these issues, computational tools must incorporate advanced techniques, such as machine learning, to better understand how gene expression correlates with patient symptoms of interest. RESULTS: Our RNAcare platform, addresses these limitations by offering an interactive and reproducible solution specifically designed for analysing transcriptomic data from patient samples in a clinical context. This enables researchers to directly integrate gene expression data with clinical features, perform exploratory data analysis, and identify patterns among patients with similar diseases. By enabling users to integrate transcriptomic and clinical data, and customise the target label, the platform facilitates the analysis of the relationships between gene expression and clinical symptoms like pain and fatigue. This allows users to generate hypotheses and illustrative visualisations/reports to support their research. As proof of concept, we use RNAcare to link inflammation-related genes to pain and fatigue in rheumatoid arthritis (RA) and detect signatures in the drug response group, confirming previous findings. CONCLUSION: We present a novel computational platform allowing the interpretation of clinical and transcriptomics data in real-time. The platform can be used for data generated by the user, such as the patient data presented here or using published datasets. The platform is available at https://rna-care.mvls.gla.ac.uk/ , and its source code is https://github.com/sii-scRNA-Seq/RNAcare/ .

Humans↗

PubMed2026

Identification of mitochondrial energy metabolism-related candidate genes UQCR10 and NDUFA6 in pediatric tetralogy of fallot: an exploratory bioinformatics study.

BACKGROUND: Tetralogy of Fallot (TOF) is one of the most common cyanotic congenital heart diseases in infants and young children. Its molecular basis remains incompletely understood. This study aimed to identify mitochondrial energy metabolism-related candidate genes associated with pediatric TOF using public heart tissue transcriptomic datasets from the GEO database. METHODS: Datasets GSE146218 and GSE217772 were downloaded and merged, followed by batch-effect correction. Differential expression analysis was performed to identify differentially expressed genes (DEGs). Functional enrichment analysis, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network analysis were used to prioritize candidate genes. The Comparative Toxicogenomics Database (CTD) was used as an exploratory literature-based tool to summarize gene-disease associations. RESULTS: A total of 960 DEGs were identified. Functional enrichment analyses showed that these genes were mainly enriched in mitochondrial energy metabolism-related pathways, including oxidative phosphorylation and the mitochondrial respiratory chain. WGCNA and PPI network analyses further prioritized UQCR10 and NDUFA6 as candidate genes, and both genes showed increased expression in TOF heart tissue samples. CTD analysis suggested literature-based associations between these genes and cardiovascular or developmental disease-related terms. CONCLUSION: This exploratory bioinformatics study identified UQCR10 and NDUFA6 as mitochondrial energy metabolism-related candidate genes upregulated in pediatric TOF heart tissue. These findings suggest that mitochondrial respiratory chain-related transcriptional alterations may be involved in TOF-associated myocardial remodeling or stress responses. Further experimental and clinical validation is required to confirm their biological relevance.

Humans↗

PubMed2026

Distinct periarticular muscle transcriptomes: inflammation in rheumatoid arthritis versus metabolic dysregulation in osteoarthritis.

OBJECTIVES: Periarticular skeletal muscle abnormalities are recognised in rheumatoid arthritis (RA) and osteoarthritis (OA), but their divergent molecular pathologies are poorly defined. This study aimed to elucidate and directly compare the transcriptomic profiles of periarticular muscle in patients with RA and OA. METHODS: We performed bulk RNA sequencing of periarticular skeletal muscle samples collected during total joint arthroplasty from RA (n=6) and OA (n=4) patients. Differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), pathway enrichment, and gene set variation analyses were conducted to identify disease-specific molecular features and their clinical associations. RESULTS: The two conditions showed fundamentally distinct profiles. RA muscle exhibited a pronounced inflammatory signature, characterised by upregulation of cytokine-responsive genes including FOS, EGR1, and CXCL2, and enrichment of tumour necrosis factor-α and interleukin-6 (IL-6)/JAK-STAT3 signalling. In contrast, OA muscle was characterised by metabolic dysregulation, with upregulation of genes linked to adipogenesis (PCK1, SFRP4) and significant enrichment of epithelial-to-mesenchymal transition (EMT) signalling. These divergent profiles were further supported by WGCNA, which identified distinct modules reflecting heightened innate immune and complement activation in RA, and disrupted metabolic processes in OA. Notably, in RA, the IL-2-STAT5 signalling pathway was unique among those tested in showing a strong positive correlation with DAS28-ESR (r=0.94, p=0.019). CONCLUSIONS: This study reveals distinct molecular pathologies in the periarticular muscle of RA and OA. RA muscle shows an intense inflammatory profile potentially linked to cachexia, whereas OA muscle displays features of metabolic disease and pro-fibrotic remodelling.

Humans↗