Gene Functional Enrichment Analysis Research Articles

Complement C1S is a potential prognostic biomarker and associated with M2 macrophage infiltration in gliomas: From bioinformatics to comprehensive experimental validation

Glioma is the most common malignant tumor of the central nervous system, and the ability of traditional clinical treatment to prolong the survival of glioma patients is limited. A substantial body of evidence underscores the pivotal role of the immune system in eradicating malignant cells and impeding tumor metastasis. Consequently, tumor immunotherapy has become a promising avenue to address the clinical conundrum faced by glioma patients. The complement system is a natural immune system that is an important line of defense in the immune response. C1S plays a key role in activating the classical complement system. Nevertheless, few studies have focused on the role of C1S in glioma tumorigenesis and progression. In this study, we demonstrated that C1S was upregulated in GBM (Grade IV) and low-grade gliomas (LGG, Grade II-III) by combining glioma cohorts from multiple public databases with our internal independent cohorts and that increased C1S expression levels predict a poor prognosis for gliomas. Cox regression analysis identified C1S as an important prognostic indicator for glioma patients. In addition, gene functional enrichment analysis demonstrated that C1S was involved in cellular immunity, T-cell activation, macrophage differentiation, and cell proliferation. Further experiments demonstrated that C1S facilitates tumor cell proliferation, cell migration and intracranial tumor growth in nude mice. More importantly, we evaluated the role of C1S in immune infiltration. These results suggested that C1S was closely related to a variety of immune cell types in glioma, especially M2 macrophages. Our findings were further validated via glioma tissue microarray immunohistochemical analysis and an M2 macrophage infiltration assay. Together, these findings revealed the underlying critical role of C1S in glioma tumorigenesis, progression, and the tumor immune microenvironment, contributing to further understanding of glioma pathogenesis and guiding immunotherapy.

Comparative transcriptome analysis of low- and high-latitude populations of Charybdis japonica under temperature stress

Global climate change has caused rapid temperature changes in marine environments. Understanding how marine organisms respond to temperature changes can help predict their richness of future biodiversity. In this study, we examined the gene expression levels and the difference in the pathways that are responsive to acute temperature stress in low- and high-latitude populations of the shore swimming crab, Charybdis japonica. The two populations of C. japonica were exposed to low- and high-temperature stresses (15°C and 28°C) and used for transcriptome sequencing. Genetic regulatory ability changes were compared to determine the diverse response of the two crab populations to temperature change. The gene expression levels and functional enrichment analysis showed that the low-latitude crab regulated more genes (938) that were mainly enriched in DNA replication and metabolic pathways, whereas the high-latitude crab regulated less genes (309) that were mainly enriched in genetic information processing at low-temperature stress. Furthermore, the low-latitude crab regulated less genes (33) that were mainly enriched in genetic information processing, whereas the high-latitude crab regulated more genes (280) that were mainly enriched in signal transduction and cellular process at high-temperature stress. These results implied that the low-latitude population was more resilient to high-temperature stress, while the high-latitude population was more resilient to low-temperature stress. This study enhances our understanding of how different geographic C. japonica populations respond to varying temperature environments in their living zone, which could be helpful for predicting future biodiversity trends of intertidal crustaceans under global climate change.

Genetic polymorphism involved in major depressive disorder: a systemic review and meta-analysis

Background and objectiveGenetic polymorphism studies in families and twins indicated the heritability of depression. However, the association between genes with genetic polymorphism and depression provides various findings and remains unclear. Therefore, we conducted a systematic review and meta-analysis to determine the genes with their polymorphism associated with the symptomatic depression known as major depressive disorder (MDD).Materials and methodsPubMed and Scopus were searched for relevant studies published before May 22, 2023 (1968–2023), and 62 were selected for this review. The study’s bias risk was investigated using the Newcastle–Ottawa scale. Gene functional enrichment analysis was investigated for molecular function (MF) and biological process (BP) and pathways. A meta-analysis of the studied genes that were replicative in the same single nucleotide polymorphism was conducted using a random-effect model.ResultsThe 49 genes involved in MDD were studied and engaged in several pathways, such as tryptophan metabolism or dopaminergic and serotonergic synapses. Based on gene overlapping in MF and BP, 13 genes with polymorphisms were identified as related to MDD. Most of them were only studied once. Solute carrier family 6 member 4 (SLC6A4) overlapping between MF and BP and brain-derived neurotrophic factor (BDNF) as unique to BP were replicative studied and used in the meta-analysis. The polymorphism of SLC6A4 SS and LS genotypes increased the occurrence of MDD development but not significantly [odd ratio (OR) = 1.39; 95% confidence interval (CI) = 0.87–2.22; P = 0.16 and OR = 1.13; 95% CI = 0.84–1.53; P = 0.42, respectively]. A similar result was observed for BDNF rs6265 GG (OR = 1.26; 95% CI = 0.78–2.06; P = 0.35) and BDNF rs6265 AA genotypes (OR = 1.12; 95% CI = 0.77–1.64; P = 0.56). These studies indicated low bias and significant heterogeneity.ConclusionAt least 13 studied genes with polymorphisms were involved in MDD development according to MF and BP, but not significantly. These results suggest that MDD development risk factors might require genetic and other factors for interaction and induction.

Identifying critical modules and biomarkers of intervertebral disc degeneration by using weighted gene co-expression network.

Intervertebral disc degeneration (IVDD) is an age-related orthopedic degenerative disease characterized by recurrent episodes of lower back pain, the pathogenesis of which is not fully understood. This study aimed to identify key biomarkers of IVDD and its causes. We acquired three gene expression profiles from the Gene Expression Omnibus (GEO) database, GSE56081, GSE124272, and GSE153761, and used limma fast differential analysis to identify differentially expressed genes (DEGs) between normal and IVDD samples after removing batch effects. We applied weighted gene co-expression network (WGCNA) to identify the key modular genes in GSE124272 and intersected these with DEGs. Next, A protein-protein interaction network (PPI) was constructed, and Cytoscape was used to identify the Top 10 hub genes. Functional enrichment analyses were performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Three key genes were validated using Western Blot (WB) and qRT-PCR. Additionally, we predicted miRNAs involved in hub gene co-regulation and analyzed miRNA microarray data from GSE116726 to identify four differentially expressed miRNAs. We identified 10 hub genes using bioinformatics analysis, gene function enrichment analysis revealed that they were primarily enriched in pathways, such as the TNF signaling pathway. We chose JUNB, SOCS3, and CEBPB as hub genes and used WB and qRT-PCR to confirm their expression. All three genes were overexpressed in the IVDD model group compared to the control group. Furthermore, we identified four miRNAs involved in the co-regulation of the hub genes using miRNet prediction: mir-191-5p, mir-20a-5p, mir-155-5p, and mir-124-3p. Using limma difference analysis, we discovered that mir-191-5p, mir-20a-5p, and mir-155-5p were all down-regulated and expressed in IVDD samples, but mir-124-3p showed no significant change. JUNB, SOCS3, and CEBPB were identified as key genes in IVDD, regulated by specific miRNAs, providing potential biomarkers for early diagnosis and therapeutic targets.

SH3 domain‑binding glutamic acid‑rich protein‑like 3 is associated with hyperglycemia and a poor outcome in Epstein‑Barr virus‑negative gastric carcinoma.

SH3 domain-binding glutamic acid-rich protein-like 3 (SH3BGRL3) is involved in several human cancers. However, its relationship with gastric cancer (GC) remains elusive. Multiple online bioinformatic tools were used to evaluate the messenger (m)RNA expression levels of SH3BGRL3 in GC using data from The Cancer Genome Atlas and Gene Expression Omnibus databases. Reverse transcription-quantitative PCR and tissue microarray-based immunohistochemistry were performed to assess SH3BGRL3 expression in relation to clinicopathological parameters and outcomes in patients with GC. Significant differentially expressed genes (DEGs) of SH3BGRL3 were enriched and visualized. Furthermore, associations between the expression of SH3BGRL3 and the infiltration of immune cells were explored. SH3BGRL3 exhibited aberrant expression in tumor tissues compared with adjacent normal tissues at the mRNA and protein expression levels, especially in Epstein-Barr virus-negative GC (EBVnGC). Higher SH3BGRL3 expression was significantly associated with increasing tumor-node-metastasis staging, tumor budding, perineural invasion, EGFR expression, and a notably higher preoperative blood glucose concentration in clinical specimens. Multivariate analysis revealed that higher SH3BGRL3 expression was an independent adverse prognostic factor for the overall survival of patients with EBVnGC (hazard ratio, 1.666; P=0.018). Furthermore, the stratified analysis revealed that the SH3BGRL3 phenotype could help to refine prognosis in patients. The C-index of the nomogram was 0.740 when combining SH3BGRL3 with other clinicopathological parameters, which indicated a good model for clinical follow-up decisions. Gene functional enrichment analysis also revealed that the DEGs of SH3BGRL3 were mainly enriched in regulating ATP metabolism, ATP synthesis, oxidative phosphorylation and the electron transport chain in GC. Moreover, a higher SH3BGRL3 expression was significantly positively correlated with the infiltrating macrophages in GC. In conclusion, SH3BGRL3 is upregulated in GC, particularly in EBVnGC. Higher SH3BGRL3 expression is closely associated with hyperglycemia and poor outcomes in patients with EBVnGC, suggesting its potential as a biomarker and prognostic predictor.

Identification and Verification of Key Genes in Colorectal Cancer Liver Metastases Through Analysis of Single-Cell Sequencing Data and TCGA Data

BackgroundColorectal cancer (CRC) is highly prevalent worldwide, with more patients experiencing colorectal cancer liver metastases (CRLM). This study aimed to identify key genes in CRLM through single-cell sequencing data reanalysis and experimental validation.MethodsThe study analyzed single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional enrichment analysis. The Cancer Genome Atlas (TCGA) data enabled bulk-RNA expression and survival prognosis analysis. Real-time polymerase chain reaction (qPCR) detected mRNA expression, whereas Western blot determined protein levels. Cell function experiments assessed SPARC’s impact on CRC cell behavior.ResultsCluster analysis showed 23 classes among 17 CRLM samples, representing six cell types. A GO and KEGG analysis identified interleukin-1 beta (IL1B), CD2 molecule (CD2), and C-X-C motif chemokine ligand 8 (CXCL8) as significant prognostic factors in CRC. Secreted protein acidic and cysteine rich (SPARC) was one of the top differentially expressed genes (DEGs) in tissue stem cells, confirmed in primary and metastatic lesions. Metastatic lesions showed higher expression of SPARC and CRC stem cell marker leucine-rich repeat containing G protein-coupled receptor 5 (LGR5), which was significantly correlated positively with LGR5 expression. Knockdown of SPARC reduced CRC cell sphere- and colony-formation, invasion, and migration abilities. Overexpression of SPARC significantly increased the malignancy of CRC cells.ConclusionsSeveral key genes were identified in the process of CRLM. In CRLM samples and those corresponding to CRC stem cells, SPARC was significantly upregulated. In the therapy of CRLM, SPARC might be a potential target.

Preliminary identification of somatic mutations profile in ACL injury

Anterior cruciate ligament (ACL) injury is a common orthopedic disease with a high incidence, long recovery time, and often requiring surgical treatment. However, the susceptibility factors for ACL injury are currently unclear, and there is a lack of analysis on the differences in the ligament itself. Previous studies have focused on germline mutations, with less research on somatic mutations. To determine the role of somatic mutations in ACL injuries, we recruited seven patients between the ages of 20 and 39 years diagnosed with ACL injuries, collected their peripheral blood, injured ligament ends, and healthy ligament ends tissues, and performed exome sequencing with gene function enrichment analysis. We detected multiple gene mutations and gene deletions, which were only present in some of the samples. Unfortunately, it was not possible to determine whether these somatic mutations are related to ligament structure or function, or are involved in ACL injury. However, this study provides valuable clues for future in-depth research.

Exploring circulating MiRNA signature for osteosarcoma detection: Bioinformatics-based analyzing and validation

Early detection followed by efficient treatment still remain a considerable challenge for osteosarcoma (OS), indicating the importance of emerging innovative diagnostic methods. Circulating miRNAs offer a promising and non-invasive approach to assess the OS molecular landscapes. This study utilized RNAseq data from OS plasma miRNA expression profiles (PRJEB30542) and PCR Array data (GSE65071) from GEO and ENA databases. In total, 43 miRNAs demonstrated significant differential expression in OS samples of training dataset. A diagnostic model, including hsa-miR-30a-5p, hsa-miR-556–3p, hsa-miR-200a-3p, and hsa-miR-582–5p was identified through multivariate logistic regression analysis and demonstrated significant efficacy in differentiating OS patients from healthy controls in the validation group (AUC: 0.917, sensitivity: 1, specificity: 0.85). The result of target gene prediction and functional enrichment analyses revealed significant associations with terms such as epithelial morphogenesis, P53 and Wnt signaling pathways, and neoplasm metastasis. Further bioinformatics-based evaluations showed that the down-regulation of these miRNAs significantly correlates with poor prognosis and lower survival rate in OS patients and propose their tumor suppressor function in pathogenesis of OS. Furthermore, the study developed a miRNA-mRNA subnetwork that connects these miRNAs to the P53 and Wnt signaling pathways, which are critical pathways with oncogenic effects on OS progression. This comprehensive approach not only presents a promising diagnostic model but also proposes potential molecular markers for OS early diagnosis, making prognosis, and targeted therapy. The identified miRNA-mRNA functional axis holds promise as a valuable resource for further research in understanding OS pathogenesis and establishing therapeutic modalities.

Construction of store-operated calcium entry-related gene signature for predicting prognosis and indicates immune microenvironment infiltration in stomach adenocarcinomas

Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.

Low-dose 60Co-γ-ray irradiation promotes the growth of cucumber seedlings by inducing CsSAUR37 expression.

Cucumber (Cucumis sativus L.) is a major vegetable crop grown globally, with a cultivation history of more than 3000years. The limited genetic diversity, low rate of intraspecific variation, and extended periods of traditional breeding have resulted in slow progress in their genetic research and the development of new varieties. Gamma (γ)-ray irradiation potentially accelerates the breeding progress; however, the biological and molecular effects of γ-ray irradiation on cucumbers are unknown. Exposing cucumber seeds to 0, 50, 100, 150, 200, and 250Gy doses of 60Co-γ-ray irradiation, this study aimed to investigate the resulting phenotype and physiological characteristics of seedling treatment to determine the optimal irradiation dose. The results showed that low irradiation doses (50-100Gy) enhanced root growth, hypocotyl elongation, and lateral root numbers, promoting seedling growth. However, high irradiation doses (150-250Gy) significantly inhibited seed germination and growth, decreasing the survival rate of seedlings. More than 100Gy irradiation significantly decreased the total chlorophyll content while increasing the malondialdehyde (MDA) and H2O2 content in cucumber. Transcriptome sequencing analysis at 0, 50, 100, 150, 200, and 250Gy doses showed that gene expression significantly differed between low and high irradiation doses. Gene Ontology enrichment and functional pathway enrichment analyses revealed that the auxin response pathway played a crucial role in seedling growth under low irradiation doses. Further, gene function analysis revealed that small auxin up-regulated gene CsSAUR37 was a key gene that was overexpressed in response to low irradiation doses, promoting primary root elongation and enhancing lateral root numbers by regulating the expression of protein phosphatase 2Cs (PP2Cs) and auxin synthesis genes.

Combined Analysis of Human and Experimental Rat Samples Identified Biomarkers for Ischemic Stroke.

The genetic transcription profile and underlying molecular mechanisms of ischemic stroke (IS) remain elusive. To address this issue, four mRNA and one miRNA expression profile of rats with middle cerebral artery occlusion (MCAO) were acquired from the Gene Expression Omnibus (GEO) database. A total of 780 differentially expressed genes (DEGs) and 56 miRNAs (DEMs) were screened. Gene set and functional enrichment analysis revealed that a substantial number of immune-inflammation-related pathways were abnormally activated in IS. Through weighted gene co-expression network analysis, the turquoise module was identified as meaningful. By taking the intersection of the turquoise module genes, DEM-target genes, and all DEGs, 354 genes were subsequently obtained as key IS-related genes. Among them, six characteristic genes were identified using the least absolute shrinkage and selection operator. After validation with three external datasets, transforming growth factor beta 1 (Tgfb1) was selected as the hub gene. This finding was further confirmed by gene expression pattern analysis in both the MCAO model rats and clinical IS patients. Moreover, the expression of the hub genes exhibited a negative correlation with the modified Rankin scale score (P < 0.05). Collectively, these results expand our knowledge of the genetic profile and molecular mechanisms involved in IS and suggest that the Tgfb1 gene is a potential biomarker of this disease.

Integrated transcriptome and 1H NMR-based metabolome to explore the potential mechanism of Spodoptera litura in response to flupyrimin

Flupyrimin (FLP) is a novel class of insecticide acting on insect nicotinic acetylcholine receptor (nAChR) and shows robust insecticidal activity. However, the toxicological effects of FLP on Spodoptera litura have not been revealed. In this study, the results showed that the larval survival rate decreased significantly with increasing concentration of FLP. The hematoxylin-eosin (HE) staining showed that FLP exposure damages the structure of the larval midgut. Additionally, FLP treatments significantly increased the activities of detoxification (GST and CarE) and digestive (α-Amylase and Trypsin) enzymes and reduced lipase activity. Transcriptome sequencing identified 855, 1493 and 735 differentially expressed genes (DEGs) at 12 h, 24 h and 48 h after exposure to 3 mM FLP, respectively. Gene function enrichment analysis revealed that DEGs were mainly related to fatty acid metabolic, protein processing in the endoplasmic reticulum and drug metabolism-cytochrome P450. The DEGs associated with food digestion and detoxification was validated by reverse-transcription quantitative PCR (RT-qPCR). Furthermore, a total of fifteen energy-related metabolites were identified, among which thirteen metabolisms were significantly influenced after FLP treatment based on 1H NMR-based metabolome analysis, including tyrosine, glucose, trehalose, malate, threonine, proline, glycine, lysine, citrate, alanine, lactate, valine, and leucine. Taken together, these results provide useful information for revealing the toxicological effect of FLP against S. litura.

Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points.

Alzheimer's disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-β plaque and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. While neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cellcell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and TF activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.

Casein kinase 1α mediates estradiol secretion via CYP19A1 expression in mouse ovarian granulosa cells

BackgroundCasein kinase 1α (CK1α), expressed in both ovarian germ and somatic cells, is involved in the initial meiosis and primordial follicle formation of mouse oocytes. Using in vitro and in vivo experiments in this study, we explored the function and mechanism of CK1α in estrogen synthesis in mice ovarian granulosa cells.MethodsA CK1α knockout (cKO) mouse model, targeted specifically to ovarian granulosa cells (GCs), was employed to establish the influence of CK1α on in vivo estrogen synthesis. The influence of CK1α deficiency on GCs was determined in vivo and in vitro by immunofluorescence analysis and Western blot assay. Transcriptome profiling, differentially expressed genes and gene functional enrichment analyses, and computation protein–protein docking, were further employed to assess the CK1α pathway. Furthermore, wild-type female mice were treated with the CK1α antagonist D4476 to elucidate the CK1α's role in estrogen regulation.ResultsOvarian GCs CK1α deficiency impaired fertility and superovulation of female mice; also, the average litter size and the estradiol (E2) level in the serum of cKO female mice were decreased by 57.3% and 87.4% vs. control mice, respectively.This deficiency disrupted the estrous cycle and enhanced the apoptosis in the GCs. We observed that CK1α mediated the secretion of estradiol in mouse ovarian GCs via the cytochrome P450 subfamily 19 member 1 (CYP19A1).ConclusionsThese findings improve the existing understanding of the regulation mechanism of female reproduction and estrogen synthesis.Trial registrationNot applicable.

Identification of candidate genes and chemicals associated with osteonecrosis of femoral head by multiomics studies and chemical-gene interaction analysis.

In-depth understanding of osteonecrosis of femoral head (ONFH) has revealed that degeneration of the hip cartilage plays a crucial role in ONFH progression. However, the underlying molecular mechanisms and susceptibility to environmental factors in hip cartilage that contribute to ONFH progression remain elusive. We conducted a multiomics study and chemical-gene interaction analysis of hip cartilage in ONFH. The differentially expressed genes (DEGs) involved in ONFH progression were identified in paired hip cartilage samples from 36 patients by combining genome-wide DNA methylation profiling, gene expression profiling, and quantitative proteomics. Gene functional enrichment and pathway analyses were performed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Functional links between proteins were discovered through protein-protein interaction (PPI) networks. The ONFH-associated chemicals were identified by integrating the DEGs with the chemical-gene interaction sets in the Comparative Toxicogenomics Database (CTD). Finally, the DEGs, including MMP13 and CHI3L1, were validated via quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC). Twenty-two DEGs were identified across all three omics levels in ONFH cartilage, 16 of which were upregulated and six of which were downregulated. The collagen-containing extracellular matrix (ECM), ECM structural constituents, response to amino acids, the relaxin signaling pathway, and protein digestion and absorption were found to be primarily involved in cartilage degeneration in ONFH. Moreover, ten major ONFH-associated chemicals were identified, including, benzo(a)pyrene, valproic acid, and bisphenol A. Overall, our study identified several candidate genes, pathways, and chemicals associated with cartilage degeneration in ONFH, providing novel clues into the etiology and biological processes of ONFH progression.

Comparative Analysis of Transcriptomes Reveals Pathways and Verifies Candidate Genes for Clubroot Resistance in Brassica oleracea.

Clubroot, a soil-borne disease caused by Plasmodiophora brassicae, is one of the most destructive diseases of Brassica oleracea all over the world. However, the mechanism of clubroot resistance remains unclear. In this research, transcriptome sequencing was conducted on root samples from both resistant (R) and susceptible (S) B. oleracea plants infected by P. brassicae. Then the comparative analysis was carried out between the R and S samples at different time points during the infection stages to reveal clubroot resistance related pathways and candidate genes. Compared with 0 days after inoculation, a total of 4991 differential expressed genes were detected from the S pool, while only 2133 were found from the R pool. Gene function enrichment analysis found that the effector-triggered immunity played a major role in the R pool, while the pathogen-associated molecular pattern triggered immune response was stronger in the S pool. Simultaneously, candidate genes were identified through weighted gene co-expression network analysis, with Bol010786 (CNGC13) and Bol017921 (SD2-5) showing potential for conferring resistance to clubroot. The findings of this research provide valuable insights into the molecular mechanisms underlying clubroot resistance and present new avenues for further research aimed at enhancing the clubroot resistance of B. oleracea through breeding.

MiRNA expression signatures induced by pasteurella multocida infection in goats lung

MicroRNAs (miRNAs) are important regulators of gene expression and are involved in bacterial pathogenesis and host–pathogen interactions. In this study, we investigated the function of miRNAs in the regulation of host responses to Pasteurella multocida infection. Using next-generation sequencing, we analyzed miRNA expression pattern and identified differentially expressed miRNAs in Pasteurella multocida-infected goat lungs. In addition, we investigated the function of differentially expressed miRNAs andtheir targeted signaling pathways in bacterial infection processes. The results showed that Pasteurella multocida infection led to 69 significantly differentially expressed miRNAs, including 28 known annotated miRNAs with miR-497-3p showing the most significant difference. Gene target prediction and functional enrichment analyses showed that the target genes were mainly involved in cell proliferation, regulation of the cellular metabolic process, positive regulation of cellular process, cellular senescence, PI3K-Akt signaling pathway, FoxO signaling pathway and infection-related pathways. In conclusion, these data provide a new perspective on the roles of miRNAs in Pasteurella multocida infection.

Expression characteristics of TBC1D4 activating protein molecule and identification of key module genes for preventing thyroid cancer progression

Endocrine tumors like thyroid carcinoma are becoming more frequent. No clinically informative predictors were found. Thus, effective gene networks and representative biomarkers can illuminate thyroid cancer prevention molecular mechanisms. TBC1D4 is an activating protein molecule that plays an important role in regulating cell metabolism and signal transduction. The aim of this study was to investigate the expression characteristics of TBC1D4 activating protein molecules and identify key module genes that prevent thyroid cancer progression. GSE65144 data were downloaded from GEO. “limma” in R found DEGs with a false discovery rate < 0.05 and a log2 fold change <1. WGCNA builds gene co-expression networks, screens key modules, and filters hub genes. Overlapping genes become hub genes. Hub genes underwent GO and KEGG pathway enrichment analysis. We used Lasso to extract hub gene expression results' distinctive genes. Key genes. GEPIA database determined expression and survival impact. A total of 3220 DEGs. Thyroid cancer was mostly associated with darkred, darkturquoise, and green modules. Venn screened 639 hub genes. Cytokine-cytokine receptor interaction was the primary KEGG enrichment. Hub genes were 14. Finally, ARHGAP6, TBC1D4, and TC2N were important genes. Through gene screening and functional enrichment analysis, we identified a group of genes related to TBC1D4 activating protein and constructed the corresponding protein interaction network.

The role of NPC2 gene in glioma was investigated based on bioinformatics analysis

Glioblastoma (GBM) is one of the most malignant primary brain tumors in adults. The NPC2 gene (Niemann–Pick type C intracellular cholesterol transporter 2) is a protein-coding gene with a lipid recognition domain. The NPC2 gene was found to be significantly increased in gliomas (LGG and GBM), and it is now thought to be a risk factor. COX analysis demonstrated that NPC2 was a significant risk factor for glioma. Functional enrichment analysis of genes that were differentially expressed between high and low expression groups revealed that genes were primarily enriched in the regulation of trans-synaptic signaling, Retrograde endocannabinoid signaling and other pathways. According to the findings of the immunoinfiltration investigation, the NPC2 gene and macrophage, DC, etc. have a strong positive association. In addition, patients with high NPC2 expression had higher levels of immune cell expression. Medication sensitivity research revealed that NPC2’s differential expression had some bearing on patients’ medication sensitivity. There was a strong correlation between the prognosis of glioma patients and the gene sets NUDT19 and NUME. In brief, the NPC2 gene was identified to be a possible biomarker of glioma, and preliminary analysis was done on the role of the NPC2 gene in immunological microenvironment of glioma.

Identification of HTRA1, DPT and MXRA5 as potential biomarkers associated with osteoarthritis progression and immune infiltration

BackgroundOur study aimed to identify potential specific biomarkers for osteoarthritis (OA) and assess their relationship with immune infiltration.MethodsWe utilized data from GSE117999, GSE51588, and GSE57218 as training sets, while GSE114007 served as a validation set, all obtained from the GEO database. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed to identify hub modules and potential functions of genes. We subsequently screened for potential OA biomarkers within the differentially expressed genes (DEGs) of the hub module using machine learning methods. The diagnostic accuracy of the candidate genes was validated. Additionally, single gene analysis and ssGSEA was performed. Then, we explored the relationship between biomarkers and immune cells. Lastly, we employed RT-PCR to validate our results.ResultsWGCNA results suggested that the blue module was the most associated with OA and was functionally associated with extracellular matrix (ECM)-related terms. Our analysis identified ALB, HTRA1, DPT, MXRA5, CILP, MPO, and PLAT as potential biomarkers. Notably, HTRA1, DPT, and MXRA5 consistently exhibited increased expression in OA across both training and validation cohorts, demonstrating robust diagnostic potential. The ssGSEA results revealed that abnormal infiltration of DCs, NK cells, Tfh, Th2, and Treg cells might contribute to OA progression. HTRA1, DPT, and MXRA5 showed significant correlation with immune cell infiltration. The RT-PCR results also confirmed these findings.ConclusionsHTRA1, DPT, and MXRA5 are promising biomarkers for OA. Their overexpression strongly correlates with OA progression and immune cell infiltration.