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 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.

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.

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 EPEN-21. IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION IN PEDIATRIC EPENDYMOMA REVEALED BY SINGLE-CELL RNA-SEQ

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii311-iii312
Author(s):  
Bernhard Englinger ◽  
Johannes Gojo ◽  
Li Jiang ◽  
Jens M Hübner ◽  
McKenzie L Shaw ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Regulatory Networks ◽  
Target Genes ◽  
Target Identification ◽  
Rna Seq ◽  
Cell Models ◽  
Pediatric Ependymoma ◽  
Glial Fate ◽  
Anatomic Locations

Abstract Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets including IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.

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 Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

2019 ◽  
Author(s):  
Ning Wang ◽  
Andrew E. Teschendorff
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Large Scale ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Dropout Rate ◽  
Rna Seq ◽  
Regulatory Activity

AbstractInferring the activity of transcription factors in single cells is a key task to improve our understanding of development and complex genetic diseases. This task is, however, challenging due to the relatively large dropout rate and noisy nature of single-cell RNA-Seq data. Here we present a novel statistical inference framework called SCIRA (Single Cell Inference of Regulatory Activity), which leverages the power of large-scale bulk RNA-Seq datasets to infer high-quality tissue-specific regulatory networks, from which regulatory activity estimates in single cells can be subsequently obtained. We show that SCIRA can correctly infer regulatory activity of transcription factors affected by high technical dropouts. In particular, SCIRA can improve sensitivity by as much as 70% compared to differential expression analysis and current state-of-the-art methods. Importantly, SCIRA can reveal novel regulators of cell-fate in tissue-development, even for cell-types that only make up 5% of the tissue, and can identify key novel tumor suppressor genes in cancer at single cell resolution. In summary, SCIRA will be an invaluable tool for single-cell studies aiming to accurately map activity patterns of key transcription factors during development, and how these are altered in disease.

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 Unification of Opposites between Two Antioxidant Transcription Factors Nrf1 and Nrf2 in Mediating Distinct Cellular Responses to the Endoplasmic Reticulum Stressor Tunicamycin

Antioxidants ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 4 ◽  
Author(s):  
Yu-ping Zhu ◽  
Ze Zheng ◽  
Shaofan Hu ◽  
Xufang Ru ◽  
Zhuo Fan ◽  
...  
Keyword(s):  
Endoplasmic Reticulum ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Er Stress ◽  
Target Genes ◽  
Cellular Responses ◽  
Water Soluble ◽  
Heme Oxygenase 1 ◽  
Nuclear Factor ◽  
Activating Transcription Factor

The water-soluble Nrf2 (nuclear factor, erythroid 2-like 2, also called Nfe2l2) is accepted as a master regulator of antioxidant responses to cellular stress, and it was also identified as a direct target of the endoplasmic reticulum (ER)-anchored PERK (protein kinase RNA-like endoplasmic reticulum kinase). However, the membrane-bound Nrf1 (nuclear factor, erythroid 2-like 1, also called Nfe2l1) response to ER stress remains elusive. Herein, we report a unity of opposites between these two antioxidant transcription factors, Nrf1 and Nrf2, in coordinating distinct cellular responses to the ER stressor tunicamycin (TU). The TU-inducible transcription of Nrf1 and Nrf2, as well as GCLM (glutamate cysteine ligase modifier subunit) and HO-1 (heme oxygenase 1), was accompanied by activation of ER stress signaling networks. Notably, the unfolded protein response (UPR) mediated by ATF6 (activating transcription factor 6), IRE1 (inositol requiring enzyme 1) and PERK was significantly suppressed by Nrf1α-specific knockout, but hyper-expression of Nrf2 and its target genes GCLM and HO-1 has retained in Nrf1α−/− cells. By contrast, Nrf2−/−ΔTA cells with genomic deletion of its transactivation (TA) domain resulted in significant decreases of GCLM, HO-1 and Nrf1; this was accompanied by partial decreases of IRE1 and ATF6, rather than PERK, but with an increase of ATF4 (activating transcription factor 4). Interestingly, Nrf1 glycosylation and its trans-activity to mediate the transcriptional expression of the 26S proteasomal subunits, were repressed by TU. This inhibitory effect was enhanced by Nrf1α−/− and Nrf2−/−ΔTA, but not by a constitutive activator caNrf2ΔN (that increased abundances of the non-glycosylated and processed Nrf1). Furthermore, caNrf2ΔN also enhanced induction of PERK and IRE1 by TU, but reduced expression of ATF4 and HO-1. Thus, it is inferred that such distinct roles of Nrf1 and Nrf2 are unified to maintain cell homeostasis by a series of coordinated ER-to-nuclear signaling responses to TU. Nrf1α (i.e., a full-length form) acts in a cell-autonomous manner to determine the transcription of most of UPR-target genes, albeit Nrf2 is also partially involved in this process. Consistently, transactivation of ARE (antioxidant response element)-driven BIP (binding immunoglobulin protein)-, PERK- and XBP1 (X-box binding protein 1)-Luc reporter genes was mediated directly by Nrf1 and/or Nrf2. Interestingly, Nrf1α is more potent than Nrf2 at mediating the cytoprotective responses against the cytotoxicity of TU alone or plus tBHQ (tert-butylhydroquinone). This is also further supported by the evidence that the intracellular reactive oxygen species (ROS) levels are increased in Nrf1α−/− cells, but rather are, to our surprise, decreased in Nrf2−/−ΔTA cells.

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

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
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.

scholarly journals Evolutionarily conserved transcription factors drive the oxidative stress response in Drosophila

2020 ◽  
Vol 223 (14) ◽  
pp. jeb221622
Author(s):  
Sarah M. Ryan ◽  
Kaitie Wildman ◽  
Briseida Oceguera-Perez ◽  
Scott Barbee ◽  
Nathan T. Mortimer ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Stress Responses ◽  
Binding Sites ◽  
Regulatory Elements ◽  
Genomic Locus ◽  
Biologically Relevant ◽  
Protein Levels ◽  
Putative Transcription Factor

ABSTRACTAs organisms are constantly exposed to the damaging effects of oxidative stress through both environmental exposure and internal metabolic processes, they have evolved a variety of mechanisms to cope with this stress. One such mechanism is the highly conserved p38 MAPK (p38K) pathway, which is known to be post-translationally activated in response to oxidative stress, resulting in the activation of downstream antioxidant targets. However, little is known about the role of p38K transcriptional regulation in response to oxidative stress. Therefore, we analyzed the p38K gene family across the genus Drosophila to identify conserved regulatory elements. We found that oxidative stress exposure results in increased p38K protein levels in multiple Drosophila species and is associated with increased oxidative stress resistance. We also found that the p38Kb genomic locus includes conserved AP-1 and lola-PT transcription factor consensus binding sites. Accordingly, over-expression of these transcription factors in D. melanogaster is sufficient to induce transcription of p38Kb and enhances resistance to oxidative stress. We further found that the presence of a putative lola-PT binding site in the p38Kb locus of a given species is predictive of the species' survival in response to oxidative stress. Through our comparative genomics approach, we have identified biologically relevant putative transcription factor binding sites that regulate the expression of p38Kb and are associated with resistance to oxidative stress. These findings reveal a novel mode of regulation for p38K genes and suggest that transcription may play as important a role in p38K-mediated stress responses as post-translational modifications.

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