The effect of altering the promoter region of ubiquitous chromatin-opening element (UCOE) and matrix attachment region (MAR) on stable and efficient expression of genes was investigated. Four different promoters were tested, namely, oct4 containing an enhancer region, sox2 having a CpG island, nanog having no regulatory elements, and CMV containing a CpG island and an enhancer region. Eight reporter plasmids were constructed: pOCT4-UCOE, pOCT4-MAR, pSOX2-UCOE, pSOX2-MAR, pNANOG-UCOE, pNANOG-MAR, pCMV-UCOE, and pCMV-MAR. Stable and efficient expression was observed when UCOE combined with the oct4 promoter, whereas the sox2 was the best promoter suited for MAR. Comparison of the stable clones of oct4-UCOE and sox2-MAR showed that UCOE-regulated expression is more stable and efficient than MAR-regulated expression. When CpG island-containing promoter is linked with UCOE, stable and efficient expression could be observed. These data suggest that an enhancer region in the promoter leads to high, yet unstable expression when combined with UCOE, whereas CpG islands stabilize expression. In conclusion, UCOE and MAR interact with regulatory elements on the promoter by altering the chromatin open state and chromatin loop to regulate gene expression.
Chromatin/genetics* ; CpG Islands/genetics* ; Gene Expression ; Gene Expression Regulation ; Promoter Regions, Genetic/genetics*

OBJECTIVETo study the differently expressed genes of oral squamous cell carcinoma (OSCC) tissue.

METHODSGene expression datasets related to oral squamous cell carcinoma in the gene expression omnibus (gene expression omnibus, GEO) repository were retrieved. Datasets were merged by normalization.Significantly expressed genes were obtained by statistical methods, and genes' functions, interactions, signaling pathways were analyzed accordingly.

RESULTSIn GEO, there were 1 125 records related to OSCC, and four of them were selected and merged to a super array data, within the super array data, 233 genes were significantly expressed (P < 0.05) , and the top 100 significantly expressed genes were selected as signature genes.Signature genes were more related to cell surface or cell-cell interactive activities. Clusters of interactive signature genes and the related signaling pathways were related with mitosis process.

CONCLUSIONSOSCC signature genes and the corresponding signaling pathways will provide not only an important clue for further research of the disease, but also reference for diagnosis and treatment.

OBJECTIVE: To screen differentially expressed gene (DEG) related to myelodysplastic syndrome (MDS) based on Gene Expression Omnibus (GEO) database, and explore the core genes and pathogenesis of MDS by analyzing the biological functions and related signaling pathways of DEG. METHODS: The expression profiles of GSE4619, GSE19429, GSE58831 including MDS patients and normal controls were downloaded from GEO database. The gene expression analysis tool (GEO2R) of GEO database was used to screen DEG according to | log FC (fold change) |≥1 and P<0.01. David online database was used to annotate gene ontology function (GO). Metascape online database was used to enrich and analyze differential genes in Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction network (PPI) was constructed by using STRING database. CytoHubba and Mcode plug-ins of Cytoscape were used to analyze the key gene clusters and hub genes. R language was used to diagnose hub genes and draw the ROC curve. GSEA enrichment analysis was performed on GSE19429 according to the expression of LEF1. RESULTS: A total of 74 co-DEG were identified, including 14 up-regulated genes and 60 down regulated genes. GO enrichment analysis indicated that BP of down regulated genes was mainly enriched in the transcription and regulation of RNA polymerase II promoter, negative regulation of cell proliferation, and immune response. CC of down regulated genes was mainly enriched in the nucleus, transcription factor complexes, and adhesion spots. MF was mainly enriched in protein binding, DNA binding, and β-catenin binding. KEGG pathway was enriched in primary immunodeficiency, Hippo signaling pathway, cAMP signaling pathway, transcriptional mis-regulation in cancer and hematopoietic cell lineage. BP of up-regulated genes was mainly enriched in type I interferon signaling pathway and viral response. CC was mainly enriched in cytoplasm. MF was mainly enriched in RNA binding. Ten hub genes and three important gene clusters were screened by STRING database and Cytoscape software. The functions of the three key gene clusters were closely related to immune regulation. ROC analysis showed that the hub genes had a good diagnostic significance for MDS. GSEA analysis indicated that LEF1 may affect the normal function of hematopoietic stem cells by regulating inflammatory reaction, which further revealed the pathogenesis of MDS. CONCLUSION Bioinformatics can effectively screen the core genes and key signaling pathways of MDS, which provides a new strategy for the diagnosis and treatment of MDS.
Computational Biology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Ontology ; Humans ; Myelodysplastic Syndromes/genetics*

PURPOSE: To identify the potential target genes of blast lung injury (BLI) for the diagnosis and treatment. METHODS: This is an experimental study. The BLI models in rats and goats were established by conducting a fuel-air explosive power test in an unobstructed environment, which was subsequently validated through hematoxylin-eosin staining. Transcriptome sequencing was performed on lung tissues from both goats and rats. Differentially expressed genes were identified using the criteria of q ≤ 0.05 and |log₂ fold change| ≥ 1. Following that, enrichment analyses were conducted for gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathways. The potential target genes were further confirmed through quantitative real-time polymerase chain reaction and enzyme linked immunosorbent assay. RESULTS: Observations through microscopy unveiled the presence of reddish edema fluid, erythrocytes, and instances of focal or patchy bleeding within the alveolar cavity. Transcriptome sequencing analysis identified a total of 83 differentially expressed genes in both rats and goats. Notably, 49 genes exhibited a consistent expression pattern, with 38 genes displaying up-regulation and 11 genes demonstrating down-regulation. Enrichment analysis highlighted the potential involvement of the interleukin-17 signaling pathway and vascular smooth muscle contraction pathway in the underlying mechanism of BLI. Furthermore, the experimental findings in both goats and rats demonstrated a strong association between BLI and several key genes, including anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4, which exhibited up-regulation. CONCLUSIONS Anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4 hold potential as target genes for the prognosis, diagnosis, and treatment of BLI.
Rats ; Animals ; Lung Injury/genetics* ; Goats/genetics* ; Keratin-4 ; Gene Expression Profiling ; Gene Expression

MicroRNA (miRNA) is a class of RNA which has been discovered in recent years and relates with genesis and development of tumors. MiRNA affects the genesis and development of tumors and carries out the function similar to oncogene and antioncogene through regulation of signaling pathway in which target genes involved, thereby the miRNA disregulation plays an important role in oncogenesis. More studies revealed that the miR-17-19 cluster closely correlates with tumorigenesis and has bifunctional effects of oncogene and antioncogene. In this review, the mechanism and function of the miR-17-19 cluster in tumorigenesis are summarized.
Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genes, Tumor Suppressor ; Humans ; MicroRNAs ; Neoplasms ; genetics ; Oncogenes ; genetics

In order to enrich the transcriptome data of Fagopyrum dibotrys plants, analyze the genes encoding key enzyme involved in flavonoid biosynthesis pathway, and mine their functional genes, in this study, we performed RNA sequencing analysis for the rhizomes, roots, flowers, leaves and stems of F. dibotrys on the BGISEQ-500 sequencing platform. After de novo assembly of transcripts, a total of 205 619 unigenes were generated and 132 372 unigenes were obtained and annotated into seven public databases, of which, 81 327 unigenes were mapped to the GO database and most of the unigenes were annotated in cellular process, biological regulation, binding and catalytic activity. Besides, 86 922 unigenes were enriched in 136 pathways using KEGG database' and we identified 82 unigenes that encodes key enzymes involved in flavonoid biosynthesis. Comparing rhizome with root, flower, leaf or stem in F. dibotrys, 27 962 co-expressed differentially expressed genes(DEGs) were obtained. Among them, 23 515 DEGs of rhizome tissue-specific were enriched into 132 pathways and 13 unigenes were significantly enriched in biosynthesis of flavone and flavonol. In addition, we also identified 3 427 unigenes encoding 60 transcription factor(TFs) families as well as four unigenes encoding bHLH TFs were enriched in flavonoid biosynthesis. Our results greatly enriched the transcriptome database of plants, provided a reference for the analysis of key enzymes involved in flavonoid biosynthesis in plants, and will facilitate the study of the functions and regulatory mechanisms of key enzymes involved in flavonoid biosynthesis in F. dibotrys at the genetic level.
Biosynthetic Pathways/genetics* ; Fagopyrum ; Flavonoids ; Flowers ; Gene Expression Profiling ; Gene Expression Regulation, Plant ; Humans ; Transcriptome/genetics*

Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb.
Carcinoma, Hepatocellular ; genetics ; Databases, Genetic ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Liver Neoplasms ; genetics

Carcinoma, Hepatocellular ; genetics ; Gene Expression ; Humans ; Liver Neoplasms ; genetics

Cell migration or movement is a highly dynamic cellular process, requiring precise regulation that is essential for a variety of biological processes. microRNAs (miRNAs) are a class of tiny non-coding RNA molecules that function as critical post-transcriptional regulators of gene expression. Emerging evidence demonstrates that miRNAs play important roles in cell migration and directly contribute to extracellular matrix (ECM) remodeling, cell adhesion, and cell signalling that controls cell migration by targeting a large number of protein-coding genes. Accordingly, the dysregulation of these miRNAs has been linked to several migration-related diseases. In this review, we summarize and highlight the recent advances concerning the roles and validated targets of miRNAs in the control of cell movement.
Animals ; Cell Movement ; genetics ; Gene Expression ; Gene Expression Regulation ; Humans ; MicroRNAs ; genetics ; metabolism ; physiology ; RNA ; genetics ; RNA, Untranslated ; genetics

OBJECTIVE: To identify the key genes and explore mechanisms in the development of myelodysplastic syndrome (MDS) by bioinformatics analysis. METHODS: Two cohorts profile datasets of MDS were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed gene (DEG) was screened by GEO2R, functional annotation of DEG was gained from GO database, gene ontology (GO) enrichment analysis was performed via Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and key genes were screened by Matthews correlation coefficient (MCC) based on STRING database. RESULTS: There were 112 DEGs identified, including 85 up-regulated genes and 27 down-regulated genes. GO enrichment analysis showed that biological processes were mainly enriched in immune response, etc, cellular component in cell membrane, etc, and molecular function in protein binding, etc. KEGG signaling pathway analysis showed that main gene enrichment pathways were primary immunodeficiency, hematopoietic cell lineage, B cell receptor signaling pathway, Hippo signaling pathway, and asthma. Three significant modules were screened by Cytoscape software MCODE plug-in, while 10 key node genes (CD19, CD79A, CD79B, EBF1, VPREB1, IRF4, BLNK, RAG1, POU2AF1, IRF8) in protein-protein interaction (PPI) network were screened based on STRING database. CONCLUSION These screened key genes and signaling pathways are helpful to better understand molecular mechanism of MDS, and provide theoretical basis for clinical targeted therapy.
Computational Biology ; Gene Expression ; Gene Expression Profiling ; Humans ; Microarray Analysis ; Myelodysplastic Syndromes/genetics* ; Protein Interaction Maps