scholarly journals Screening Driving Transcription Factors in the Processing of Gastric Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Guangzhong Xu ◽  
Kai Li ◽  
Nengwei Zhang ◽  
Bin Zhu ◽  
Guosheng Feng
Keyword(s):  
Gastric Cancer ◽  
Transcription Factors ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Regulatory Mechanisms ◽  
Integrated Analysis ◽  
Transcriptional Regulatory

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer.Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed.Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer.Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

Transcriptional regulatory network analysis of developing human erythroid progenitors reveals patterns of coregulation and potential transcriptional regulators

2006 ◽  
Vol 28 (1) ◽  
pp. 114-128 ◽  
Author(s):  
M. A. Keller ◽  
S. Addya ◽  
R. Vadigepalli ◽  
B. Banini ◽  
K. Delgrosso ◽  
...  
Keyword(s):  
Network Analysis ◽  
Blood Cell ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Patterns ◽  
Transcriptional Regulators ◽  
Erythroid Progenitors ◽  
Hematopoietic Stem ◽  
Transcriptional Regulatory

Deciphering the molecular basis for human erythropoiesis should yield information benefiting studies of the hemoglobinopathies and other erythroid disorders. We used an in vitro erythroid differentiation system to study the developing red blood cell transcriptome derived from adult CD34+ hematopoietic progenitor cells. mRNA expression profiling was used to characterize developing erythroid cells at six time points during differentiation ( days 1, 3, 5, 7, 9, and 11). Eleven thousand seven hundred sixty-three genes (20,963 Affymetrix probe sets) were expressed on day 1, and 1,504 genes, represented by 1,953 probe sets, were differentially expressed (DE) with 537 upregulated and 969 downregulated. A subset of the DE genes was validated using real-time RT-PCR. The DE probe sets were subjected to a cluster metric and could be divided into two, three, four, five, or six clusters of genes with different expression patterns in each cluster. Genes in these clusters were examined for shared transcription factor binding sites (TFBS) in their promoters by comparing enrichment of each TFBS relative to a reference set using transcriptional regulatory network analysis. The sets of TFBS enriched in genes up- and downregulated during erythropoiesis were distinct. This analysis identified transcriptional regulators critical to erythroid development, factors recently found to play a role, as well as a new list of potential candidates, including Evi-1, a potential silencer of genes upregulated during erythropoiesis. Thus this transcriptional regulatory network analysis has yielded a focused set of factors and their target genes whose role in differentiation of the hematopoietic stem cell into distinct blood cell lineages can be elucidated.

scholarly journals Identification of a GrgA-Euo-HrcA Transcriptional Regulatory Network in Chlamydia

mSystems ◽  
2021 ◽  
Author(s):  
Wurihan Wurihan ◽  
Yi Zou ◽  
Alec M. Weber ◽  
Korri Weldon ◽  
Yehong Huang ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Bacterial Pathogen ◽  
Developed Countries ◽  
Developmental Cycle ◽  
Content Type ◽  
Sexually Transmitted ◽  
Transcriptional Regulatory ◽  
Preventable Blindness

Chlamydia trachomatis is the most prevalent sexually transmitted bacterial pathogen worldwide and is a leading cause of preventable blindness in underdeveloped areas as well as some developed countries. Chlamydia carries genes that encode a limited number of known transcription factors. While Euo is thought to be critical for early chlamydial development, the functions of GrgA and HrcA in the developmental cycle are unclear.

scholarly journals Functional Modules Analysis and Hub Gene Prognostic Values Evaluation Based on Co-Expression Network in Gastric Cancer

2021 ◽  
Author(s):  
Yujia Liu ◽  
Xiaoping Hu ◽  
Zongfu Pan ◽  
Yuchen Jiang ◽  
Dandan Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Transcriptional Regulatory Network ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Gene ◽  
Transcriptional Regulatory ◽  
Key Nodes

Abstract Background: Gastric cancer is one of the most common fatal disease worldwide, but its mechanism and therapeutic targets are still unclear. In this study, we have analyzed the differences in gene modules and key pathways in gastric cancer patients, then elaborated the mechanism and effective treatment of gastric cancer with microarray data from the gene expression omnibus(GEO) database. Methods: GEO2R tools were used to identify differential expression genes (DEGs), String database was employed to construct a protein-protein interaction (PPI) network. We imported the PPI network into the Cytoscape software to find key nodes, and employed statistical approach of MCODE to cluster genes. After that the ClueGO was used to enrich and annotate the pathways of key modules. To investigate the relationship between the upstream regulator and hub genes, the transcriptional regulatory network was built based on TFCAT database. Results: 63 characteristic genes of gastric cancer are involved in regulation of ECM-receptor interaction, focal adhesion and protein digestion and absorption. SPARC, FN1, BGN and COL1A2 are four key nodes relating to tumor proliferation and metastasis, and their expression were strongly associated with poor survival (p<0.05). 13 transcription factors including PRRX1 have remarkable changes in gastric cancer, which may play a key role in hub gene regulation. Conclusions: The present study defined the gene expression characteristics and transcriptional regulatory network that promote our understanding of the molecular mechanisms underlying the development of gastric cancer, and might provide new insights into targeted therapy and prognostic markers for the personalized treatment of gastric cancer.

scholarly journals Identification of pathogenic genes and transcription factors in respiratory syncytial virus

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lei Li ◽  
Yong An Ni ◽  
Zhenfeng Song ◽  
Zhi Yi ◽  
Fang Wang
Keyword(s):  
Transcription Factors ◽  
Respiratory Syncytial Virus ◽  
Respiratory Infections ◽  
Transcriptional Regulatory Network ◽  
Enrichment Analysis ◽  
Microarray Dataset ◽  
Integrated Analysis ◽  
Pathogenic Genes ◽  
Transcriptional Regulatory ◽  
Syncytial Virus

Abstract Background Respiratory syncytial virus (RSV) is a major cause of acute lower respiratory infections in children, especially bronchiolitis. Our study aimed to identify the key genes and upstream transcription factors in RSV. Methods To screen for RSV pathogenic genes, an integrated analysis was performed using the RSV microarray dataset in GEO. Functional annotation and potential pathways for differentially expressed genes (DEGs) were further explored by GO and KEGG enrichment analysis. We constructed the RSV-specific transcriptional regulatory network to identify key transcription factors for DEGs in RSV. Results From three GEO datasets, we identified 1059 DEGs (493 up-regulated and 566 down-regulated genes, FDR < 0.05 and |Combined.ES| > 0.8) between RSV patients and normal controls. GO and KEGG analysis revealed that ‘response to virus’ (FDR = 7.13E-15), ‘mitochondrion’ (FDR = 1.39E-14) and ‘Asthma’ (FDR = 1.28E-06) were significantly enriched pathways for DEGs. The expression of IFI27, IFI44, IFITM3, FCER1A, and ISG15 were shown to be involved in the pathogenesis of RSV. Conclusions We concluded that IFI27, IFI44, IFITM3, FCER1A, and ISG15 may play a role in RSV. Our finding may contribute to the development of new potential biomarkers, reveal the underlying pathogenesis and also identify novel therapeutic targets for RSV.

scholarly journals Genome-Wide Phylogenetic Analysis, Expression Pattern, and Transcriptional Regulatory Network of the Pig C/EBP Gene Family

2021 ◽  
Vol 17 ◽  
pp. 117693432110413
Author(s):  
Chaoxin Zhang ◽  
Tao Wang ◽  
Tongyan Cui ◽  
Shengwei Liu ◽  
Bing Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Phylogenetic Analysis ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Genome Wide ◽  
A Genome

The CCAAT/enhancer binding protein (C/EBP) transcription factors (TFs) regulate many important biological processes, such as energy metabolism, inflammation, cell proliferation etc. A genome-wide gene identification revealed the presence of a total of 99 C/EBP genes in pig and 19 eukaryote genomes. Phylogenetic analysis showed that all C/EBP TFs were classified into 6 subgroups named C/EBPα, C/EBPβ, C/EBPδ, C/EBPε, C/EBPγ, and C/EBPζ. Gene expression analysis showed that the C/EBPα, C/EBPβ, C/EBPδ, C/EBPγ, and C/EBPζ genes were expressed ubiquitously with inconsistent expression patterns in various pig tissues. Moreover, a pig C/EBP regulatory network was constructed, including C/EBP genes, TFs and miRNAs. A total of 27 feed-forward loop (FFL) motifs were detected in the pig C/EBP regulatory network. Based on the RNA-seq data, gene expression patterns related to FFL sub-network were analyzed in 27 adult pig tissues. Certain FFL motifs may be tissue specific. Functional enrichment analysis indicated that C/EBP and its target genes are involved in many important biological pathways. These results provide valuable information that clarifies the evolutionary relationships of the C/EBP family and contributes to the understanding of the biological function of C/EBP genes.

scholarly journals Genetic and pharmacological inactivation of adenosine A2A receptor reveals an Egr-2-mediated transcriptional regulatory network in the mouse striatum

2005 ◽  
Vol 23 (1) ◽  
pp. 89-102 ◽  
Author(s):  
Liqun Yu ◽  
Peter M. Haverty ◽  
Juliana Mariani ◽  
Yumei Wang ◽  
Hai-Ying Shen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Transcriptional Regulatory Network ◽  
Expression Profiles ◽  
Mrna Level ◽  
Gene Expression Profiles ◽  
Bioinformatics Analyses ◽  
Mouse Striatum ◽  
Transcriptional Regulatory

The adenosine A2A receptor (A2AR) is highly expressed in the striatum, where it modulates motor and emotional behaviors. We used both microarray and bioinformatics analyses to compare gene expression profiles by genetic and pharmacological inactivation of A2AR and inferred an A2AR-controlled transcription network in the mouse striatum. A comparison between vehicle (VEH)-treated A2AR knockout (KO) mice (A2AR KO-VEH) and wild-type (WT) mice (WT-VEH) revealed 36 upregulated genes that were partially mimicked by treatment with SCH-58261 (SCH; an A2AR antagonist) and 54 downregulated genes that were not mimicked by SCH treatment. We validated the A2AR as a specific drug target for SCH by comparing A2AR KO-SCH and A2AR KO-VEH groups. The unique downregulation effect of A2AR KO was confirmed by comparing A2AR KO-SCH with WT-SCH gene groups. The distinct striatal gene expression profiles induced by A2AR KO and SCH should provide clues to the molecular mechanisms underlying the different phenotypes observed after genetic and pharmacological inactivation of A2AR. Furthermore, bioinformatics analysis discovered that Egr-2 binding sites were statistically overrepresented in the proximal promoters of A2AR KO-affected genes relative to the unaffected genes. This finding was further substantiated by the demonstration that the Egr-2 mRNA level increased in the striatum of both A2AR KO and SCH-treated mice and that striatal Egr-2 binding activity in the promoters of two A2AR KO-affected genes was enhanced in A2AR KO mice as assayed by chromatin immunoprecipitation. Taken together, these results strongly support the existence of an Egr-2-directed transcriptional regulatory network controlled by striatal A2ARs.

scholarly journals Spatial organization of the transcriptional regulatory network of Saccharomyces cerevisiae

2019 ◽  
Author(s):  
Dong-Qing Sun ◽  
Liu Tian ◽  
Bin-Guang Ma
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Regulatory Network ◽  
Spatial Organization ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
3D Structure ◽  
Three Dimensional ◽  
3D Genome ◽  
Transcriptional Regulatory ◽  
Four Levels

AbstractTranscriptional regulatory network (TRN) is a directed complex network composed of all regulatory interactions between transcription factors and corresponding target genes. Recently, the three-dimensional (3D) genomics studies have shown that the 3D structure of the genome makes a difference to the regulation of gene transcription, which provides us with a novel perspective. In this study, we constructed the TRN of the budding yeast Saccharomyces cerevisiae and placed it in the context of 3D genome model. We analyzed the spatial organization of the yeast TRN on four levels: global feature, central nodes, hierarchical structure and network motifs. Our results suggested that the TRN of S. cerevisiae presents an optimized structure in space to adapt to functional requirement.

scholarly journals Genome-wide phylogenetic analysis, expression pattern, and transcriptional regulatory network of the pig C/EBP gene family

2020 ◽  
Author(s):  
Chaoxin Zhang ◽  
Tao Wang ◽  
Shengwei Liu ◽  
Bing Zhang ◽  
Xue Li ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Rna Seq ◽  
Group I

Abstract Background: The vertebrate C/EBP transcription factors regulate many important biological processes, such as cell proliferation, differentiation, signal transduction, inflammation, and energy metabolism. The first C/EBP protein was identified in rat liver nuclei. Development of sequencing technology resulted in identification of the C/EBP genes in various species. In this study, a bioinformatics approach was used to determine the distribution of the members of the C/EBP family in vertebrates. A phylogenetic tree was constructed to analyze the C/EBP genes in vertebrates. Based on RNA-seq data, the expression patterns of pig C/EBP members in various tissues were analyzed. In addition, a gene transcription regulatory network was constructed with pig C/EBP members as the core.Results: We identified a total of 92 C/EBP genes in 17 vertebrate genomes. Phylogenetic analysis showed that all C/EBP TFs were classified into two groups; group I contained C/EBPβ TFs, and group II contained the remaining C/EBP TFs. The C/EBPα, C/EBPβ, C/EBPδ, C/EBPγ, and C/EBPζ genes were expressed ubiquitously with inconsistent expression patterns in various tissues. Moreover, a pig C/EBP regulatory network was constructed, including C/EBP genes, TFs, and miRNAs. A total of 39 FFL motifs were detected in the pig C/EBP regulatory network. Based on the RNA-seq data, gene expression patterns related to this FFL sub-network were analyzed in 27 adult Duroc tissues. Certain FFL motifs may be tissue specific. Functional enrichment analysis indicated that C/EBP and its target genes are involved in many important biological pathways. Conclusions: These results provide valuable information that clarifies the evolutionary relationships of the C/EBP family and contributes to the understanding of the biological function of C/EBP genes.

scholarly journals Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chen Su ◽  
Simon Rousseau ◽  
Amin Emad
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Organ Damage ◽  
Host Cells ◽  
Regulatory Mechanisms ◽  
Transcriptional Regulatory ◽  
Transcriptional Regulatory Mechanisms ◽  
The Impact

AbstractIdentification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.

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