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

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.

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

10.21203/rs.2.16967/v2 ◽

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.

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Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1517140113 ◽

2016 ◽

Vol 113 (13) ◽

pp. E1835-E1843 ◽

Cited By ~ 8

Author(s):

Mina Fazlollahi ◽

Ivor Muroff ◽

Eunjee Lee ◽

Helen C. Causton ◽

Harmen J. Bussemaker

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Target Genes ◽

Regulation Of Gene Expression ◽

Nonsynonymous Mutation ◽

Gene Regulatory ◽

Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

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

10.21203/rs.2.16967/v1 ◽

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.

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Diversity and Versatility in Small RNA-Mediated Regulation in Bacterial Pathogens

Frontiers in Microbiology ◽

10.3389/fmicb.2021.719977 ◽

2021 ◽

Vol 12 ◽

Author(s):

Brice Felden ◽

Yoann Augagneur

Keyword(s):

Gene Expression ◽

High Throughput Screening ◽

Regulatory Networks ◽

Target Genes ◽

Bacterial Pathogens ◽

Regulation Of Gene Expression ◽

Transcriptional Level ◽

Large Set ◽

Bacterial Gene ◽

Bacterial Gene Expression

Bacterial gene expression is under the control of a large set of molecules acting at multiple levels. In addition to the transcription factors (TFs) already known to be involved in global regulation of gene expression, small regulatory RNAs (sRNAs) are emerging as major players in gene regulatory networks, where they allow environmental adaptation and fitness. Developments in high-throughput screening have enabled their detection in the entire bacterial kingdom. These sRNAs influence a plethora of biological processes, including but not limited to outer membrane synthesis, metabolism, TF regulation, transcription termination, virulence, and antibiotic resistance and persistence. Almost always noncoding, they regulate target genes at the post-transcriptional level, usually through base-pair interactions with mRNAs, alone or with the help of dedicated chaperones. There is growing evidence that sRNA-mediated mechanisms of actions are far more diverse than initially thought, and that they go beyond the so-called cis- and trans-encoded classifications. These molecules can be derived and processed from 5' untranslated regions (UTRs), coding or non-coding sequences, and even from 3' UTRs. They usually act within the bacterial cytoplasm, but recent studies showed sRNAs in extracellular vesicles, where they influence host cell interactions. In this review, we highlight the various functions of sRNAs in bacterial pathogens, and focus on the increasing examples of widely diverse regulatory mechanisms that might compel us to reconsider what constitute the sRNA.

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

10.21203/rs.2.16967/v3 ◽

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.

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

10.21203/rs.2.16967/v4 ◽

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.

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YY1 is a cis-regulator in the organoid models of high mammographic density

Bioinformatics ◽

10.1093/bioinformatics/btz812 ◽

2019 ◽

Vol 36 (6) ◽

pp. 1663-1667 ◽

Cited By ~ 1

Author(s):

Qingsu Cheng ◽

Mina Khoshdeli ◽

Bradley S Ferguson ◽

Kosar Jabbari ◽

Chongzhi Zang ◽

...

Keyword(s):

Transcription Factors ◽

Cell Lines ◽

Mammographic Density ◽

Regulatory Networks ◽

Regulation Of Gene Expression ◽

Human Mammary Epithelial Cell ◽

Mammary Epithelial ◽

Supplementary Information ◽

Mrna Levels ◽

High Mammographic Density

Abstract Motivation Our previous study has shown that ERBB2 is overexpressed in the organoid model of MCF10A when the stiffness of the microenvironment is increased to that of high mammographic density (MD). We now aim to identify key transcription factors (TFs) and functional enhancers that regulate processes associated with increased stiffness of the microenvironment in the organoid models of premalignant human mammary cell lines. Results 3D colony organizations and the cis-regulatory networks of two human mammary epithelial cell lines (184A1 and MCF10A) are investigated as a function of the increased stiffness of the microenvironment within the range of MD. The 3D colonies are imaged using confocal microscopy, and the morphometries of colony organizations and heterogeneity are quantified as a function of the stiffness of the microenvironment using BioSig3D. In a surrogate assay, colony organizations are profiled by transcriptomics. Transcriptome data are enriched by correlative analysis with the computed morphometric indices. Next, a subset of enriched data are processed against publicly available ChIP-Seq data using Model-based Analysis of Regulation of Gene Expression to predict regulatory transcription factors. This integrative analysis of morphometric and transcriptomic data predicted YY1 as one of the cis-regulators in both cell lines as a result of the increased stiffness of the microenvironment. Subsequent experiments validated that YY1 is expressed at protein and mRNA levels for MCF10A and 184A1, respectively. Also, there is a causal relationship between activation of YY1 and ERBB2 when YY1 is overexpressed at the protein level in MCF10A. Supplementary information Supplementary data are available at Bioinformatics online.

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The PARP Inhibitor Olaparib Modulates the Transcriptional Regulatory Networks of Long Non-Coding RNAs during Vasculogenic Mimicry

Cells ◽

10.3390/cells9122690 ◽

2020 ◽

Vol 9 (12) ◽

pp. 2690

Author(s):

Mónica Fernández-Cortés ◽

Eduardo Andrés-León ◽

Francisco Javier Oliver

Keyword(s):

Transcription Factors ◽

Binding Sites ◽

Regulatory Networks ◽

Target Genes ◽

Parp Inhibitor ◽

Vasculogenic Mimicry ◽

Transcriptome Profiling ◽

Key Species ◽

Non Coding Rnas ◽

The Impact

In highly metastatic tumors, vasculogenic mimicry (VM) involves the acquisition by tumor cells of endothelial-like traits. Poly-(ADP-ribose) polymerase (PARP) inhibitors are currently used against tumors displaying BRCA1/2-dependent deficient homologous recombination, and they may have antimetastatic activity. Long non-coding RNAs (lncRNAs) are emerging as key species-specific regulators of cellular and disease processes. To evaluate the impact of olaparib treatment in the context of non-coding RNA, we have analyzed the expression of lncRNA after performing unbiased whole-transcriptome profiling of human uveal melanoma cells cultured to form VM. RNAseq revealed that the non-coding transcriptomic landscape differed between olaparib-treated and non-treated cells: olaparib significantly modulated the expression of 20 lncRNAs, 11 lncRNAs being upregulated, and 9 downregulated. We subjected the data to different bioinformatics tools and analysis in public databases. We found that copy-number variation alterations in some olaparib-modulated lncRNAs had a statistically significant correlation with alterations in some key tumor suppressor genes. Furthermore, the lncRNAs that were modulated by olaparib appeared to be regulated by common transcription factors: ETS1 had high-score binding sites in the promoters of all olaparib upregulated lncRNAs, while MZF1, RHOXF1 and NR2C2 had high-score binding sites in the promoters of all olaparib downregulated lncRNAs. Finally, we predicted that olaparib-modulated lncRNAs could further regulate several transcription factors and their subsequent target genes in melanoma, suggesting that olaparib may trigger a major shift in gene expression mediated by the regulation lncRNA. Globally, olaparib changed the lncRNA expression landscape during VM affecting angiogenesis-related genes.

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Expresso: A database and web server for exploring the interaction of transcription factors and their target genes in Arabidopsis thaliana using ChIP-Seq peak data

F1000Research ◽

10.12688/f1000research.10041.1 ◽

2017 ◽

Vol 6 ◽

pp. 372 ◽

Cited By ~ 7

Author(s):

Delasa Aghamirzaie ◽

Karthik Raja Velmurugan ◽

Shuchi Wu ◽

Doaa Altarawy ◽

Lenwood S. Heath ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Chromatin Immunoprecipitation ◽

Target Genes ◽

Regulation Of Gene Expression ◽

Data Sets ◽

Motif Analysis ◽

Chromatin Immunoprecipitation Sequencing

Motivation: The increasing availability of chromatin immunoprecipitation sequencing (ChIP-Seq) data enables us to learn more about the action of transcription factors in the regulation of gene expression. Even though in vivo transcriptional regulation often involves the concerted action of more than one transcription factor, the format of each individual ChIP-Seq dataset usually represents the action of a single transcription factor. Therefore, a relational database in which available ChIP-Seq datasets are curated is essential. Results: We present Expresso (database and webserver) as a tool for the collection and integration of available Arabidopsis ChIP-Seq peak data, which in turn can be linked to a user’s gene expression data. Known target genes of transcription factors were identified by motif analysis of publicly available GEO ChIP-Seq data sets. Expresso currently provides three services: 1) Identification of target genes of a given transcription factor; 2) Identification of transcription factors that regulate a gene of interest; 3) Computation of correlation between the gene expression of transcription factors and their target genes. Availability: Expresso is freely available at http://bioinformatics.cs.vt.edu/expresso/

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FLI1 and FRA1 transcription factors drive the transcriptional regulatory networks characterizing muscle invasive bladder cancer

10.1101/2021.11.22.468946 ◽

2021 ◽

Author(s):

Perihan Yagmur Guneri Sozeri ◽

Gulden Ozden Yilmaz ◽

Asli Kisim ◽

Aleyna Eray ◽

Hamdiye Uzuner ◽

...

Keyword(s):

Bladder Cancer ◽

Transcription Factors ◽

Regulatory Networks ◽

Target Genes ◽

Cell Junction ◽

Transcriptional Regulatory Networks ◽

Histopathological Classification ◽

Knock Down ◽

Muscle Invasive ◽

Regulatory Landscape

Bladder cancer is mostly present in the form of urothelium carcinoma, causing over 150.000 deaths each year. Its histopathological classification as muscle invasive (MIBC) and non-muscle invasive (NMIBC) is the most prominent aspect, affecting the prognosis and progression of this disease. In this study, we defined the active regulatory landscape of MIBC and NMIBC cell lines using H3K27ac-seq and used an integrative data approach to combine our findings with existing data. Our analysis revealed FRA1 and FLI1 as the two critical transcription factors differentially regulating MIBC regulatory landscape. Importantly, we show that FRA1 and FLI1 regulate the genes involved in epithelial cell migration and cell junction organization. Knock-down of FRA1 and FLI1 in MIBC revealed the downregulation of several EMT-related genes such as MAP4K4 and FLOT1. Further, ChIP-SICAP performed for FRA1 and FLI1 enabled us to infer chromatin binding partners of these two transcription factors and link this information with their target genes, providing a comprehensive regulatory circuit for the genes implicated in invasive ability of the bladder cancer cells. Finally, for the first time we show that knock-down of FRA1 and FRA1-FLI1 double knock-down results in significant reduction of invasion capacity of MIBC cells towards muscle microenvironment using IC-CHIP assays. Our results collectively highlight the role of these two transcription factors in invasive characteristics of bladder cancer in selection and design of targeted options for treatment of MIBC.

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