scholarly journals Transcriptomic profile of Pea3 family members reveal regulatory codes for axon outgrowth and neuronal connection specificity

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Başak Kandemir ◽  
Gizem Gulfidan ◽  
Kazim Yalcin Arga ◽  
Bayram Yilmaz ◽  
Isil Aksan Kurnaz
Keyword(s):  
Transcription Factor ◽  
Target Genes ◽  
Neural Circuit ◽  
Molecular Model ◽  
Expression Profiles ◽  
Neuroblastoma Cells ◽  
Branching Morphogenesis ◽  
Subfamily Member ◽  
Circuit Formation ◽  
Cell Cell

Abstract PEA3 transcription factor subfamily is present in a variety of tissues with branching morphogenesis, and play a particularly significant role in neural circuit formation and specificity. Many target genes in axon guidance and cell–cell adhesion pathways have been identified for Pea3 transcription factor (but not for Erm or Er81); however it was not so far clear whether all Pea3 subfamily members regulate same target genes, or whether there are unique targets for each subfamily member that help explain the exclusivity and specificity of these proteins in neuronal circuit formation. In this study, using transcriptomics and qPCR analyses in SH-SY5Y neuroblastoma cells, hypothalamic and hippocampal cell line, we have identified cell type-specific and subfamily member-specific targets for PEA3 transcription factor subfamily. While Pea3 upregulates transcription of Sema3D and represses Sema5B, for example, Erm and Er81 upregulate Sema5A and Er81 regulates Unc5C and Sema4G while repressing EFNB3 in SH-SY5Y neuroblastoma cells. We furthermore present a molecular model of how unique sites within the ETS domain of each family member can help recognize specific target motifs. Such cell-context and member-specific combinatorial expression profiles help identify cell–cell and cell-extracellular matrix communication networks and how they establish specific connections.

scholarly journals Essential Functions of the Transcription Factor Npas4 in Neural Circuit Development, Plasticity, and Diseases

2020 ◽  
Vol 14 ◽  
Author(s):  
Jian Fu ◽  
Ouyang Guo ◽  
Zhihang Zhen ◽  
Junli Zhen
Keyword(s):  
Transcription Factor ◽  
Neural Circuit ◽  
Second Messenger ◽  
Synaptic Activity ◽  
Postsynaptic Potentials ◽  
Calcium Dependent ◽  
Neural Information ◽  
Formation Function ◽  
Second Messenger Pathways ◽  
Circuit Formation

Signaling from the synapse to nucleus is mediated by the integration and propagation of both membrane potential changes (postsynaptic potentials) and intracellular second messenger cascades. The electrical propagation of postsynaptic potentials allows for rapid neural information processing, while propagating second messenger pathways link synaptic activity to the transcription of genes required for neuronal survival and adaptive changes (plasticity) underlying circuit formation and learning. The propagation of activity-induced calcium signals to the cell nucleus is a major synapse-to-nucleus communication pathway. Neuronal PAS domain protein 4 (Npas4) is a recently discovered calcium-dependent transcription factor that regulates the activation of genes involved in the homeostatic regulation of excitatory–inhibitory balance, which is critical for neural circuit formation, function, and ongoing plasticity, as well as for defense against diseases such as epilepsy. Here, we summarize recent findings on the neuroprotective functions of Npas4 and the potential of Npas4 as a therapeutic target for the treatment of acute and chronic diseases of the central nervous system.

scholarly journals Transient cell–cell interactions in neural circuit formation

2009 ◽  
Vol 10 (4) ◽  
pp. 262-271 ◽  
Author(s):  
Daniel L. Chao ◽  
Le Ma ◽  
Kang Shen
Keyword(s):  
Neural Circuit ◽  
Cell Interactions ◽  
Circuit Formation ◽  
Cell Cell

scholarly journals ADAMTS-1: a novel target gene of an estrogen-induced transcription factor, EGR1, critical for embryo implantation in the mouse uterus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mira Park ◽  
So Hee Park ◽  
Hyunsun Park ◽  
Hye-Ryun Kim ◽  
Hyunjung J. Lim ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Target Gene ◽  
Target Genes ◽  
Expression Profiles ◽  
Embryo Implantation ◽  
Uterine Epithelium ◽  
Expression Vectors ◽  
Dependent Manner ◽  
Mouse Uterus ◽  
Novel Target

Abstract Background Recently, we demonstrated that estrogen (E2) induces early growth response 1 (Egr1) to mediate its actions on the uterine epithelium by controlling progesterone receptor signaling for successful embryo implantation. EGR1 is a transcription factor that regulates the spectrum of target genes in many different tissues, including the uterus. E2-induced EGR1 regulates a set of genes involved in epithelial cell remodeling during embryo implantation in the uterus. However, only few target genes of EGR1 in the uterus have been identified. Result The expression of ADAM metallopeptidase with thrombospondin type 1 motif 1 (Adamts-1) was significantly downregulated in the uteri of E2-treated ovariectomized (OVX) Egr1(−/−) mice. Immunostaining of ADAMTS-1 revealed its exclusive expression in the uterine epithelium of OVX wild-type but not Egr1(−/−) mice treated with E2. The expression profiles of Adamts-1 and Egr1 were similar in the uteri of E2-treated OVX mice at various time points tested. Pre-treatment with ICI 182, 780, a nuclear estrogen receptor (ER) antagonist, effectively inhibited the E2-dependent induction of Egr1 and Adamts-1. Pharmacologic inhibition of E2-induced ERK1/2 or p38 phosphorylation interfered with the induction of EGR1 and ADAMTS-1. Furthermore, ADAMTS-1, as well as EGR1, was induced in stroma cells surrounding the implanting blastocyst during embryo implantation. Transient transfection with EGR1 expression vectors significantly induced the expression of ADAMTS-1. Luciferase activity of the Adamts-1 promoter containing EGR1 binding sites (EBSs) was increased by EGR1 in a dose-dependent manner, suggesting functional regulation of Adamts-1 transcription by EGR1. Site-directed mutagenesis of EBS on the Adamts-1 promoter demonstrated that EGR1 directly binds to the EBS at -1151/-1134 among four putative EBSs. Conclusions Collectively, we have demonstrated that Adamts-1 is a novel target gene of E2-ER-MAPK-EGR1, which is critical for embryo implantation in the mouse uterus during early pregnancy.

scholarly journals Prognostic significance of MYCN related genes in pediatric neuroblastoma: a study based on TARGET and GEO datasets

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Ji Zhang ◽  
Hua Cao
Keyword(s):  
Transcription Factor ◽  
Poor Prognosis ◽  
Target Genes ◽  
Cox Regression ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Gene Set Enrichment Analysis ◽  
Mycn Amplification ◽  
Prognostic Relevance ◽  
The Poor

Abstract Background: Neuroblastoma patients with MYCN amplification are associated with poor prognosis. However, the prognostic relevance of MYCN associated genes in neuroblastoma is unclear. Methods: The expression profiles of MYCN associated genes were identified from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) datasets. Enriched transcription factors and signaling pathways were determined using gene set enrichment analysis (GSEA). Kaplan-Meier plotter was used to identify the prognostic relevance of MYCN associated genes. Multivariate cox regression and Spearman’s correlation were used to determine the correlation coefficients of MYCN associated genes.Results: In TARGET and GSE85047 datasets, neuroblastoma patients with MYCN amplification were associated with worse prognosis. Transcription factor MYC was positively associated with MYCN amplification in GSEA assay. We identified 13 MYC target genes which were increased in neuroblastoma patients with MYCN amplification in TARGET, GSE19274 and GSE85047 datasets. Moreover, six out of the 13 MYC target genes ARMC6, DCTPP1, EIF4G1, ELOVL6, FBL and PRMT1 were associated with adverse prognosis in TARGET and GSE85047 datasets. Transcription factor E2F1 was up-regulated by MYCN amplification and associated with the poor prognosis of neuroblastoma. Furthermore, RPS19 in ribosome signaling pathway was also associated with MYCN amplification and correlated with the poor prognosis of neuroblastoma. At last, we showed that most of MYCN target genes were correlated with each other. However, EIF4G1 was an independent prognostic marker. And the prognostic effects of the combination of MYCN amplification and EIF4G1 expression were more significant than MYCN or EIF4G1 alone.Conclusions: MYCN target genes ARMC6, DCTPP1, EIF4G1, ELOVL6, FBL, PRMT1, E2F1 and RPS19 had significant prognostic effects in pediatric neuroblastoma. And neuroblastoma patients without MYCN amplification and low EIF4G1 expression had best prognosis.

scholarly journals The transcription factor C/EBPβ orchestrates dendritic cell maturation and functionality under homeostatic and malignant conditions

2020 ◽  
Vol 117 (42) ◽  
pp. 26328-26339
Author(s):  
Florian Scholz ◽  
Michael Grau ◽  
Lutz Menzel ◽  
Annika Graband ◽  
Myroslav Zapukhlyak ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Dendritic Cell ◽  
Cell Fate ◽  
Target Genes ◽  
Expression Profiles ◽  
B Cell Lymphoma ◽  
Negative Regulator ◽  
Cell Fate Decisions ◽  
Factor C ◽  
Dc Maturation

Dendritic cell (DC) maturation is a prerequisite for the induction of adaptive immune responses against pathogens and cancer. Transcription factor (TF) networks control differential aspects of early DC progenitor versus late-stage DC cell fate decisions. Here, we identified the TF C/EBPβ as a key regulator for DC maturation and immunogenic functionality under homeostatic and lymphoma-transformed conditions. Upon cell-specific deletion of C/EBPβ in CD11c+MHCIIhiDCs, gene expression profiles of splenic C/EBPβ−/−DCs showed a down-regulation of E2F cell cycle target genes and associated proliferation signaling pathways, whereas maturation signatures were enriched. Total splenic DC cell numbers were modestly increased but differentiation into cDC1 and cDC2 subsets were unaltered. The splenic CD11c+MHCIIhiCD64+DC compartment was also increased, suggesting that C/EBPβ deficiency favors the expansion of monocytic-derived DCs. Expression of C/EBPβ could be mimicked in LAP/LAP* isoform knockin DCs, whereas the short isoform LIP supported a differentiation program similar to deletion of the full-length TF. In accordance with E2F1 being a negative regulator of DC maturation, C/EBPβ−/−bone marrow-derived DCs matured much faster enabling them to activate and polarize T cells stronger. In contrast to a homeostatic condition, lymphoma-exposed DCs exhibited an up-regulation of the E2F transcriptional pathways and an impaired maturation. Pharmacological blockade of C/EBPβ/mTOR signaling in human DCs abrogated their protumorigenic function in primary B cell lymphoma cocultures. Thus, C/EBPβ plays a unique role in DC maturation and immunostimulatory functionality and emerges as a key factor of the tumor microenvironment that promotes lymphomagenesis.

scholarly journals Rev7/MAD2B Links c-Jun N-Terminal Protein Kinase Pathway Signaling to Activation of the Transcription Factor Elk-1

2007 ◽  
Vol 27 (8) ◽  
pp. 2861-2869 ◽  
Author(s):  
Lin Zhang ◽  
Shen-Hsi Yang ◽  
Andrew D. Sharrocks
Keyword(s):  
Gene Expression ◽  
Dna Damage ◽  
Transcription Factor ◽  
Protein Kinase ◽  
Transcriptional Activation ◽  
Cellular Response ◽  
Map Kinases ◽  
Target Genes ◽  
Expression Profiles ◽  
Terminal Protein

ABSTRACT The mitogen-activated protein (MAP) kinases represent one of the most important classes of signaling cascades that are used by eukaryotic cells to sense extracellular signals. One of the major responses to these cascades is a change in cellular gene expression profiles mediated through the direct targeting of transcriptional regulators, such as the transcription factor Elk-1. Here we have identified human Rev7 (hRev7)/MAD2B/MAD2L2 as an interaction partner for Elk-1 and demonstrate that hRev7 acts to promote Elk-1 phosphorylation by the c-Jun N-terminal protein kinase (JNK) MAP kinases. As phosphorylation of Elk-1 potentiates the activity of its transcriptional activation domain, hRev7 therefore contributes to the upregulation of Elk-1 target genes, such as egr-1, following exposure of cells to stress conditions caused by DNA-damaging agents. Thus, given its previous roles in permitting DNA damage bypass during replication and regulating cell cycle progression, our data linking hRev7 to gene expression changes suggest that hRev7 has a widespread role in coordinating the cellular response to DNA damage.

scholarly journals Clustered, information-dense transcription factor binding sites identify genes with similar tissue-wide expression profiles

2018 ◽  
Author(s):  
Ruipeng Lu ◽  
Peter K. Rogan
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Transcription Factor ◽  
Binding Site ◽  
Target Gene ◽  
Target Genes ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Factor Binding

ABSTRACTBackgroundThe distribution and composition ofcis-regulatory modules (e.g. transcription factor binding site (TFBS) clusters) in promoters substantially determine gene expression patterns and TF targets, whose expression levels are significantly regulated by TF binding. TF knockdown experiments have revealed correlations between TF binding profiles and gene expression levels. We present a general framework capable of predicting genes with similar tissue-wide expression patterns from activated or repressed TF targets using machine learning to combine TF binding and epigenetic features.MethodsGenes with correlated expression patterns across 53 tissues were identified according to their Bray-Curtis similarity. DNase I HyperSensitive region (DHS) -accessible promoter intervals of direct TF target genes were scanned with previously derived information theory-based position weight matrices (iPWMs) of 82 TFs. Features from information density-based TFBS clusters were used to predict target genes with machine learning classifiers. The accuracy, specificity and sensitivity of the classifiers were determined for different feature sets. Mutations in TFBSs were also introduced to examine their impact on cluster densities and the regulatory states of predicted target genes.ResultsWe initially chose the glucocorticoid receptor gene (NR3C1), whose regulation has been extensively studied, to test this approach.SLC25A32andTANKwere found to exhibit the most similar expression patterns to this gene across 53 tissues. Prediction of other genes with similar expression profiles was significantly improved by eliminating inaccessible promoter intervals based on DHSs. A Random Forest classifier exhibited the best performance in detecting such coordinately regulated genes (accuracy was 0.972 for training, 0.976 for testing). Target gene prediction was confirmed using CRISPR knockdown data of TFs, which was more accurate than siRNA inactivation. Mutation analyses of TFBSs also revealed that one or more information-dense TFBS clusters in promoters are required for accurate target gene prediction.ConclusionsMachine learning based on TFBS information density, organization, and chromatin accessibility accurately identifies gene targets with comparable tissue-wide expression patterns. Multiple, information-dense TFBS clusters in promoters appear to protect promoters from the effects of deleterious binding site mutations in a single TFBS that would effectively alter the expression state of these genes.

A Molecular Signature of the Transcription Factor GATA1 in Acute Megakaryoblastic Leukemia of Childhood.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 1117-1117
Author(s):  
Jean-Pierre Bourquin ◽  
Claudia Langebrake ◽  
Aravind Subramanian ◽  
Xiaochun Li ◽  
Dirk Reinhardt ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Target Genes ◽  
Cellular Proliferation ◽  
Expression Profiles ◽  
Chromosome 21 ◽  
Molecular Signature ◽  
Consensus Clustering ◽  
Acute Megakaryoblastic Leukemia ◽  
Megakaryoblastic Leukemia

Abstract To investigate the pathogenesis of acute megakaryoblastic leukemia, AML M7 (M7), we analyzed the gene expression profiles of 113 patient samples on Affymetrix U133A GeneChips. Classification by unsupervised clustering discriminates 70 M7 samples from 12 with other AML FAB subtypes, 3 normal controls, 10 normal and remission samples of patients with Down Syndrome (DS) and 18 ALL samples from DS patients. Further, M7 subclasses can be identified. DS samples (21 DS-M7 and 9 transient myeloproliferative disease (TMD) samples) cluster apart from non-DS M7 samples, with a few exceptions, most notably the 4 M7 samples with the translocation t(1;22). Smaller subgroups can be detected by consensus clustering in DS and non-DS M7. The DS-non-DS distinction is not driven by differential expression of chromosome 21 genes, in particular RUNX1 expression levels are not increased in DS. Consistent with differences observed by flow cytometry, DS samples show a higher expression of ANK1, GYPA, GYPB and CD36, while non-DS M7 samples have higher VWF and CD34 expression, reflecting known morphologic differences. The hematopoietic transcription factor GATA1 is overexpressed in DS M7/TMD when compared to non-DS M7s or controls, and is among the most significant markers of the DS class. The mutation of GATA1 that is characteristic for DS is likely to affect its transcriptome specifically. By nearest neighbour analysis, about 300 genes follow the pattern of the GATA1 gene expression within a significant range by permutation testing. This GATA-1 signature is highly enriched in the DS samples and includes several known target genes of GATA1, such as GATA2, GYPA, ANK1 and ALAD. This approach should lead to the identification of genes contributing to cellular proliferation and differentiation in the context of the GATA1 mutation of DS M7.

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