Gene Expression Profiling of the Habenula in Rats Exposed to Chronic Restraint Stress.

The aim of the present study was to identify genes, microRNAs (miRNAs/miRs) or pathways associated with the development of pituitary gonadotroph adenomas. The array data of GSE23207, which included 16 samples of multiple endocrine neoplasia-associated rat pituitary homozygous mutations and 5 pituitary tissue samples from healthy rats, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were analyzed prior to functional enrichment analysis and protein-protein interaction (PPI) network construction. miRNAs associated with DEGs were predicted, and an miRNA-target regulatory network was constructed. A total of 187 upregulated and 370 downregulated DEGs were identified in the pituitary gonadotroph adenoma group compared with the healthy (control) group. Cyclin-dependent kinase (Cdk) 1 exhibited the highest degree in the PPI network. The upregulated DEGs were predominately enriched in ‘neuroactive ligand-receptor interaction’ pathway, and downregulated DEGs were mainly enriched in ‘cell cycle’. The DEGs in module were predominately enriched in the ‘cell cycle’, whereas DEGs in module b and c were enriched in ‘neuroactive ligand-receptor interaction’. miR-374, −153, −145 and −33 were identified as important miRNAs in the regulation of the DEGs. Cdk1, cyclin (Ccn) A2, Ccnb1, ‘cell cycle’ and ‘neuroactive ligand-receptor interaction’ pathways may serve important roles in the development of pituitary gonadotroph adenomas; Ccna2 and Ccnb1 may contribute to this development via an effect on the ‘cell cycle’ pathway. Furthermore, miR-374 and −145 may contribute to the development of pituitary gonadotroph adenomas via regulation of the expression of target genes.

Glioblastoma (GBM) is the most common type of malignant tumor of the central nervous system. The prognosis of patients with GBM is very poor, with a survival time of ~15 months. GBM is highly heterogeneous and highly aggressive. Surgical removal of intracranial tumors does provide a good advantage for patients as there is a high rate of recurrence. The understanding of this type of cancer needs to be strengthened, and the aim of the present study was to identify gene signatures present in GBM and uncover their potential mechanisms. The gene expression profiles of GSE15824 and GSE51062 were downloaded from the Gene Expression Omnibus database. Normalization of the data from primary GBM samples and normal samples in the two databases was conducted using R software. Then, joint analysis of the data was performed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Identification of prognostic biomarkers was conducted using UALCAN. In total, 9,341 DEGs were identified in the GBM samples, including 9,175 upregulated genes and 166 downregulated genes. The top 1,000 upregulated DEGs and all of the downregulated DEGs were selected for GO, KEGG and prognostic biomarker analyses. The GO results showed that the upregulated DEGs were significantly enriched in biological processes (BP), including immune response, cell division and cell proliferation, and the downregulated DEGs were also significantly enriched in BP, including cell growth, intracellular signal transduction and signal transduction by protein phosphorylation. KEGG pathway analysis showed that the upregulated DEGs were enriched in circadian entrainment, cytokine-cytokine receptor interaction and maturity onset diabetes of the young, while the downregulated DEGs were enriched in the TGF-β signaling pathway, MAPK signaling pathway and pathways in cancer. All of the downregulated genes and the top 1,000 upregulated genes were selected to establish the PPI network, and the sub-networks revealed that these genes were involved in significant pathways, including olfactory transduction, neuroactive ligand-receptor interaction and viral carcinogenesis. In total, seven genes were identified as good prognostic biomarkers. In conclusion, the identified DEGs and hub genes contribute to the understanding of the molecular mechanisms underlying the development of GBM and they may be used as diagnostic and prognostic biomarkers and molecular targets for the treatment of patients with GBM in the future.

Background:HAR1 is a 118-bp segment that lies in a pair of novel non-coding RNA genes. It shows a dramatic accelerated change with an estimated 18 substitutions in the human lineage since the human–chimpanzee ancestor, compared with the expected 0.27 substitutions based on the slow rate of change in this region in other amniotes. Mutations of HAR1 lead to a different HAR1 secondary structure in humans compared to that in chimpanzees.Methods: We cloned HAR1 into the EF-1α promoter vector to generate transgenic mice. Morris water maze tests and step-down passive avoidance tests were conducted to observe the changes in memory and cognitive abilities of mice. RNA-seq analysis was performed to identify differentially expressed genes (DEGs) between the experimental and control groups. Systematic bioinformatics analysis was used to confirm the pathways and functions that the DEGs were involved in.Results: Memory and cognitive abilities of the transgenic mice were significantly improved. The results of Gene Ontology (GO) analysis showed that Neuron differentiation, Dentate gyrus development, Nervous system development, Cerebral cortex neuron differentiation, Cerebral cortex development, Cerebral cortex development and Neurogenesis are all significant GO terms related to brain development. The DEGs enriched in these terms included Lhx2, Emx2, Foxg1, Nr2e1 and Emx1. All these genes play an important role in regulating the functioning of Cajal–Retzius cells (CRs). The DEGs were also enriched in glutamatergic synapses, synapses, memory, and the positive regulation of long-term synaptic potentiation. In addition, “cellular response to calcium ions” exhibited the second highest rich factor in the GO analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the DEGs showed that the neuroactive ligand–receptor interaction pathway was the most significantly enriched pathway, and DEGs also notably enriched in neuroactive ligand–receptor interaction, axon guidance, and cholinergic synapses.Conclusion:HAR1 overexpression led to improvements in memory and cognitive abilities of the transgenic mice. The possible mechanism for this was that the long non-coding RNA (lncRNA) HAR1A affected brain development by regulating the function of CRs. Moreover, HAR1A may be involved in ligand–receptor interaction, axon guidance, and synapse formation, all of which are important in brain development and evolution. Furthermore, cellular response to calcium may play an important role in those processes.

In order to explore the differentially expressed genes (DEGs) related to the high incidence of sham-chewing behavior in pregnant sows, 50 sows (Large White × Landrace) were used to observe sham-chewing behavior in early, middle and late gestation. And then according to the number of sham-chewing observed, sows were divided into high incidence of sham-chewing (group H) and low incidence of sham-chewing (group L). After weaning, 4 sows were randomly selected from group H and group L, samples of brain were collected after slaughter, and hypothalamus was sequenced with transcriptome. After bioinformatics analysis, the DEGs were analyzed and enriched in GO and KEGG, afterwards the candidate genes were screened. qRT-PCR was used to verify the accuracy of the sequencing data. Hypothalamic transcriptome results showed that compared with group L, 1286 genes were significantly differentially expressed in group H, among which 934 genes were up-regulated and 352 genes were down-regulated. The results of GO enrichment analysis showed that in biological process, cell component and molecular function, the most significant terms of enrichment are trans-synaptic signaling, neuron part and gated channel activity. These terms are strongly related to synaptic plasticity, synaptic transmission, neurodevelopment and neuropsychiatric diseases, FGF12, SNAP25, CAMK1D, SYNDIG1, GABRD, RBFOX1, CRH, HCN1, HCN4, GLRA3, GRIN2A, ANXA2, MBP and NTF4 genes with high fold change and more in-depth functional research were selected for sham-chewing and depressive emotion-related genes. KEGG enrichment analysis results indicated that differential expressed genes were significantly enriched in 29 pathways, such as neuroactive ligand-receptor interaction, cAMP and Ras-MAPK signaling pathway. In conclusion, the results of hypothalamic transcriptome indicate that there is a molecular genetic basis for depression-like symptoms in group H, the 14 DEGs screened above might be candidate genes involved in high incidence of sham-chewing and depression-like emotion.

Stress causes extensive changes in hippocampal genomic expression, leading to changes in hippocampal structure and function. The dynamic changes in hippocampal gene expression caused by stress of different durations are still unknown. mRNA sequencing was used to analyze the hippocampal transcriptome of rats subjected to chronic unpredictable mild stress (CUMS) of different durations. Compared with the control, 501, 442 and 235 differentially expressed genes (DEGs) were detected in the hippocampus of rats subjected to CUMS for 3 days and 2 and 6 weeks, respectively. Gene Ontology (GO) analysis was used to determine the potential mechanism underlying the dynamic harmful effects of stress on the hippocampus; Certain GO terms of the down-regulated DEGs in CUMS (3 days) rats were also found in the up-regulated DEGs in CUMS (6 weeks) rats. These results showed opposing regulation patterns of DEGs between CUMS at 3 days and 6 weeks, which suggested a functional change from adaptation to damage in during the early and late stages of chronic stress. GO analysis for upregulated genes in rats subjected to CUMS for 3 days and 2 weeks suggested significant changes in ‘extracellular matrix’ and ‘wound healing’. Upregulated genes in rats subjected to CUMS for 2 weeks were involved in changes associated with visual function. GO analysis of DEGs in rats subjected to CUMS for 6 weeks revealed increased expression of genes associated with ‘apoptotic process’ and ‘aging’ and decreased expression of those associated with inhibition of cell proliferation and cell structure. These results suggest that the early and middle stages of chronic stress primarily promote adaptive regulation and damage repair in the organism, while the late stage of chronic stress leads to damage in the hippocampus.

The aim of the present study was to identify the common molecular mechanisms of multiple glioma subtypes, including astrocytoma, glioblastoma and oligodendroglioma, in addition to the specific mechanisms of different types. The gene expression profile set GSE4290 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) from three types of glioma, relative to non-tumor tissue, were calculated by the t-test method with a linear regression model. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs was performed. GeneVenn online analysis software was used for the comparison of the DEGs between subtypes. A total of 795 DEGs, including 619 up and 176 downregulated DEGs were screened from the astrocytoma expression profiles; these were enriched in the KEGG pathways of ‘neuroactive ligand-receptor interaction’ (upregulated) and ‘Wnt signaling pathway’ (downregulated). Protein-protein interaction networks for astrocytoma, glioblastoma and oligodendroglioma were constructed with 1,617, 7,027 and 1,172 pairs, respectively. A total of 595 common DEGs were obtained between the three subtypes, which were enriched in pathways associated with neural signaling. Glioblastoma is a subtype of astrocytoma; there were 195 DEGs common between these subtypes that were not also associated with oligodendroglioma. DEGs unique to astrocytoma, glioblastoma and oligodendroglioma were associated with the development of the nervous system, the cell cycle and cell matrix components, respectively. The screened DEG p53 gene is likely to be critical for glioma development, including via the Wnt and p53 signaling pathways. Brain-derived neurotrophic factor and cyclin-dependent kinase 1 genes were also likely to be important in the mechanism of glioma development, and were associated with the cell cycle and p53 signaling pathways. Immune system-associated and cell matrix component pathways may be unique signaling pathways associated with astrocytoma and oligodendroglioma, respectively.

To identify genes involving in the pathogenesis of polycystic ovary syndrome (PCOS). In this study, the comprehensive analysis of GSE8157 was downloaded. Overlapping genes of differentially expressed genes (DEGs) were identified, and enrichment analysis for these genes was performed. A modular network of differentially expressed genes was constructed by weighted gene co-expression network analyses (WGCNA), and a total of 322 differentially expressed genes in 5 stable modules were screened. The correlations of genes of the stable modules in BioGRID 3.4, STRING 10.5, HPRD9 databases were screened, and the interaction network of 104 DEGs was constructed. In addition, some genes and the key words were searched in CTD. A total of 596 differentially expressed genes were screened, including 379 genes that were up-regulated in case group and down-regulated in control group and treat group, and 217 genes that were down-regulated in case group and up-regulated in control group and treat group. The differentially expressed genes were enriched in PPAR signaling pathway, Neuroactive ligand-receptor interaction, cAMP signaling pathway, of which pathways were involved in the cancer development. Finally, 7 important target genes were identified, such as APOC3 was interacted with pioglitazone, ADCY2 involved in cAMP signaling pathway, and the genes (C3AR1, HRH2, GRIA1, MLNR and TAAR2) involved in neuroactive ligand-receptor interaction. In addition, the important target genes were significantly differential expression. These results implied that the 7 important target genes were played an important role in the development and progression of PCOS. Our study implied that genes had played a key role in the development and progression of PCOS, the results showed that microarray can be use as a method for the discovery of new biomarkers and therapeutic targets for PCOS.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

This study aims to investigate the effect of maternal nicotine exposure on the gene expression profiles in the liver of offspring mice. Pregnant mice were subcutaneously injected with either saline vehicle or nicotine twice a day on gestational days 11-21. Total RNA from the liver samples which collected from the offspring mice of postnatal day 7 and 21 was subjected to RNA sequencing. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis were conducted to identify the functions of differentially expressed genes (DEGs). Four genes were selected for further validation by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A total of 448 DEGs and 186 DEGs were identified on postnatal day 7 and 21, respectively. GO analysis revealed that the DEGs on postnatal day 7 mainly participated in the biological functions of cell growth and proliferation, and the DEGs on postnatal day 21 mainly participated in ion transport/activity. KEGG enrichment analysis showed that the DEGs on postnatal day 7 were mainly enriched in the cell cycle, cytokine-cytokine receptor interactions, hypertrophic cardiomyopathy, and the p53 signaling pathway, while the DEGs on postnatal day 21 were mainly enriched in neuroactive ligand-receptor interactions, the calcium signaling pathway, retinol metabolism, and axon guidance. The qRT-PCR results were consistent with the RNA sequencing data. The DEGs may affect the growth of liver in early postnatal period while may affect ion transport/activity in late postnatal period.

BackgroundProstate adenocarcinoma (PRAD) poses a significant global health burden. Apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3C (APOBEC3C) exhibits context-dependent roles in cancer but its function in PRAD remains unclear. This study aims to resolve APOBEC3C’s functional duality in PRAD and identify immune-related hub genes using integrated bioinformatics and experimental validation.MethodsScreening of PRAD differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and CIBERSORT immune infiltration assessment were performed based on The Cancer Genome Atlas (TCGA) database. Second, key genes in DEGs were screened using random forest (RF) analysis, the least absolute shrinkage and selection operator (LASSO) regression model, and the Support Vector Machine-Recursive Feature Elimination (SVM-RFE). The diagnostic value of the characterized core gene was evaluated by receiver operating characteristic (ROC) curve analysis in both TCGA and external Gene Expression Omnibus (GEO)-GSE29079 cohorts. The correlation between the core gene and tumor-infiltrating immune cells was further analyzed. In addition, in vitro PRAD models (PC-3/DU145 cell lines) were established to validate bioinformatics findings through functional assays, including quantitative real-time polymerase chain reaction (qRT-PCR), small interfering RNA (siRNA) knockdown, proliferation/migration tests, and chemokine profiling.ResultsDEG analysis identified 24,208 genes (2,269 up-regulated and 1,966 down-regulated). GO enrichment analysis showed that DEGs were mainly involved in biological processes such as regulation of vascular contraction, maintenance of epithelial homeostasis in the gastrointestinal tract, and intercellular adhesion; the KEGG pathway was enriched in vascular smooth muscle contraction, neuroactive ligand-receptor interactions, and cyclic adenosine monophosphate (cAMP) signaling pathways. Immune infiltration showed distinct distribution of 21 immune cells in PRAD vs. normal tissues (P=0.045). Machine learning (LASSO/RF/SVM-RFE) identified APOBEC3C as a core gene with high diagnostic accuracy [TCGA area under the curve (AUC) =0.859; GEO AUC =0.835]. Further analysis showed that APOBEC3C expression was significantly positively correlated with anti-tumor immune cells (activated dendritic cells: r=0.45, P=0.008; resting memory CD4+ T cells: r=0.38, P=0.015). The qRT-PCR results showed that APOBEC3C was expressed at significantly lower mRNA levels in PRAD cell lines (PC-3: 0.32±0.05-fold, P=0.003; DU145: 0.28±0.04-fold, P=0.001) than in normal prostate epithelial cells (RWPE-1). Functional validation confirmed that siRNA-mediated APOBEC3C knockdown (>75% efficiency) promoted malignant phenotypes: proliferation increased 1.8-fold (P<0.001) and migration accelerated 2.1-fold (P<0.001). Crucially, knockdown suppressed T-cell-recruiting chemokines C-X-C motif chemokine ligands 9 (CXCL9) (62% reduction) and C-X-C motif chemokine ligands 10 (CXCL10) (60% reduction) in PRAD cells (P<0.001).ConclusionsThis study revealed the regulatory role of APOBEC3C as an oncogene in PRAD progression, suggesting that it may become a potential molecular marker for PRAD diagnosis and targeted therapy and providing new ideas for clinical intervention.

Different combinations of high-frequency rTMS and cognitive training improve the cognitive function of cerebral ischemic rats

To explore the molecular mechanisms of diabetic nephropathy (DN) progression and provide the theoretical basis for treating DN, GSE1009 microarray data were downloaded from Gene Expression Omnibus database. Microarray data were obtained from glomeruli isolated from normal kidneys (n=3) and kidneys from patients with DN (n=3). We first screened the differentially expressed genes (DEGs) in kidneys by the Linear Models for Microarray Data package in R. Then the function of DEGs in DN was explored through Gene Ontology (GO) and KEGG pathway enrichment analyses. Critical DEGs for DN progression were investigated by constructing PPI network and mining significant modules. Afterwards, enriched protein domains of modules were analyzed by Interpro and DAVID. At last, the regulatory miRNAs for DEGs were calculated by WebGestalt, and DEGs-miRNAs network was visualized with Cytoscape. A total of 666 DEGs including 384 up- and 282 down-regulated genes were screened out. The up-regulated DEGs were significantly enriched in plasma membrane and signal transmission, and mainly participated in pathways of cytokine-cytokine receptor and neuroactive ligand-receptor interaction. The down-regulated DEGs significantly enriched in extracellular region and cytoskeletal protein binding, and mainly participated in ECM-receptor interaction and dilated cardiomyopathy. 2 PPI networks were constructed with confidence score>0.4. One significant module obtained from PPI network for up-regulated DEGs mainly enriched in protein domain of rhodopsin-like G protein-coupled receptors. The down-regulated DEGs were mainly regulated by 10 miRNAs clusters. Together, we constructed a comprehensive molecular network for DN progression and miR-1 and miR-25 might be theoretical targets for DN.

BackgroundAll birds reproduce via internal fertilization, but only ~3% of male birds possess the external genitalia that allows for intromission. Waterfowl (e.g., duck and goose) are representatives of them, and the external genitalia development of male geese is directly related to mating ability. Notably, some male geese show abnormal external genitalia development during ontogenesis. However, until now little is known about the molecular mechanisms of the external genitalia development in goose. In the present study, comparative transcriptomic analyses were performed on the hypothalamus, pituitary gland, testis, and external genitalia isolated from the 245-day-old male Tianfu meat geese showing normal (NEGG, n = 3) and abnormal (AEGG, n = 3) external genitals in order to provide a better understanding of the mechanisms controlling the development of the external genitalia in aquatic bird species.ResultsThere were 107, 284, 2192, and 1005 differentially expressed genes (DEGs) identified in the hypothalamus, pituitary gland, testis and external genitalia between NEGG and AEGG. Functional enrichment analysis indicated that the DEGs identified in the hypothalamus were mainly enriched in the ECM-receptor interaction pathway. The ECM-receptor interaction, focal adhesion, and neuroactive ligand-receptor interaction pathways were significantly enriched by the DEGs in the pituitary gland. In the testis, the DEGs were enriched in the neuroactive ligand-receptor interaction, cell cycle, oocyte meiosis, and purine metabolism. In the external genitalia, the DEGs were enriched in the metabolic, neuroactive ligand-receptor interaction, and WNT signaling pathways. Furthermore, through integrated analysis of protein-protein interaction (PPI) network and co-expression network, fifteen genes involved in the neuroactive ligand-receptor interaction and WNT signaling pathways were identified, including KNG1, LPAR2, LPAR3, NPY, PLCB1, AVPR1B, GHSR, GRM3, HTR5A, FSHB, FSHR, WNT11, WNT5A, WIF1, and WNT7B, which could play crucial roles in the development of goose external genitalia.ConclusionsThis study is the first systematically comparing the hypothalamus, pituitary gland, testis, and external genitalia transcriptomes of male geese exhibiting normal and abnormal external genitals. Both bioinformatic analysis and validation experiments indicated that the neuroactive ligand-receptor interaction pathway could regulate the WNT signaling pathway through PLCB1 to control male goose external genitalia development.

Transcriptomic analysis of the thyroid and ovarian stroma reveals key pathways and potential candidate genes associated with egg production in ducks

Colorectal cancer (CRC) is one of the most common malignant tumors. The aim of the present study was to identify key genes and pathways to improve the understanding of the mechanism of CRC. GSE87211, including 203 CRC samples and 160 control samples, was screened to identify differentially expressed genes (DEGs). In total, 853 DEGs were obtained, including 363 upregulated genes and 490 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs were performed to obtain enrichment datasets. GO analysis showed that DEGs were significantly enriched in the extracellular region, cell-cell signaling, hormone activity, and cytokine activity. KEGG pathway analysis revealed that the DEGs were mainly enriched in the cytokine-cytokine receptor interaction, drug metabolism, androgen and estrogen metabolism, and neuroactive ligand-receptor interaction. The Protein-Protein Interaction (PPI) network of DEGs was constructed by using Search Tool for the Retrieval of Interacting Genes (STRING). The app MCODE plugged in Cytoscape was used to explore the key modules involved in disease development. 43 key genes involved in the top two modules were identified. Six hub genes (CXCL2, CXCL3, PTGDR2, GRP, CXCL11, and AGTR1) were statistically associated with patient overall survival or disease-free survival. The functions of six hub genes were mainly related to the hormone and chemokine activities. In conclusion, the present study may help understand the molecular mechanisms of CRC development.