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PubMed2024

Effects of different temperatures on chondrocyte growth: a transcriptomic analysis.

BACKGROUND: Our previous study demonstrated that temperature-related microwave ablation (MWA) can safely modulate growth plates of piglets' vertebrae. Therefore, this study is designed to investigate the effects of different temperatures on chondrocyte viability and the underlying molecular mechanisms in vitro. METHODS: Following a 10-minute treatment at different temperatures (37 °C, 40 °C, 42 °C, 44 °C, 46 °C, 48 °C, and 50 °C), CCK-8 assay was used to examine the viability of ATDC5 cells at 12 h. Differentially expressed genes (DEGs) and the hub genes in ATDC5 cells treated at 37 °C, 40 °C and 44 °C were identified using RNA-seq. The expression of hub genes in ATDC5 cells was validated using RT-qPCR. RESULTS: Compared with 37 °C, exposure to 40 °C significantly increased the viability of ATDC5 cells, while 42 °C had no significant effect. Additionally, exposure to 44 °C, 46 °C, 48 °C, and 50 °C exhibited the opposite pattern, with ATDC5 cells being particularly less than 50% active after treatment at 46 °C, 48 °C, and 50 °C. Differential expression analysis identified 179, 374 and 221 DEGs in the comparisons of 40 °C vs. 37 °C, 44 °C vs. 37 °C, and 44 °C vs. 40 °C, respectively. These DEGs predominantly regulated proliferation, differentiation, necrosis, inflammatory and immune responses, and ECM synthesis/degradation. Furthermore, they were associated with the Ras, PI3K/AKT, mTOR, cAMP, and MAPK pathways. Agt, Hspa1a, Hspb1, and Nlrc4 were identified as hub genes in DEGs, and RT-qPCR confirmed that the mRNA expression patterns of these hub genes in ATDC5 cells were largely consistent with the RNA-seq results. CONCLUSION: The regulation of chondrocyte viability by temperature is associated with Ras, PI3K/AKT, mTOR, cAMP, and MAPK pathways. Additionally, Agt, Hspa1a, Hspb1, and Nlrc4 may be the key regulatory genes in this process.

Chondrocytes↗

PubMed2026

Transcriptome Analysis Reveals Key Drought-Stress-Responsive Genes in Two Bermudagrass Genotypes.

Drought inhibits grass development and survival. However, molecular-based studies on drought tolerance mechanisms in bermudagrass (Cynodon dactylon) remain scarce. Therefore, a drought-resistant bermudagrass (Tianshui) and a drought-sensitive (Zhengzhou) genotype were selected and subjected to 28 days of 50% drought stress. Leaves were sampled for RNA sequencing. Under drought stress, 2410 differentially expressed genes (DEGs) were discovered in which 1214 were upregulated (tolerant vs. sensitive) and 1196 downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that these specific DEGs are notably present in hormonal signal transduction pathways, flavonoids biogenesis, carbohydrate metabolic processes, abscisic acid-mediated pathways, MAPK signaling, and gluconeogenesis. Additionally, the plant hormone signal transduction pathway is predominantly linked to abscisic acid signal transduction, and many other plant hormones were also drought-responsive. The study specifically targeted genes associated with the antioxidant enzyme system, with a particular emphasis on responsive TFs such as MYB, bHLH, bZIP, GRAS, and WRKY. This study establishes the theoretical framework and identifies gene sources for the genetic enhancement and breeding of bermudagrass in the future.

Cynodon↗

PubMed2026

Comparative transcriptome analysis reveals ncRNA-mediated regulatory networks associated with muscle crispiness in grass carp.

Non-coding RNAs (ncRNAs) have been demonstrated to be involved in muscle development and to function as key regulators. However, the molecular mechanism underlying muscle crispiness in grass carp (GC) remains poorly understood, and whether these ncRNAs are involved in its regulation is still unknown. In the current investigation, differentially expressed (DE) RNAs (including lncRNAs, circRNAs, miRNAs, and mRNAs) were identified; concomitantly, target genes prediction was conducted, and functional and signaling pathway enrichment analyses were performed. Pathways related to muscle crispiness were identified, and the competitive endogenous RNA (ceRNA) (lncRNA/circRNA-miRNA-mRNA) regulatory network was further constructed. The results showed that a total of 126 DE-lncRNAs, 17 DE-circRNAs, 329 DE-miRNAs, and 442 DE-mRNAs were identified in muscle tissues of both the GC and crisp grass carp (CGC). GO and KEGG enrichment analyses revealed that target genes of DE-ncRNAs were significantly enriched in signaling pathways, including structural constituents of muscle, apoptosis, oxidative phosphorylation, and regulation of actin cytoskeleton, suggesting that these pathways may be involved in muscle texture remodeling. Subsequently, DE-RNAs enriched in related pathways were identified, and a core ceRNA regulation network comprising 3 lncRNAs, 4 circRNAs, 3 miRNAs, and 17 mRNAs was constructed. Additionally, 10 DE-RNAs from randomly selected groups were validated by qRT-PCR. Our findings not only provide scientific evidence elucidating the molecular mechanisms underlying muscle crispiness in GC but also establish a foundation for studying changes in muscle textural qualities across other fish species.

Animals↗

PubMed2026

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma↗

PubMed2026

Research on identification of key genes and immune-metabolic mechanisms in atrial fibrillation through integrated multi-cohort transcriptomic analysis and machine learning.

This study aimed to integrate multiple datasets for the identification of atrial fibrillation (AF)-related differentially expressed genes (DEGs), analyze their underlying mechanisms through functional enrichment and machine learning, construct diagnostic models, and explore immune-metabolic interactions to provide novel biomarkers and theoretical foundations. Gene expression datasets were integrated and normalized, with batch effects removed using principal component analysis. Differential expression analysis, functional enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways), and machine learning-based feature gene selection and model construction were performed. Shapley additive explanations analysis was utilized to interpret the constructed models, while gene set enrichment analysis, gene set variation analysis, and immune cell infiltration analysis were conducted to investigate the associations between feature genes and immune infiltration. After integrating and normalizing gene expression data and eliminating batch effects via principal component analysis, 6 DEGs were identified, including 4 upregulated and 2 down-regulated ones. Functional enrichment analysis showed these DEGs were significantly enriched in neuro-related biological processes and pathways, indicating their key roles in AF pathogenesis. Five key feature genes were selected using LASSO, random forest, and support vector machine-recursive feature elimination algorithms. They had significant expression differences between the AF and control groups (P < .001) and were located on distinct chromosomes. The constructed random forest and support vector machine models performed excellently (area under the curve ≥ 0.85). Shapley additive explanations analysis revealed TNNI1 contributed most to model prediction, with its expression significantly positively correlated with immune cell infiltration. Gene set enrichment analysis and gene set variation analysis analyses further showed feature genes participated in AF pathogenesis by regulating immune modulation, metabolic pathways, and autophagy. Immune cell infiltration analysis found altered proportions of T-cell subsets and M0 macrophages in the AF group, along with complex links between feature gene expression and immune cell function. This study systematically elucidated the unique gene expression patterns and key regulatory pathways associated with AF, clarifying the crucial roles of feature genes in immune regulation, metabolic imbalance, and cellular dysfunction. These findings provide a theoretical basis and potential therapeutic targets for understanding AF pathogenesis and developing targeted treatment strategies.

Atrial Fibrillation↗

PubMed2026

Comparative analysis of histological and transcriptomic characteristics in caudal muscles of nile crocodiles (Crocodylus niloticus), siamese crocodiles (Crocodylus siamensis), and their hybrids.

Crocodylus niloticus and Crocodylus siamensis are high-value aquaculture species. C. niloticus is large-bodied but less abundant, while C. siamensis grows fast but is small-sized. Their hybrids combine parental advantages, yet relevant research is scarce. This study compared the histological and transcriptomic characteristics of the caudal muscle across the three taxa. HE staining indicated that C. niloticus had significantly larger myofiber diameters (p < 0.05); C. siamensis had the smallest, and the myofiber density of hybrids was much closer to that of C. siamensis. Masson's trichrome staining indicated that C. niloticus had the thickest collagen fibers (p < 0.05), C. siamensis the thinnest, and hybrids exhibited highly similar histological traits to C. siamensis. C. niloticus had higher LDH and SDH activities in caudal muscles, whereas the hybrid crocodile indicated the highest CK activity. Transcriptomic analysis identified numerous differentially expressed genes (DEGs), which were enriched in growth, muscle metabolism, and energy allocation pathways via GO/KEGG annotations. PPI analysis screened 24 hub genes related to energy metabolism. This study systematically reveals caudal muscle differences, providing insights into growth-related molecular mechanisms and theoretical support for crocodile artificial breeding.

Animals↗

PubMed2026

Comprehensive Profiling of Claudin 18.2 Immunohistochemical Expression in 564 Surgically Resected Gastric and Gastroesophageal Junction Adenocarcinomas.

Claudin 18 isoform 2 (CLDN18.2) is a novel therapeutic target for advanced, HER2-negative gastric/gastroesophageal junction (GEJ) adenocarcinoma positive for CLDN18.2 immunohistochemical (IHC) expression, defined as ≥75% tumor cells with moderate-to-strong membranous staining. Clinical studies for emerging CLDN18.2-targeted therapeutics have used less stringent enrollment criteria to test the efficacy of such therapies in patients with moderate-to-low CLDN18.2 IHC expression. Anticipating the advent of such treatments, this study aimed to provide a comprehensive survey of CLDN18.2 expression using a clinical trial-validated CLDN18.2 monoclonal antibody in surgically resected gastric/GEJ adenocarcinomas and characterize CLDN18.2-positive carcinomas using both high- and low-expression thresholds. Crisp membranous CLDN18.2 staining was detected in 59% (335/564) carcinomas, including 57% (164/286) of gastric and 62% (171/278) of GEJ adenocarcinomas. Most gastric (147/164, 90%) and GEJ (166/171, 97%) adenocarcinomas with staining demonstrated moderate or strong staining intensity. Using the high-expression threshold (≥75% tumor cells with moderate-to-strong staining), positive CLDN18.2 expression was observed in 20% (57/286) of gastric and 27% (75/278) of GEJ adenocarcinomas and was associated with Epstein-Barr virus status (P < .001) and stage I gastric adenocarcinomas (P = .02) but stage IV GEJ adenocarcinomas (P = .03). Using a low-expression threshold (≥10% tumor cells with membranous staining), positive CLDN18.2 remained significantly associated with stage I (P = .004) and showed an unadjusted association with improved disease-specific survival in gastric adenocarcinomas (P = .045), which was not retained in multivariable analysis. Whole transcriptomic analysis showed concordance between IHC and CLDN18 messenger RNA expression. Transcriptomic alterations in CLDN18.2 IHC-positive gastric adenocarcinomas included pathways in drug resistance and tumor invasion. In summary, our study presents a detailed characterization of the prevalence and distribution of CLDN18.2 IHC expression patterns. Our results showed that 59% surgically resected gastric/GEJ adenocarcinomas exhibited CLDN18.2 staining. CLDN18.2 IHC positivity defined by both high- and low-expression thresholds may be associated with early-stage gastric adenocarcinoma. These findings expand our recognition of patients who may benefit from CLDN18.2-targeted therapy.

CLDN18.2↗

PubMed2026

Transcriptome-Proteome Analysis of Human Naive and Memory B Cell Subsets Reveals Isotype and Subclass-Specific Phenotypes.

Antibodies produced by B cells aid in the recognition and clearance of pathogens and are the cornerstone of vaccination strategies. Humans produce nine different antibody isotypes, and their effector functions differ according to the type of antigen and route of exposure. Phenotypic variation between isotype-switched B cell subsets is expected but not studied in detail. To obtain a molecular definition of isotype-defined cell identity, we performed proteomics and transcriptomics on isotype-defined populations of human naive and memory B cells (MBCs): CD27-IgM+IgD+, CD27+CD38lo/-IgM+IgD+, CD27+CD38lo/-IgM+IgD-, and IgA1, IgA2, IgG1, IgG2, IgG3, and IgG4 MBCs (CD27+CD38lo/-Ig+). Combined proteome and transcriptome analysis revealed that mRNA and protein expression profiles separate isotype-defined B cell subsets according to their differentiation status. mRNA and protein expression levels correlated reasonably well for many genes. IgG4-switched B cells were most distinct from naive B cells in terms of mRNA as well as protein expression profiles. Besides a distinct expression profile of cytokine and Fc receptors, we identified a high expression of IgE-coding mRNA in IgG4-switched B cells. SDR16C5 was identified as uniquely upregulated in IgG4-switched B cells. Taken together, this study highlights the distinct phenotypic profile of IgG4-switched B cells.

Humans↗

PubMed2026

Mycosis Fungoides-Like Atopic Dermatitis Represents a Th22-Dominant Inflammatory Endotype.

BACKGROUND: Early-stage mycosis fungoides (MF) often presents diagnostic challenges because of its clinical overlap with atopic dermatitis (AD). In clinical practice, we encountered a subset of patients with severe AD who fulfilled the MF diagnostic criteria yet remained clinically indistinguishable from AD and presented refractoriness to advanced therapies. We termed this ambiguous entity "mycosis fungoides-like AD" (mfAD) and sought to determine whether it represents malignant transformation or a distinct inflammatory endotype of AD. METHODS: Skin biopsies were obtained from 7 patients with AD and 11 patients with mfAD. We performed paired single-cell RNA sequencing and single-cell T-cell receptor sequencing analyses. Publicly available MF and AD datasets were integrated for comparative analysis. Spatial transcriptomic profiling was used to contextualize single-cell findings within the tissue architecture. RESULTS: Comparative transcriptomic analysis revealed that T cells in mfAD were aligned with those in AD and lacked genomic instability. High-resolution profiling showed that mfAD was characterized by oligoclonal Th22 expansion rather than a single dominant malignant clone. Notably, all patients with mfAD achieved rapid clinical remission with selective JAK1 inhibition, indicating the therapeutic response characteristics of inflammatory dermatoses. CONCLUSION: Our findings demonstrate that mfAD is not a true malignancy, but rather a Th22-driven inflammatory endotype of AD. These results redefine mfAD as an inflammatory subtype within the AD spectrum, providing a mechanistic explanation for both the "pseudo-monoclonality" that leads to MF misdiagnosis and the failure of dupilumab. This study establishes a rationale for the use of JAK inhibitors in precision medicine for this patient population.

JAK inhibitor↗

PubMed2026

Genetic dissection of cardiac iron regulation using transcriptome network analysis and systems genetics in BXD mice.

Cardiac iron homeostasis is essential for myocardial energy metabolism and contractile function, yet the genetic and molecular mechanisms governing iron levels within the heart remain poorly understood. We used a systems genetics approach to dissect the transcriptional regulation of cardiac iron homeostasis. Myocardial iron level varies substantially across BXD strains (40-112 μg/g) and is under heritable genetic control (H2 = 0.38). Elevated cardiac iron is associated with reduced ventricular mass, increased ventricular ectopy, and prolonged atrioventricular conduction in the BXD population. Weighted gene co-expression network analysis of the BXD heart transcriptome identified a co-expression module that was significantly and negatively correlated with cardiac iron levels in both young and old BXD mice and enriched for pathways related to metabolic regulation, cyclic AMP (cAMP) signaling, circadian entrainment, and cardiovascular physiology. The module showed substantial overlap with a curated cardiac iron gene set, and cross-species enrichment analysis confirmed its conservation in human cardiomyopathy differentially expressed genes (enrichment ratio = 1.49; false discovery rate [FDR] = 0.0342). Quantitative trait locus (QTL) mapping of the first principal component of the overlapping module iron genes (n = 38), corroborated by individual gene mapping, identified trans-eQTL hotspots on multiple chromosomes, implicating Fcho2, Gcc2, and Rmdn1 as candidate upstream regulators operating through sequential steps of intracellular iron trafficking. Together, these findings establish a systems-level map of cardiac iron gene regulation, identify candidate genetic regulators, and provide a molecular framework linking disruption of iron-related transcriptional networks to structural and electrical cardiac dysfunction with implications for iron-related heart diseases.

BXD mouse population↗

PubMed2026

Potential Involvement of the IL-6/STAT3/MMP12 Signaling Axis in DMSO-Mediated Anti-Fibrotic Effects in Experimental Silicosis.

This study aims to investigate the anti-inflammatory and anti-fibrotic effects of dimethyl sulfoxide (DMSO) in a mouse model of silicosis, thereby exploring its potential therapeutic value. A mouse model of silicosis was established by intranasal instillation, and DMSO treatment was administered via intraperitoneal injection. The experiment was conducted over a period of 1 month. Lung tissues were collected from all mice; a subset was subjected to transcriptomic analysis, and differentially expressed genes were identified using the limma package. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were conducted using ClusterProfiler to investigate gene functions and associated pathways. The remaining samples were subjected to histopathological assessment by hematoxylin and eosin staining (HE) and Masson's trichrome staining, while Western blot analysis was performed to validate transcriptomic results. This study suggests that DMSO may alleviate the fibrotic process in silicosis by modulating the IL-6/STAT3-MMP12 signaling axis. In the silica-induced silicosis mouse model, DMSO attenuated disease-associated weight loss and reduced collagen deposition. Transcriptomic analysis indicated that DMSO suppressed the activity of multiple fibrosis-related pathways and identified 51 key genes, including MMP12, which was significantly downregulated. Western blot analysis further confirmed reduced MMP12 expression, accompanied by markedly decreased levels of IL-6 and p-STAT3, suggesting the IL-6/STAT3 pathway may play a crucial role in regulating MMP12 expression. DMSO may attenuate inflammatory responses and pulmonary fibrosis in silicosis by inhibiting activation of the IL-6/STAT3 signaling pathway, thereby reducing MMP12 expression.

Animals↗

PubMed2026

A Practical Workflow for Spatial Transcriptomics Data Analysis: From Data Acquisition to Advanced Analyses.

Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving the two-dimensional spatial context of mRNA molecules within tissue sections, enabling studies of tissue architecture and microenvironment-associated biology. However, ST analysis remains challenging because data import, quality control, integration, deconvolution, spatial statistics, and visualization often require multiple software environments and reproducible parameter choices. This protocol presents a practical computational workflow for public ST datasets in R, beginning with data acquisition and software setup and proceeding through Seurat-based data loading, quality control, normalization, multi-sample integration, clustering, and spatially variable gene analysis. The workflow then applies complementary deconvolution strategies, including reference-guided SPOTlight analysis and unsupervised STdeconvolve topic modeling, followed by Giotto-based spatial cell-cell communication analysis and interactive region-of-interest (ROI) selection using a custom Python Dash application. By emphasizing script-based execution, explicit parameter rationales, expected outputs, and troubleshooting checkpoints, the protocol provides an adaptable framework for standard array-based ST datasets and related platforms after dataset- and platform-specific parameter evaluation.

Spatial Transcriptomics↗

PubMed2026

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗

PubMed2026

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

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

Spatial Transcriptomics↗

PubMed2025

Multiomics Analysis Reveals Therapeutic Targets for Chronic Kidney Disease With Sarcopenia.

BACKGROUND: The presence of sarcopenia in patients with chronic kidney disease (CKD) is associated with poor prognosis. The mechanism underlying CKD-induced muscle wasting has not yet been fully explored. This study investigates the influence of renal secretions on muscles using multiomics sequencing. METHODS: The kidney transcriptome analysis by RNA-seq and protein profiling by tandem mass tag (TMT), serum TMT and muscle TMT were performed in CKD established using 0.2% adenine and control mice. Spp1 recombinant protein was used to study its effect on myotube atrophy in vitro. In animal experiments on CKD, pharmacological inhibition of Spp1 was used to explore the role of Spp1 in skeletal muscle wasting. Transcriptome analysis was performed to identify differentially expressed genes (DEGs) in the gastrocnemius muscle following Spp1 pharmacological inhibition. RESULTS: In the renal transcriptome and TMT, 503 and 377 proteins/genes respectively were co-upregulated and co-downregulated. In the serum TMT of CKD and normal control (NC) mice, 22 upregulated and 7 downregulated differentially expressed proteins (DEPs) showed the same expression patterns as those in the kidney transcriptome and TMT analysis. Based on bioinformatics analysis and reported studies, we selected Spp1 for further validation. Spp1 recombinant protein was added to C2C12 myotubes in vitro, and the results indicated that Spp1 significantly increased the protein levels of the muscle atrophy marker (Murf-1) and promoted the smaller myotubes (all p < 0.05). Compared with NC mice, Spp1 mRNA and protein levels were significantly upregulated in the kidneys of CKD mice, and the serum concentration of Spp1 was also markedly increased (all p < 0.05). In animal experiments, pharmacological inhibition of Spp1 increased the weights of gastrocnemius and tibialis anterior muscles (p < 0.05) and improved muscle atrophy phenotype. Transcriptome analysis showed that DEGs in the gastrocnemius muscle following Spp1 pharmacological inhibition were enriched in protein digestion and absorption, glucagon signalling pathway, apelin signalling pathway and ECM-receptor interaction pathway. CONCLUSIONS: Our study is the first to establish a regulatory network of kidney-muscle crosstalk to explore the potential mechanism of CKD-related sarcopenia. Employing multiomics analysis, cellular assessment and animal experiments, we have identified that Spp1 could potentialy serve as a promising therapeutic target for CKD patients with sarcopenia.

Sarcopenia↗

PubMed2026

Identification of Critical Genes for Recurrent Aphthous Ulcer by Transcriptome Data Analysis and Mendelian Randomization.

PURPOSE: Recurrent aphthous ulcer (RAU) is a common oral mucosal disorder with a poorly understood etiology, significantly affecting patients' quality of life. This study aims to investigate critical genes linked to RAU and explore their biological mechanisms using transcriptomic data and Mendelian randomization (MR) analysis. MATERIALS AND METHODS: RAU-related gene expression data from the GEO database (GSE37265) were analyzed to identify differentially expressed genes (DEGs). A two-sample MR approach was used to assess the causal impact of expression quantitative trait loci (eQTL) on RAU. Critical genes were identified by intersecting DEGs with significant MR findings. GO and KEGG pathway enrichment analyses were performed, along with GSEA and immune cell infiltration analysis, to investigate the functions and mechanisms of these genes in RAU. RESULTS: A total of 184 differentially expressed genes (DEGs) were identified, while 339 RAU-associated genes were screened through MR analysis. Cross-validation further identified 7 critical genes. Among these, CCR1, ERP27, HCK, MICB, and SLC2A3 showed protective associations with RAU risk, whereas CD177 and IFITM1 were positively associated with increased risk. Enrichment analysis revealed that these genes are involved in specific biological processes, including cell migration, immune response, and metabolic regulation, which are closely linked to RAU pathogenesis. CONCLUSION: This systematic study comprehensively investigates the critical causative genes underlying RAU, emphasizing the intricate relationships between immune regulation and metabolic disturbances in its pathology. These findings lay a solid foundation for the development of novel biomarkers and may inform future research on targeted therapeutic strategies for RAU.

Stomatitis, Aphthous↗

PubMed2025

Transcriptome-Wide Analysis of the 5' Cap Status of RNA Using 5' Monophosphate-Dependent Exonuclease Digestion and RNA Sequencing.

Eukaryotic mRNAs carry an N7-methylguanosine (m7G) cap structure at their 5' extremity, which protects them from the degradation by 5'-3' exoribonucleases and plays a pivotal role in mRNA metabolism, promoting splicing, nuclear export, and translation. Decapping, the enzymatic process that removes this structure, is a key event during cytoplasmic mRNA 5'-3' decay, leading to the degradation of the transcript body by Xrn1. In this chapter, we describe a procedure to assess the cap status of RNA at the transcriptome level. It is based on a treatment of total RNA extracts with a 5' monophosphate-dependent exonuclease, which like Xrn1 specifically degrades decapped RNAs harboring 5' monophosphate extremities, but not RNAs with intact m7G cap. The digested RNAs are then analyzed by RNA sequencing.

Exoribonucleases↗

PubMed2026

Identification and characterization of G protein-coupled receptors in the nocturnal halictid bee Megalopta genalis.

G protein-coupled receptors (GPCRs) are one of the largest families of membrane proteins in insects, regulating vision, neural signal transduction, and various physiological behaviors. Megalopta genalis exhibits a unique facultatively eusocial lifestyle and possesses adaptations for nocturnal activity; however, its GPCR family has not yet been systematically characterized. In this study, we performed genome-wide identification, phylogenetic analysis, and expression profiling of GPCRs in M. genalis by integrating genomic annotation and transcriptomic analysis. The results showed that a total of 99 GPCRs were identified in the genome of M. genalis, which were classified into four major families. Here, we show that M. genalis has undergone lineage-specific GPCR repertoire remodeling, marked by the expansion of novel orphan receptors and the systematic loss of multiple receptor subtypes, such as the neuropeptide receptors MIP-R and NPFR. Moreover, opsins have formed a diverse array of combinations and non-GPCR odorant receptors have undergone significant expansion via tandem duplication. Together, these features may represent part of the molecular repertoire associated with the adaptation of M. genalis to a nocturnal lifestyle. Furthermore, transcriptomic analysis revealed distinct spatiotemporal expression divergence within each of the Mth/Mthl and Fz GPCR families, suggesting functional specialization across development and adult tissues. This study provides the first systematic identification and initial functional characterization of GPCRs in M. genalis, revealing an evolutionary pattern characterized by the coexistence of contraction and expansion within the GPCR family. These findings lay a foundation for further studies aimed at elucidating the roles of these GPCRs in regulating M. genalis physiology and behavior.

Animals↗