No abstract available.
Gene Expression Regulation* ; Oocytes*

This experiment studied the expression pattern of key gene CO in the photoperiod of Chrysanthemum indicum. The CDS sequence of the Ch. indicum CO gene was cloned by RT-PCR. The open reading frame was 1 380 bp in length and encoded 459 amino acids. The bioinformatics analysis results showed that the Ch. indicum CO had higher homology with Ch. lavandulifolium and Artemisia annua,and the CO was more conservative in the same family. The molecular weight of the predicted protein encode by CO is 52. 04 k Da,the p I is 4. 81,the α-helix structure accounted for 17. 65%,the random coil accounted for 76. 69%,the extension chain accounted for 5. 66%,there are no β-fold and signal peptide. The experimental results showed that short-day treatment could increase the expression level of CO gene in Ch. indicum and induce its flowering. The results of qRT-PCR showed that the relative expression of CO gene in different tissues and different treatment periods of Ch. indicum was significantly different. In this paper,we studied the effect of short-day treatment on the expression of key genes in the flowering cycle of Ch. indicum,providing a basis for photoperiod regulation and harvesting period of Ch.indicum.
Chrysanthemum ; Gene Expression Regulation, Plant

The exogenous gene expression and its impacts on the bacterial population are important to study quorum sensing systems and synthetic biology industry. However, the behavior of exogenous protein expressing bacteria remains poorly understood. To find out which factors are playing a critical role in the growth of population and exogenous gene expression, we measured Lux-type receptor-regulated exogenous gene expression under the induction of N-acyl homoserine lactone (N-AHL) signaling molecules and impacts on the bacterial population dynamics after such stimulation. To analyze the cause of fitness burden of bacteria, we set up a hypothetical mathematical model. Previous studies often arrogate this phenomenon to the synthesis cost and the toxicity of N-AHL signaling molecule. However, we suggested another possible cause of the fitness burden.
Bacteria ; Gene Expression ; Gene Expression Regulation, Bacterial ; Quorum Sensing

Natural products (NPs), especially those from traditional herbal medicines, can evidently modulate human gene expression at multiple levels, leading to a wide diversity of bioactivities. Although numerous bio-functions of NPs for human body have been found, there is little understanding about how NPs achieve it, as less attention was drawn to the definite mechnism by which NPs regulate gene expression. Furthermore, based on the rapidly advancing knowledge of mechanisms for gene regulation in recent years, newly-understood mechanisms, such as post-transcriptional regulation, are found to be involved in NP-elicited bio-effects, providing a new perspective on understanding the role of NPs in gene expression. Therefore, in the current review, we summarize the function of NPs in gene expression from the perspectives of transcriptional, post-transcriptional, and post-translational regulation, which will reinforce the understanding of NP-induced effects in gene expression and facilitate the exploration of more NPs with potential therapeutic effects.
Biological Products/pharmacology* ; Gene Expression ; Gene Expression Regulation ; Humans

Different mechanisms, including transcriptional and post transcriptional processes, regulate tissue specific expression of genes. In this study, we report differences in gene/protein compositional features between apoptosis involved genes selectively expressed in human tissues. We found some correlations between codon/amino acid usage and tissue specific expression level of genes. The findings can be significant for understanding the translational selection on these features. The selection may play an important role in the differentiation of human tissues and can be considered for future studies in diagnosis of some diseases such as cancer.
Apoptosis* ; Codon* ; Diagnosis ; Gene Expression Regulation ; Humans

It is becoming increasingly clear that eukaryotic genomes are subjected to higher-order chromatin organization by the CCCTC-binding factor/cohesin complex. Their dynamic interactions in three dimensions within the nucleus regulate gene transcription by changing the chromatin architecture. Such spatial genomic organization is functionally important for the spatial disposition of chromosomes to control cell fate during development and differentiation. Thus, the dysregulation of proper long-range chromatin interactions may influence the development of tumorigenesis and cancer progression.
Carcinogenesis ; Chromatin* ; Gene Expression Regulation ; Genome ; Humans*

Objective: To analyze the expression levels of the F9 gene and F9 protein in hepatocellular carcinoma by combining multiple gene chip data, real-time fluorescence quantitative PCR (RT qPCR), and immunohistochemistry. Additionally, explore their correlation with the occurrence and development of hepatocellular carcinoma, as well as with various clinical indicators and prognosis. Methods: The mRNA microarray dataset from the GEO database was analyzed to identify the F9 gene with significant expression differences associated with hepatocellular carcinoma. Liver cancer and adjacent tissues were collected from 18 cases of hepatocellular carcinoma. RT-qPCR method was used to detect the F9 gene expression level. Immunohistochemistry was used to detect the F9 protein level. Combined with the TCGA database information, the correlation between F9 gene expression level and prognostic and clinicopathological parameters was analyzed. The biological function of F9 co-expressed genes associated with hepatocellular carcinoma was analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Statistical analysis was performed using Graphpad Prism software. Results: Meta-analysis results showed that the expression of the F9 gene was lower in HCC tissues than in non-cancerous tissues. Immunohistochemistry results were basically consistent with those of RT-qPCR. The data obtained from TCGA showed that the F9 gene had lower expression values in stages III-IV, T3-T4, and patients with vascular invasion. A total of 127 genes were selected for bioinformatics analysis as co-expressed genes of F9, which were highly enriched in redox processes and metabolic pathways. Conclusion: This study validates that the F9 gene and F9 protein are lower in HCC. The down-regulation of the F9 gene predicts adverse outcomes, which may provide a new therapeutic target for HCC.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Down-Regulation ; Prognosis ; Gene Expression ; Gene Expression Regulation, Neoplastic

OBJECTIVES: Recently, comparison of drug responses on gene expression has been a major approach to identifying the functional similarity of drugs. Previous studies have mostly focused on a single feature, the expression differences of individual genes. We provide a more robust and accurate method to compare the functional similarity of drugs by diversifying the features of comparison in gene expression and considering the sample dependent variations. METHODS: For differentially expressed gene measurement, we modified the conventional t-test to normalize variations in diverse experimental conditions of individual samples. To extract significant differentially co-expressed gene modules, we searched maximal cliques among the co-expressed gene network. Finally, we calculated a combined similarity score by averaging the two scaled scores from the above two measurements. RESULTS: This method shows significant performance improvement in comparison to other approaches in the test with Connectivity Map data. In the test to find the drugs based on their own expression profiles with leave-one-out cross validation, the proposed method showed an area under the curve (AUC) score of 0.99, which is much higher than scores obtained with previous methods, ranging from 0.71 to 0.93. In the drug networks, we could find well clustered drugs having the same target proteins and novel relations among drugs implying the possibility of drug repurposing. CONCLUSIONS: Inclusion of the features of a co-expressed module provides more implications to infer drug action. We propose that this method be used to find collaborative cellular mechanisms associated with drug action and to simply identify drugs having similar responses.
Biomarkers, Pharmacological ; Drug Repositioning ; Gene Expression Regulation ; Gene Expression* ; Gene Regulatory Networks ; Methods ; Transcriptome*

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*

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.