scholarly journals Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure

2019 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Heart Failure ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptional Profiling ◽  
Normal Heart ◽  
Developmental Progress

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure developmental progress also are largely unclear.Methods: The transcriptional profiling of heart failure was identified from integrated gene expression datasets. The enriched pathways and transcription factors were analyzed using DAVID and GSEA assay. The transcriptional networks were created by Cytoscape.Results: Compared with the normal heart tissues, we found 90 genes were particularly differentially expressed in heart failing tissues, and those genes were associated with multiple metabolism pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in heart failing tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of heart failing tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in heart failing tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were decreased in heart failing tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed the transcription factor MYC and C/EBPβ mediated regulatory networks in heart failing tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the failure developmental progress by literature research. Conclusions: Our results suggested that transcription factor MYC and C/EBPβ played critical roles in heart failure developmental progress. And new heart failure treatments may be developed by targeting MYC and C/EBPβ.

Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on GEO dataset

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptional Profiling ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development. Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using DAVID website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape. Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress. Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

scholarly journals Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on Gene Expression Omnibus datasets

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development. Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using Database for Annotation, Visualization and Integrated Discovery (DAVID) website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape. Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress. Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

scholarly journals Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on Gene Expression Omnibus datasets

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development.Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using Database for Annotation, Visualization and Integrated Discovery (DAVID) website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape.Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress.Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

scholarly journals The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat

2020 ◽  
Vol 10 (10) ◽  
pp. 3675-3686 ◽  
Author(s):  
Sophie A. Harrington ◽  
Anna E. Backhaus ◽  
Ajit Singh ◽  
Keywan Hassani-Pak ◽  
Cristobal Uauy
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Candidate Gene ◽  
Web Application ◽  
Regulatory Networks ◽  
Target Genes ◽  
Gene Prediction ◽  
Relevant Information ◽  
Rna Seq ◽  
Biologically Relevant

Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.

scholarly journals Transcriptome Analysis of Insulin Signaling-Associated Transcription Factors in C. elegans Reveal Their Genome-Wide Target Genes Specificity and Complexity

2021 ◽  
Vol 22 (22) ◽  
pp. 12462
Author(s):  
Neha Kaushik ◽  
Soumya Rastogi ◽  
Sonia Verma ◽  
Deepak Pandey ◽  
Ashutosh Halder ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Large Set ◽  
Sequencing Analysis ◽  
Experimental Conditions ◽  
Functional Annotations ◽  
C Elegans

Insulin/IGF-1-like signaling (IIS) plays a crucial, conserved role in development, growth, reproduction, stress tolerance, and longevity. In Caenorhabditis elegans, the enhanced longevity under reduced insulin signaling (rIIS) is primarily regulated by the transcription factors (TFs) DAF-16/FOXO, SKN-1/Nrf-1, and HSF1/HSF-1. The specific and coordinated regulation of gene expression by these TFs under rIIS has not been comprehensively elucidated. Here, using RNA-sequencing analysis, we report a systematic study of the complexity of TF-dependent target gene interactions during rIIS under analogous genetic and experimental conditions. We found that DAF-16 regulates only a fraction of the C. elegans transcriptome but controls a large set of genes under rIIS; SKN-1 and HSF-1 show the opposite trend. Both of the latter TFs function as activators and repressors to a similar extent, while DAF-16 is predominantly an activator. For expression of the genes commonly regulated by TFs under rIIS conditions, DAF-16 is the principal determining factor, dominating over the other two TFs, irrespective of whether they activate or repress these genes. The functional annotations and regulatory networks presented in this study provide novel insights into the complexity of the gene regulatory networks downstream of the IIS pathway that controls diverse phenotypes, including longevity.

scholarly journals Taiji: System-level identification of key transcription factors reveals transcriptional waves in mouse embryonic development

2019 ◽  
Vol 5 (3) ◽  
pp. eaav3262 ◽  
Author(s):  
Kai Zhang ◽  
Mengchi Wang ◽  
Ying Zhao ◽  
Wei Wang
Keyword(s):  
Transcription Factors ◽  
Embryonic Development ◽  
Regulatory Networks ◽  
Target Genes ◽  
Developmental Stages ◽  
Three Dimensional ◽  
Cell Types ◽  
System Level ◽  
Transcriptional Regulatory Networks ◽  
Developmental Progress

Transcriptional regulation is pivotal to the specification of distinct cell types during embryonic development. However, it still lacks a systematic way to identify key transcription factors (TFs) orchestrating the temporal and tissue specificity of gene expression. Here, we integrated epigenomic and transcriptomic data to reveal key regulators from two cells to postnatal day 0 in mouse embryogenesis. We predicted three-dimensional chromatin interactions in 12 tissues across eight developmental stages, which facilitates linking TFs to their target genes for constructing transcriptional regulatory networks. To identify driver TFs, we developed a new algorithm, dubbed Taiji, to assess the global influence of each TF and systematically uncovered TFs critical for lineage-specific and stage-dependent tissue specification. We have also identified TF combinations that function in spatiotemporal order to form transcriptional waves regulating developmental progress. Furthermore, lacking stage-specific TF combinations suggests a distributed timing strategy to orchestrate the coordination between tissues during embryonic development.

scholarly journals Validation and characterisation of a wheat GENIE3 network using an independent RNA-Seq dataset

2019 ◽  
Author(s):  
Sophie A. Harrington ◽  
Anna E. Backhaus ◽  
Ajit Singh ◽  
Keywan Hassani-Pak ◽  
Cristobal Uauy
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Candidate Gene ◽  
Web Application ◽  
Regulatory Networks ◽  
Target Genes ◽  
De Novo ◽  
Rna Seq ◽  
Expression Levels ◽  
Biologically Relevant

AbstractGene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently, as part of an analysis of the RefSeqv1.0 wheat transcriptome, a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we have used an independent and publicly-available RNA-Seq dataset to validate the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analysed the RNA-Seq data against the RefSeqv1.0 genome and identified a de novo set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the de novo DEGs, more than would be expected for a random transcription factor. Based on high levels of overlap between GENIE3-predicted target genes and the de novo DEGs, we also identified a set of candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and homoeolog expression levels and found that only homoeologous transcription factors are likely to share predicted targets in common. However, homoeologs in dynamic triads, i.e. with higher variation in homoeolog expression levels across tissues, are less likely to share predicted targets than stable triads. This suggests that homoeologs in dynamic triads are more likely to act on distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.

Systematic genetic analysis of transcription factors to map the fission yeast transcription-regulatory network

2013 ◽  
Vol 41 (6) ◽  
pp. 1696-1700 ◽  
Author(s):  
Gordon Chua
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Fission Yeast ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptome Profiling ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory ◽  
Transcription Factor Genes ◽  
Almost All

Mapping transcriptional-regulatory networks requires the identification of target genes, binding specificities and signalling pathways of transcription factors. However, the characterization of each transcription factor sufficiently for deciphering such networks remains laborious. The recent availability of overexpression and deletion strains for almost all of the transcription factor genes in the fission yeast Schizosaccharomyces pombe provides a valuable resource to better investigate transcription factors using systematic genetics. In the present paper, I review and discuss the utility of these strain collections combined with transcriptome profiling and genome-wide chromatin immunoprecipitation to identify the target genes of transcription factors.

scholarly journals Regulatory Network Analysis in Estradiol-Treated Human Endothelial Cells

2021 ◽  
Vol 22 (15) ◽  
pp. 8193
Author(s):  
Daniel Pérez-Cremades ◽  
Ana B. Paes ◽  
Xavier Vidal-Gómez ◽  
Ana Mompeón ◽  
Carlos Hermenegildo ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Regulatory Network ◽  
Mirna Target ◽  
Target Genes ◽  
Functional Characterization ◽  
Human Endothelial Cells ◽  
Mrna Targets ◽  
Canonical Pathways

Background/Aims: Estrogen has been reported to have beneficial effects on vascular biology through direct actions on endothelium. Together with transcription factors, miRNAs are the major drivers of gene expression and signaling networks. The objective of this study was to identify a comprehensive regulatory network (miRNA-transcription factor-downstream genes) that controls the transcriptomic changes observed in endothelial cells exposed to estradiol. Methods: miRNA/mRNA interactions were assembled using our previous microarray data of human umbilical vein endothelial cells (HUVEC) treated with 17β-estradiol (E2) (1 nmol/L, 24 h). miRNA–mRNA pairings and their associated canonical pathways were determined using Ingenuity Pathway Analysis software. Transcription factors were identified among the miRNA-regulated genes. Transcription factor downstream target genes were predicted by consensus transcription factor binding sites in the promoter region of E2-regulated genes by using JASPAR and TRANSFAC tools in Enrichr software. Results: miRNA–target pairings were filtered by using differentially expressed miRNAs and mRNAs characterized by a regulatory relationship according to miRNA target prediction databases. The analysis identified 588 miRNA–target interactions between 102 miRNAs and 588 targets. Specifically, 63 upregulated miRNAs interacted with 295 downregulated targets, while 39 downregulated miRNAs were paired with 293 upregulated mRNA targets. Functional characterization of miRNA/mRNA association analysis highlighted hypoxia signaling, integrin, ephrin receptor signaling and regulation of actin-based motility by Rho among the canonical pathways regulated by E2 in HUVEC. Transcription factors and downstream genes analysis revealed eight networks, including those mediated by JUN and REPIN1, which are associated with cadherin binding and cell adhesion molecule binding pathways. Conclusion: This study identifies regulatory networks obtained by integrative microarray analysis and provides additional insights into the way estradiol could regulate endothelial function in human endothelial cells.

scholarly journals Inhibition of Wnt signaling by ICAT, a novel β-catenin-interacting protein

2000 ◽  
Vol 14 (14) ◽  
pp. 1741-1749 ◽  
Author(s):  
Ken-ichi Tago ◽  
Tsutomu Nakamura ◽  
Michiru Nishita ◽  
Junko Hyodo ◽  
Shin-ichi Nagai ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Transcription Factors ◽  
Embryonic Development ◽  
Wnt Signaling ◽  
Signaling Pathway ◽  
Target Genes ◽  
Wnt Signaling Pathway ◽  
Axis Formation ◽  
Interacting Protein

Wnt signaling has an important role in both embryonic development and tumorigenesis. β-Catenin, a key component of the Wnt signaling pathway, interacts with the TCF/LEF family of transcription factors and activates transcription of Wnt target genes. Here, we identify a novel β-catenin-interacting protein, ICAT, that was found to inhibit the interaction of β-catenin with TCF-4 and represses β-catenin–TCF-4-mediated transactivation. Furthermore, ICAT inhibited Xenopus axis formation by interfering with Wnt signaling. These results suggest that ICAT negatively regulates Wnt signaling via inhibition of the interaction between β-catenin and TCF and is integral in development and cell proliferation.

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