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PubMed2024

Transcriptome analysis under pecan scab infection reveals the molecular mechanisms of the defense response in pecans.

Pecan scab, caused by the fungal pathogen Venturia effusa, is the most devastating disease of pecan (Carya illinoinensis) in the southeastern United States. Resistance to this pathogen is determined by a complex interaction between host genetics and disease pathotype with even field-susceptible cultivars being resistant to most scab isolates. To understand the underlying molecular mechanisms of scab resistance in pecan, we performed a transcriptome analysis of the pecan cultivar, 'Desirable', in response to inoculation with a pathogenic and a non-pathogenic scab isolate at three different time points (24, 48, and 96 hrs. post-inoculation). Differential gene expression and gene ontology enrichment analyses showed contrasting gene expression patterns and pathway enrichment in response to the contrasting isolates with varying pathogenicity. The weighted gene co-expression network analysis of differentially expressed genes detected 11 gene modules. Among them, two modules had significant enrichment of genes involved with defense responses. These genes were particularly upregulated in the resistant reaction at the early stage of fungal infection (24 h) compared to the susceptible reaction. Hub genes in these modules were predominantly related to receptor-like protein kinase activity, signal reception, signal transduction, biosynthesis and transport of plant secondary metabolites, and oxidoreductase activity. Results of this study suggest that the early response of pathogen-related signal transduction and development of cellular barriers against the invading fungus are likely defense mechanisms employed by pecan cultivars against non-virulent scab isolates. The transcriptomic data generated here provide the foundation for identifying candidate resistance genes in pecan against V. effusa and for exploring the molecular mechanisms of disease resistance.

Carya↗

PubMed2025

GSK3B inhibition partially reverses brain ethanol-induced transcriptomic changes in C57BL/6J mice: Expression network co-analysis with human genome-wide association studies.

Alcohol use disorder (AUD) is a chronic behavioral disease with greater than 50% of its risk due to complex genetic contributions. Existing pharmacological and behavioral treatments for AUD are minimally effective and underutilized. Animal model behavioral genetics and human genome-wide association studies have begun to identify individual genes contributing to the progressive compulsive consumption of ethanol that occurs with AUD, promising possible new therapeutic targets. Our laboratory has previously identified Gsk3b as a central member in a network of ethanol-responsive genes in mouse prefrontal cortex, which altered ethanol consumption with genetic manipulation and was also significantly associated with risk for alcohol dependence in human genome-wide association studies. Here we perform detailed brain RNA sequencing transcriptomic studies to characterize a highly specific and clinically available GSK3B pharmacological inhibitor, tideglusib, as a possible therapeutic for clinical trials on treatment of AUD. A model of chronic intermittent ethanol consumption was used to study gene expression changes in prefrontal cortex and nucleus accumbens in the presence or absence of tideglusib treatment. Multivariate analysis of differentially expressed genes showed that tideglusib largely reversed ethanol- induced expression changes for two prominent clusters of genes in both prefrontal cortex and nucleus accumbens. Bioinformatic analysis showed these genes to have prominent roles in neuronal functioning and synaptic activity. Additionally, mouse brain differential gene expression data was analyzed together with human protein-protein interaction and genome-wide association studies on AUD to derive networks responding to tideglusib and relevant to human genetic risk for alcohol dependence. These studies identified discrete networks significantly enriched with genes provisionally associated with AUD, and provide key information on central hubs of such networks. Together these studies document tideglusib as a major modulator of chronic ethanol consumption-evoked brain gene expression signatures, and identify possible new targets for therapeutic modulation of AUD.

Journal Article↗

PubMed2026

Prognostic value of genes associated with metastasis and propionate metabolism in rectal cancer.

BACKGROUND: Research indicates that alterations in propionate metabolic pathways play a critical role in cancer development and invasion. Postoperative metastatic recurrence remains a major cause of mortality in patients with rectal cancer. However, propionate metabolism-related genes (PMRGs) in rectal cancer remain insufficiently characterized. Therefore, this study aimed to identify prognostic biomarkers associated with lymph node metastasis and propionate metabolism and construct a risk‑prediction model for rectal cancer via bioinformatic analyses. METHODS: The Cancer Genome Atlas-Rectum Adenocarcinoma (TCGA-READ) and GSE87211 datasets, together with a curated PMRGs gene set, were used in this study. Pearson correlation analysis was performed to assess associations between overlapping genes (differentially expressed genes between READ and normal tissues, as well as between N0 and N1-N2 stages) and PMRGs, leading to the identification of candidate genes. Functional enrichment analyses were subsequently conducted to characterize the biological roles of these candidates. Prognostic biomarkers were identified using univariate Cox regression combined with least absolute shrinkage and selection operator (LASSO) regression, and a prognostic model was constructed accordingly. Independent prognostic validation was then performed. In addition, immune checkpoint profiling and immunotherapy response analyses were conducted across risk subgroups. Single-gene Gene Set Enrichment Analysis (GSEA) was applied to elucidate the pathways associated with the identified biomarkers. Finally, drug sensitivity analyses were performed. RESULTS: A total of 157 candidate genes were identified through the analytical pipeline. Functional enrichment analysis indicated that these genes were primarily involved in inflammatory response regulation and tumor necrosis factor (TNF) signaling pathways. Five prognostic biomarkers were subsequently identified and incorporated into a predictive model. External validation using the GSE87211 cohort confirmed the robustness of the model. Risk score and disease status were identified as independent prognostic factors. Six immune checkpoint molecules exhibited differential expression between risk groups. Correlation analyses revealed that the risk score was positively associated with most immune checkpoint genes. Single-gene GSEA demonstrated that the biomarkers were mainly enriched in ribosomal biogenesis and cell adhesion molecule-related pathways. Furthermore, 51 therapeutic agents exhibited significantly different half-maximal inhibitory concentration (IC50) values between risk subgroups. CONCLUSIONS: This study identified five biomarkers (CCL24, IGFBP3, ODC1, PYGM, and VKORC1) associated with lymph node metastasis and propionate metabolism pathways, providing a potential foundation for prognostic prediction in patients with rectal cancer.

Rectal cancer↗

PubMed2026

Shared genetic architecture and neurobiological pathways of problematic alcohol use and anxiety disorders.

Problematic alcohol use (PAU) and anxiety disorders (ANX) frequently co-occur, implying shared genetic and neurobiological foundations. However, the directionality of potential causal relationships and the specific mechanisms underlying the overlap remain unclear. Thus, we investigated the shared genetic architecture and neurobiological pathways between PAU and ANX using a multimethod genomic approach. We analyzed summary statistics from genome-wide association studies (GWAS) of PAU and ANX using Mendelian Randomization to assess causal associations between ANX and PAU. We used MiXeR to assess the overall shared genomic architecture, Local Analysis of (co)Variant Association to estimate regional genetic correlations, and conjunctional false discovery rate (conjFDR) to identify individual overlapping loci. We used FUMA to map single-nucleotide polymorphisms (SNPs) to independent loci, conduct differential gene expression analyses across 30 general and 54 specific tissue types, and perform cell-type specificity analyses using a human brain cell atlas. Druggability of identified targets was also evaluated. Mendelian Randomization analyses indicated bidirectional causal associations between ANX and PAU. MiXeR identified moderate polygenic overlap (52.5%) and genetic correlation (rg = 0.44) between the traits, with high effect direction concordance among shared estimated causal variants (86.4%). ConjFDR identified 97 shared lead SNPs, of which 89 had concordant and 8 discordant effects on PAU and ANX. These loci mapped to 97 genes, including DRD2 and PDE4B, genes linked to dopaminergic and cAMP signaling pathways, respectively. Concordant gene expression was enriched in brain, nerve, adrenal gland, esophagus, stomach, and colon, with enriched expression specifically in the prefrontal cortex, anterior cingulate cortex, hippocampus, hypothalamus, substantia nigra and amygdala. FUMA cell-type enrichment analysis identified associations predominantly in neurons from the cerebral cortex, hippocampus, and thalamus. We found substantial genetic and neurobiological overlap between PAU and ANX, highlighting reciprocal, causal relationships between the traits, with differentially expressed genes enriched in addiction- and anxiety-relevant brain regions. These findings support shared genetic and neurobiological mechanisms linking PAU and ANX, while acknowledging that some signals may reflect broader internalizing or psychiatric liability.

Journal Article↗

PubMed2025

Deciphering estrogen receptor alpha-driven transcription in human endometrial stromal cells via transcriptome, cistrome, and integration with chromatin landscape.

OBJECTIVE: To investigate estrogen receptor gene 1 (ESR1) and estrogen-driven transcription in human endometrial stromal cells. DESIGN: RNA sequencing (RNA-seq) and Cleavage Under Targets and Release Using Nuclease (Cut&Run) were performed on telomerase-immortalized human endometrial stromal cells with Clustered Regularly Interspaced Short Palindromic Repeats-mediated ESR1 activation. Hi-C-based chromatin architecture analysis (H3K27ac HiChIP) was conducted in primary endometrial stromal cells. SUBJECTS: Biopsies from two healthy, reproductive-aged volunteers with regular menstrual cycles and no history of gynecological malignancies. EXPOSURE: The ESR1-activated and control endometrial stromal cells were treated with estradiol (E2) or vehicle. Primary endometrial stromal cells were treated with vehicle or a decidualization cocktail. MAIN OUTCOME MEASURES: Differential gene expression analysis (RNA-seq) identified ligand-independent and -dependent ESR1 activity. Cut&Run profiled ESR1 genomic binding in ESR1-activated cells. H3K27ac HiChIP mapped hormone-induced changes in chromatin looping in primary cells. RESULTS: Among seven tested guide RNAs (gRNA), the ESR1-3 gRNA induced robust ESR1 activation and restored E2 responsiveness. Bulk RNA-seq revealed both ligand-dependent and -independent ESR1 transcriptional programs regulating inflammation, proliferation, and cancer-related pathways. Notably, 72% of differentially expressed genes overlapped with genes active in human endometrial tissue during the proliferative estrogen-dominant phase, supporting their physiological relevance. The Cut&Run-seq identified genome-wide ESR1 binding sites, with most binding sites located at distal regulatory elements. Integration of Cut&Run data with H3K27ac HiChIP chromatin loops linked distal ESR1 binding sites to gene promoters, including genes involved in decidualization (e.g., FOXO1) and endometrial cancer (e.g., ERRFI1, NRIP1, and EPAS1). Functional assays showed that ESR1 promotes cell viability and, in the presence of E2, enhances migration. CONCLUSION: The CRISPR-mediated ESR1 activation restores estrogen responsiveness in endometrial stromal cells. Combined transcriptomic, cistromic, and chromatin architecture analyses reveal ESR1's role in regulating decidualization and inflammation-related gene networks, with relevance to endometrial pathologies including endometrial cancer. This model serves as a powerful tool to study estrogen signaling in endometrial stromal cell biology and related pathologies.

Humans↗

PubMed2026

Multi-Omics Landscape of Paraspinal Muscles in Spinal Muscular Atrophy With Scoliosis.

Most spinal muscular atrophy (SMA) patients develop severe scoliosis by late adolescence. Given that the paraspinal muscles-particularly the multifidus-are indispensable for maintaining spinal stability, their site-specific multi-omics characteristics in SMA remain insufficiently defined. Herein, integrated multi-omics sequencing was performed on bilateral multifidus samples from SMA patients and surgical controls. We identified 5219 differentially expressed genes, 1063 differentially expressed proteins and 370 differential metabolites between the control and SMA, showing significant enrichment in glucose and amino acid metabolism pathways, specifically key steps of glycolysis/gluconeogenesis. Key enzymes in the glycolytic process such as PFKM, ENO3 and PKM1 were markedly downregulated. Notably, a comparative analysis of the bilateral paraspinal muscles in SMA revealed asymmetrical metabolic signatures in carbohydrate and amino acid processing between the concave and convex sides. Key regulatory enzymes exhibited significant differential expression: PYGL, a central driver of starch and sucrose metabolism; creatine kinase, involved in arginine and proline metabolism; and PGAM2, a key mediator of glycine, serine, and threonine metabolism. These metabolic signatures indicate a complex metabolic reprogramming in the multifidus, where asymmetric disparities point to the influence of mechanical loading, while systemic dysregulation aligns with the effects of SMN depletion.

Humans↗

PubMed2026

Methylation-Associated Differentiation Features Define Biological and Prognostic Heterogeneity in CMS4 Colorectal Cancer.

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell-cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC.

Humans↗

PubMed2026

Preliminary Exploration on Melatonin-Mediated Protective Effects in Intracranial Aneurysms: Transcriptomic, Proteomic, and Metabolomic Profiling of Cerebral Vascular Tissues Combined with in vivo Animal Experiments.

BACKGROUND: Intracranial aneurysm (IA) is a life-threatening cerebrovascular disease with unclear molecular mechanisms and limited drug treatment. Our previous research has shown that melatonin (MLT) has potential protective effects in IA, but its mechanism remains unclear. The purpose of this study is to explore the pathological mechanism of IA and the therapeutic mechanism of MLT by integrating transcriptomic, proteomic and metabolomic analyses. METHODS: In this study, mouse models of IA were successfully established by combining elastase injection with angiotensin II infusion. C57BL/6 mice were divided into control, IA model, IA model+MLT, and IA model+nimodipine groups. The pathological conditions were evaluated by hematoxylin-eosin (HE) staining, TUNEL staining, and scanning electron microscopy. Transcriptomic (n=3 for each group), proteomic (n=3 for each group), and metabolomic (n=6 for each group) analyses were performed based on cerebral vascular tissue samples. The screening thresholds for differentially expressed genes and differentially expressed proteins were P <0.05 and fold change >1.5 and fold change <0.667. The screening criteria for differential metabolites were variable importance for the projection (VIP)> 1.0, fold change >1.2 and fold change <0.833, and P <0.05. RESULTS: MLT alleviated brain tissue damage, vascular endothelial damage, structural disruption, and apoptosis in IA mice. Transcriptomic, proteomic and metabolomic analyses identified numerous differential molecules. Functional annotation revealed that these molecules may be involved in biological pathways and processes such as immune inflammation, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress and metabolic pathways, thereby regulating the occurrence and development of IA or mediating the therapeutic effects of MLT. Furthermore, transcriptomic and proteomic analyses also suggest that there may be extensive post-transcriptional, translational and post-translational regulatory events in the progression of IA and the therapeutic effects of MLT. Integrated transcriptomic and proteomic analyses suggest that Npy may be a key molecule in regulating IA progression and mediating MLT therapeutic effects, and its potential value is further supported by our immunohistochemical validation results. CONCLUSION: Multi-omics integrative analysis preliminarily revealed that the potential mechanisms of MLT may involve the regulation of inflammatory response, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress, metabolic pathways, and post-transcriptional/translational regulation.

Animals↗

PubMed2026

Beyond ion channel dysfunction: Integration of the transcriptome and proteome from patient-specific re-engineered cardiac cells, and population-level QT genome-wide association study reveals broad cellular dysfunction.

BACKGROUND: Congenital long QT syndrome (LQTS) is a cardiac channelopathy with increased risk of cardiac-triggered syncope/seizures, sudden cardiac arrest, and sudden cardiac death. OBJECTIVE: This study aimed to describe the transcriptomic and proteomic profiles in patient-derived inducible pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of the 3 canonical genotypes of congenital LQTS: LQT1, LQT2, and LQT3 and integrate these omics-level findings with each other and with population/clinical level QT-genome-wide association study (GWAS) data. METHODS: LQT1, LQT2, LQT3 and respective isogenic control iPSC-CMs were cultured, and RNA and protein samples were collected. RNA sequencing and mass spectrometry-enabled proteomic analysis was performed. PrediXcan analysis was performed using QT GWAS summary statistics and transcriptome expression data. Differential gene and protein expression and ingenuity pathway analysis (IPA) was performed comparing each LQT genotype with its respective isogenic control. RESULTS: 1645 differentially expressed genes (DEGs) were identified; 13 were altered in all 3 LQTS genotypes. IPA analysis of DEGs revealed 301 altered pathways; 47 were altered in all LQTS genotypes. Proteomic analysis identified 2561 differentially expressed proteins (DEPs); 30 were altered in all 3 genotypes. IPA analysis of DEPs identified 646 altered pathways. 306 genes/proteins were identified as significantly altered in both the transcriptome and proteome; pathway analysis of these 301 genes identified 201 altered pathways. 7 pathways were altered in all 3 LQTS genotypes in both the transcriptome and proteome. Integration of the population-level PrediXcan results and the cardiomyocyte-derived omics results identified multiple shared pathways. CONCLUSION: Multi-omics analysis of LQTS and integration of omics results with QT GWAS data reveals that primary LQTS-causative ion channel defects precipitate secondary alterations in a wide range of cellular pathways. Our findings suggest more broad molecular level changes throughout the cell. This study lays the foundation for further exploration of broad cellular changes resulting from ion channel disturbances and how they contribute to disease mechanism.

Humans↗

PubMed2026

Chromosome engineering to correct a complex rearrangement on Chromosome 8 reveals the effects of 8p syndrome on gene expression and neural differentiation.

Chromosomal rearrangements on the short arm of Chromosome 8 cause 8p syndrome, a rare developmental disorder characterized by neurodevelopmental delays, epilepsy, and cardiac abnormalities. Although significant progress has been made in managing the symptoms of 8p syndrome and other conditions caused by large-scale chromosomal aneuploidies, no therapeutic approach has yet been demonstrated to target the underlying disease-causing chromosome. Here, we establish a two-step approach to eliminate the abnormal copy of Chromosome 8 and restore euploidy in cells derived from an individual with a complex rearrangement of Chromosome 8p. Transcriptomic analysis revealed 361 differentially expressed genes between the proband and the euploid revertant, highlighting genes both within and outside the 8p region that may contribute to 8p syndrome pathology. Furthermore, we demonstrate that the proband exhibits a significant defect in neural differentiation that could be partially rescued by treatment with small-molecule inhibitors of cell death. Our work demonstrates the feasibility of using chromosome engineering to correct complex aneuploidies in vitro and establishes a platform to further dissect the pathophysiology of 8p syndrome and other conditions caused by chromosomal rearrangements.

Humans↗

PubMed1978

Differential expression of the gene for the large subunit of ribulose bisphosphate carboxylase in maize leaf cell types.

Mesophyll cells and bundle sheath cells, the dimorphic photosynthetic cell types in the C4 plant Zea mays, differ in protein composition. In particular, the large subunit of the chloroplast enzyme ribulose-1,5-bisphosphate carbocylase (EC 4.1.1.39) is found entirely or almost exclusively in bundle sheath cells. The DNA sequence coding for this polypeptide is contained in the chloroplast DNA of both mesophyll cells and bundle sheath cells. RNA complementary to this coding sequence has been detected in RNA from bundle sheath cells, but is almost or entirely absent from mesophyll cells. Similarly, translatable mRNA for this polypeptide has been detected in RNA from bundle sheath cells, but not from mesophyll cells. Portions of the 4200 base pair maize plastid DNA sequence Bam 9 outside the large subunit gene region appear to be transcribed in mesophyll cells. Thus differential gene expression at the mRNA level has been directly demonstrated to occur in these two cell types.

Carboxy-Lyases↗

PubMed2026

Stratifying lung adenocarcinoma: a novel prognostic model based on mitochondrial outer membrane permeabilization activity.

UNLABELLED: Mitochondrial outer membrane permeabilization (MOMP) is a core apoptotic regulatory event that dictates mitochondrial integrity, where full activation drives cell death and sublethal dysregulation contributes to tumor genomic instability. We used the Cancer Genome Atlas lung adenocarcinoma cohort (TCGA-LUAD) as the training cohort and the Gene Expression Omnibus dataset GSE42127 as the validation cohort to identify prognostic genes related to MOMP activity in lung adenocarcinoma (LUAD) and to evaluate their potential biological significance. By intersecting MOMP-related genes with differentially expressed genes, combined with survival analysis, Mendelian randomization analysis, and 101 machine-learning algorithm combinations, seven prognostic genes, namely BIRC5, PSMD11, TNFRSF13C, YWHAZ, YWHAG, CYCS, and LTB, were identified. Next, an optimal prognostic model was constructed based on the gradient boosting machine (GBM) algorithm. Based on the risk score, LUAD patients were stratified into high- and low-risk groups, and patients in the high-risk group exhibited poorer overall survival in both the training and validation cohorts. Furthermore, a nomogram integrating the risk score and clinicopathological factors was developed and showed favorable predictive performance for 1-, 3-, and 5-year survival. Meanwhile, functional and immune analyses revealed that the high-risk group was enriched in DNA replication-related pathways and demonstrated a higher tumor mutation burden (TMB). Correlation analysis indicated that TNFRSF13C was positively correlated with activated B cells, whereas BIRC5 was negatively correlated with eosinophils, suggesting that MOMP-related genes might be involved in remodeling the immune microenvironment of LUAD. Drug sensitivity analysis showed differences in predicted half-maximal inhibitory concentration (IC50) values between the risk groups, suggesting the potential value of this model in assisting therapeutic stratification. Single-cell RNA sequencing (scRNA-seq) further identified T lymphocytes as a key cell type, with numerous prognostic genes exhibiting differential expression in T cells or dynamic changes during differentiation. We suggest that the MOMP-related signature established in this study may provide a reference for prognostic stratification in LUAD and offers candidate prognostic genes for subsequent experimental and clinical validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13205-026-05058-6.

Lung adenocarcinoma↗

PubMed2026

Transcriptomic and metabolomic analyses revealed the action mechanism of nesfatin-1 gene on glucolipid metabolism during early development stage of largemouth bass.

Nesfatin-1 has biological roles including the suppression of food intake and the regulation of glucose and lipid metabolism. However, the information available regarding nesfatin-1 in the glycolipid metabolism in the early development stage of fish is still limited. In order to investigate the role of the nesfatin-1 gene in the early development stage of the largemouth bass (Micropterus salmoides), the nesfatin-1 gene was knocked down using siRNA interference technology. Then, we evaluated its mRNA expression levels, transcriptomes and metabolomes. The mRNA expression levels of nesfatin-1 gene were appreciably decreased at 48 h, 72 h and 96 h after injection of nesfatin-1 siRNA in the early development stage. The omics results revealed that knockdown of the nesfatin-1 gene induced 1833 differentially expressed genes (DEGs) and 2370 differentially expressed metabolites (DEMs). Bioinformatic analysis enriched the most affected molecular pathways (sphingolipid metabolism, fatty acid elongation, amino sugar and nucleotide sugar metabolism and biosynthesis of unsaturated fatty acids) and metabolic pathways (biosynthesis of unsaturated fatty acids, sphingolipid metabolism and amino sugar and nucleotide sugar metabolism) in early development stage of largemouth bass. In amino sugar and nucleotide sugar metabolism, increased expression levels of genes such as chic, chs1, and gck genes, alongside decreased expression levels of the chia.1 gene, resulted in significantly elevated concentrations of N-Acetyl-D-glucosamine, β-d-fructose 6-phosphate, β-d-Fructose, D-mannose 6-phosphate, d-glucose, d-glucose 1-phosphate, UDP-glucose, and UDP-glucuronate, whilst the concentration of UDP-N-acetyl-α-D-glucosamine was markedly reduced. Therefore, the nesfatin-1 gene may influence the early development stage of largemouth bass by affecting signaling pathways associated with glycolipid metabolism. Our findings further expand the understanding of molecular mechanisms of the nesfatin-1 gene, and provide further theoretical support for the initial breeding and feed adaptation of largemouth bass.

Animals↗

PubMed2025

Host-Associated Genetic Differentiation in the Face of Ongoing Gene Flow: Ecological Speciation in a Pathogenic Parasite of Freshwater Fish.

Adaptive evolution in response to varying environments, leading to population divergence, is among the most intriguing processes of speciation. However, the extent to which these adaptive processes effectively drive population divergence amidst ongoing gene flow remains controversial. Our study addresses this by analyzing population genetic structure, gene flow, and genomic divergence between lineages of a tapeworm parasite (Ligula intestinalis) isolated from sympatric fish hosts. This parasite, which must overcome host immunological defenses for successful infection, significantly impacts host health. Utilizing genome-wide Single Nucleotide Polymorphisms (SNPs) and transcriptome data, we investigated whether host species impose distinct selection pressures on parasite populations. Genetic clustering analyses revealed clear divergence, with parasites from bream (Abramis brama) forming a distinct genetic cluster separate from those infecting roach (Rutilus rutilus), rudd (Scardinius erythrophthalmus), and bleak (Alburnus alburnus). Demographic modeling indicated isolation with continuous gene flow as the most plausible scenario for this divergence. Selection analyses identified 896 SNPs under selection, displaying low to moderate nucleotide diversity and genetic divergence compared with neutral loci. Transcriptome profiling supported these findings, revealing distinct gene expression profiles between parasite populations. Examination of selected SNPs and differentially expressed genes identified candidate genes linked to immune evasion mechanisms, potentially driving ecological speciation. This research highlights the interplay of host specificity, population demography, and disruptive selection in ecological speciation. By dissecting genomic factors, our study improves the understanding of mechanisms facilitating population divergence despite ongoing gene flow.

Animals↗

PubMed2025

Inflammatory pathways and immune dysregulation in pediatric postoperative septic shock: A study integrating transcriptomics, machine learning and molecular docking.

This study elucidates the molecular and immune regulatory mechanisms of pediatric postoperative septic shock. Transcriptomic data were obtained from the Gene Expression Omnibus database. Differentially expressed genes were identified using the limma package, and gene co-expression modules were constructed using Weighted Gene Co-expression Network Analysis. Functional enrichment was performed via gene set enrichment analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. Immune cell infiltration was assessed using ESTIMATE and CIBERSORT. Mendelian randomization was applied to explore causal relationships between gene expression and septic shock. Feature genes were selected using machine learning algorithms, and a diagnostic nomogram model was constructed. Finally, molecular docking analysis was performed to screen and evaluate the binding affinity of traditional Chinese medicine monomers to core target proteins. A total of 1331 differentially expressed genes were identified, and the turquoise module was strongly correlated with septic shock. Enrichment analysis revealed significant activation of IL-6/JAK/STAT3, TNF-α/NF-κB, and PI3K/Akt/mTOR pathways. Immune infiltration analysis indicated suppressed immune scores and imbalances in neutrophils, macrophages, T cells, and B cells. Mendelian randomization confirmed causal associations for 6 genes, including PIM3. The predictive model based on feature genes demonstrated high diagnostic performance. Molecular docking suggested that quercetin and astramembrannin I could stably bind PIM3. This study systematically identified core genes, dysregulated immune pathways, and candidate small-molecule interventions in pediatric septic shock, providing novel insights for early diagnosis and targeted therapy.

Humans↗

PubMed2026

Prognostic model based on calcium-related genes predicts prognosis and reveals the immune landscape of acute myeloid leukemia.

Acute myeloid leukemia (AML) exhibits heterogeneous outcomes and lacks reliable prognostic markers. As a critical regulator of cell fate, the prognostic value of calcium signaling in AML requires investigation. This study aimed to construct a calcium-related gene (CRG)-based prognostic model for AML. Differential analysis on RNA-seq data was conducted for AML from The Cancer Genome Atlas and Gene Expression Omnibus (GEO). Intersecting differentially expressed genes and CRGs yielded AML-associated differentially expressed CRGs (DECRGs). A prognostic model was developed using univariate/multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) and validated in a GEO dataset. Bioinformatics analyses explored the links between risk groups and immune characteristics, genomic mutations, and drug sensitivity. Key genes' effects on cell proliferation, apoptosis, and differentiation were verified in vitro using CCK-8 assay, colony formation assay, and flow cytometry. The 13-DECRG-based model distinguished high- and low-risk patients in both training and validation cohorts, with high-risk patients showing a worse prognosis. The risk score was an independent prognostic factor. Immune analysis revealed a unique immune microenvironment for the high-risk group. CAMK2A overexpression inhibited cell proliferation and colony-forming ability, promoted cell apoptosis, and induced an increased proportion of CD11b- and CD14-positive cells. In vitro experiments indicated CAMK2A-induced suppression of AML cells' malignant phenotype by activating the P53 signaling pathway. An AML CRG-based model with favorable risk stratification performance was constructed. In vitro experiments revealed CAMK2A-induced inhibition of the malignant phenotype via suppressing proliferation, promoting apoptosis, and facilitating myeloid differentiation in AML cells. This study provides novel evidence for understanding CRGs in AML as well as the potential functions of CAMK2A.

Journal Article↗

PubMed2025

DyNDG: Identifying Leukemia-related Genes Based on Time-series Dynamic Network by Integrating Differential Genes.

Leukemia is a malignant disease characterized by progressive accumulation with high morbidity and mortality rates, and investigating its disease genes is crucial for understanding its etiology and pathogenesis. Network propagation methods have emerged and been widely employed in disease gene prediction, but most of them focus on static biological networks, which hinders their applicability and effectiveness in the study of progressive diseases. Moreover, there is currently a lack of special algorithms for the identification of leukemia disease genes. Here, we proposed a novel Dynamic Network-based model integrating Differentially expressed Genes (DyNDG) to identify leukemia-related genes. Initially, we constructed a time-series dynamic network to model the development trajectory of leukemia. Then, we built a background-temporal multilayer network by integrating both the dynamic network and the static background network, which was initialized with differentially expressed genes at each stage. To quantify the associations between genes and leukemia, we extended a random walk process to the background-temporal multilayer network. The results demonstrate that DyNDG achieves superior accuracy compared to several state-of-the-art methods. Moreover, after excluding housekeeping genes, DyNDG yields a set of promising candidate genes associated with leukemia progression or potential biomarkers, indicating the value of dynamic network information in identifying leukemia-related genes. The implementation of DyNDG is available at both https://ngdc.cncb.ac.cn/biocode/tool/BT7617 and https://github.com/CSUBioGroup/DyNDG.

Leukemia↗

PubMed2025

Experimental study on the role and biomarker potential of CX3CR1 in osteoarthritis.

BACKGROUND: Osteoarthritis (OA) is a chronic joint disorder marked by progressive degeneration of articular cartilage and the formation of secondary osteophytes. Despite extensive research, the underlying molecular mechanisms remain poorly understood. This study aimed to identify OA-associated genes and elucidate the molecular pathways implicated, with the goal of discovering reliable diagnostic biomarkers. METHODS: The microarray dataset was retrieved from the Gene Expression Omnibus (GEO) and analyzed using R software to identify the signature gene, CX3CR1. Differentially expressed genes (DEGs) correlated with CX3CR1 were subsequently subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immune infiltration analyses. A ceRNA regulatory network was also constructed. Vali-dation of CX3CR1 expression was conducted through qRT-PCR, Western blotting, and immunohistochemistry. RESULTS: CX3CR1 emerged as a candidate gene significantly associated with OA, exhibiting regulatory roles primarily in lipid metabolism-related and extra-cellular matrix-related biological processes and signaling cascades. The infiltration levels of immune cells, particularly activated mast cells, appeared to modulate OA progression. Both in vitro and in vivo experiments demonstrated elevated CX3CR1 expression in OA tissues relative to controls, with a robust positive correlation observed between CX3CR1 and MMP13 levels. CONCLUSION: CX3CR1 represents a potential biomarker for OA diagnosis and therapeutic targeting, exerting its effects by modulating lipid metabolism, extracellular matrix dynamics, and immune cell infiltration.

CX3C Chemokine Receptor 1↗