scholarly journals Dissecting the pre-placodal transcriptome to reveal presumptive direct targets of Six1 and Eya1 in cranial placodes

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Nick Riddiford ◽  
Gerhard Schlosser
Keyword(s):  
Transcription Factor ◽  
Protein Synthesis ◽  
Regulatory Network ◽  
Target Genes ◽  
Nuclear Translocation ◽  
Transcriptional Regulators ◽  
Rna Seq ◽  
Loss Of Function ◽  
Genes Encoding ◽  
Gene Regulatory

The pre-placodal ectoderm, marked by the expression of the transcription factor Six1 and its co-activator Eya1, develops into placodes and ultimately into many cranial sensory organs and ganglia. Using RNA-Seq in Xenopus laevis we screened for presumptive direct placodal target genes of Six1 and Eya1 by overexpressing hormone-inducible constructs of Six1 and Eya1 in pre-placodal explants, and blocking protein synthesis before hormone-inducing nuclear translocation of Six1 or Eya1. Comparing the transcriptome of explants with non-induced controls, we identified hundreds of novel Six1/Eya1 target genes with potentially important roles for placode development. Loss-of-function studies confirmed that target genes encoding known transcriptional regulators of progenitor fates (e.g. Sox2, Hes8) and neuronal/sensory differentiation (e.g. Ngn1, Atoh1, Pou4f1, Gfi1) require Six1 and Eya1 for their placodal expression. Our findings provide insights into the gene regulatory network regulating placodal neurogenesis downstream of Six1 and Eya1 suggesting new avenues of research into placode development and disease.

scholarly journals Regulatory Network Connecting Two Glucose Signal Transduction Pathways in Saccharomyces cerevisiae

2004 ◽  
Vol 3 (1) ◽  
pp. 221-231 ◽  
Author(s):  
Aneta Kaniak ◽  
Zhixiong Xue ◽  
Daniel Macool ◽  
Jeong-Ho Kim ◽  
Mark Johnston
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Signal Transduction ◽  
Transcription Factor ◽  
Regulatory Network ◽  
Target Genes ◽  
Glucose Repression ◽  
Signal Transduction Pathways ◽  
Glucose Signaling ◽  
Genes Encoding ◽  
Glucose Induction

ABSTRACT The yeast Saccharomyces cerevisiae senses glucose, its preferred carbon source, through multiple signal transduction pathways. In one pathway, glucose represses the expression of many genes through the Mig1 transcriptional repressor, which is regulated by the Snf1 protein kinase. In another pathway, glucose induces the expression of HXT genes encoding glucose transporters through two glucose sensors on the cell surface that generate an intracellular signal that affects function of the Rgt1 transcription factor. We profiled the yeast transcriptome to determine the range of genes targeted by this second pathway. Candidate target genes were verified by testing for Rgt1 binding to their promoters by chromatin immunoprecipitation and by measuring the regulation of the expression of promoter lacZ fusions. Relatively few genes could be validated as targets of this pathway, suggesting that this pathway is primarily dedicated to regulating the expression of HXT genes. Among the genes regulated by this glucose signaling pathway are several genes involved in the glucose induction and glucose repression pathways. The Snf3/Rgt2-Rgt1 glucose induction pathway contributes to glucose repression by inducing the transcription of MIG2, which encodes a repressor of glucose-repressed genes, and regulates itself by inducing the expression of STD1, which encodes a regulator of the Rgt1 transcription factor. The Snf1-Mig1 glucose repression pathway contributes to glucose induction by repressing the expression of SNF3 and MTH1, which encodes another regulator of Rgt1, and also regulates itself by repressing the transcription of MIG1. Thus, these two glucose signaling pathways are intertwined in a regulatory network that serves to integrate the different glucose signals operating in these two pathways.

scholarly journals Identification of key tissue-specific, biological processes by integrating enhancer information in maize gene regulatory networks

2020 ◽  
Author(s):  
Maud Fagny ◽  
Marieke Lydia Kuijjer ◽  
Maike Stam ◽  
Johann Joets ◽  
Olivier Turc ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Binding Sites ◽  
Regulatory Network ◽  
Tissue Specificity ◽  
Target Genes ◽  
Specific Gene ◽  
Tissue Specific ◽  
Genome Wide ◽  
Gene Regulatory

AbstractEnhancers are important regulators of gene expression during numerous crucial processes including tissue differentiation across development. In plants, their recent molecular characterization revealed their capacity to activate the expression of several target genes through the binding of transcription factors. Nevertheless, identifying these target genes at a genome-wide level remains a challenge, in particular in species with large genomes, where enhancers and target genes can be hundreds of kilobases away. Therefore, the contribution of enhancers to regulatory network is still poorly understood in plants. In this study, we investigate the enhancer-driven regulatory network of two maize tissues at different stages: leaves at seedling stage and husks (bracts) at flowering. Using a systems biology approach, we integrate genomic, epigenomic and transcriptomic data to model the regulatory relationship between transcription factors and their potential target genes. We identify regulatory modules specific to husk and V2-IST, and show that they are involved in distinct functions related to the biology of each tissue. We evidence enhancers exhibiting binding sites for two distinct transcription factor families (DOF and AP2/ERF) that drive the tissue-specificity of gene expression in seedling immature leaf and husk. Analysis of the corresponding enhancer sequences reveals that two different transposable element families (TIR transposon Mutator and MITE Pif/Harbinger) have shaped the regulatory network in each tissue, and that MITEs have provided new transcription factor binding sites that are involved in husk tissue-specificity.SignificanceEnhancers play a major role in regulating tissue-specific gene expression in higher eukaryotes, including angiosperms. While molecular characterization of enhancers has improved over the past years, identifying their target genes at the genome-wide scale remains challenging. Here, we integrate genomic, epigenomic and transcriptomic data to decipher the tissue-specific gene regulatory network controlled by enhancers at two different stages of maize leaf development. Using a systems biology approach, we identify transcription factor families regulating gene tissue-specific expression in husk and seedling leaves, and characterize the enhancers likely to be involved. We show that a large part of maize enhancers is derived from transposable elements, which can provide novel transcription factor binding sites crucial to the regulation of tissue-specific biological functions.

scholarly journals BMP2-dependent gene regulatory network analysis reveals Klf4 as a novel transcription factor of osteoblast differentiation

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Shuaitong Yu ◽  
Jinqiang Guo ◽  
Zheyi Sun ◽  
Chujiao Lin ◽  
Huangheng Tao ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Transcription Factor ◽  
Gene Regulatory Network ◽  
Stromal Cells ◽  
Regulatory Network ◽  
Bone Marrow Stromal Cells ◽  
Osteoblast Differentiation ◽  
Marrow Stromal Cells ◽  
Rna Seq ◽  
Gene Regulatory

AbstractTranscription factors (TFs) regulate the expression of target genes, inducing changes in cell morphology or activities needed for cell fate determination and differentiation. The BMP signaling pathway is widely regarded as one of the most important pathways in vertebrate skeletal biology, of which BMP2 is a potent inducer, governing the osteoblast differentiation of bone marrow stromal cells (BMSCs). However, the mechanism by which BMP2 initiates its downstream transcription factor cascade and determines the direction of differentiation remains largely unknown. In this study, we used RNA-seq, ATAC-seq, and animal models to characterize the BMP2-dependent gene regulatory network governing osteoblast lineage commitment. Sp7-Cre; Bmp2fx/fx mice (BMP2-cKO) were generated and exhibited decreased bone density and lower osteoblast number (n > 6). In vitro experiments showed that BMP2-cKO mouse bone marrow stromal cells (mBMSCs) had an impact on osteoblast differentiation and deficient cell proliferation. Osteogenic medium induced mBMSCs from BMP2-cKO mice and control were subjected to RNA-seq and ATAC-seq analysis to reveal differentially expressed TFs, along with their target open chromatin regions. Combined with H3K27Ac CUT&Tag during osteoblast differentiation, we identified 2338 BMP2-dependent osteoblast-specific active enhancers. Motif enrichment assay revealed that over 80% of these elements were directly targeted by RUNX2, DLX5, MEF2C, OASIS, and KLF4. We deactivated Klf4 in the Sp7 + lineage to validate the role of KLF4 in osteoblast differentiation of mBMSCs. Compared to the wild-type, Sp7-Cre; Klf4fx/+ mice (KLF4-Het) were smaller in size and had abnormal incisors resembling BMP2-cKO mice. Additionally, KLF4-Het mice had fewer osteoblasts and decreased osteogenic ability. RNA-seq and ATAC-seq revealed that KLF4 mainly “co-bound” with RUNX2 to regulate downstream genes. Given the significant overlap between KLF4- and BMP2-dependent NFRs and enriched motifs, our findings outline a comprehensive BMP2-dependent gene regulatory network specifically governing osteoblast differentiation of the Sp7 + lineage, in which Klf4 is a novel transcription factor.

scholarly journals SCENIC: Single-cell regulatory network inference and clustering

2017 ◽  
Author(s):  
Sara Aibar ◽  
Carmen Bravo González-Blas ◽  
Thomas Moerman ◽  
Jasper Wouters ◽  
Vân Anh Huynh-Thu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Regulatory Network ◽  
Network Inference ◽  
Target Genes ◽  
Single Cells ◽  
State Transitions ◽  
Rna Seq ◽  
Cell State ◽  
Gene Regulatory

AbstractSingle-cell RNA-seq allows building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories. Both the maintenance and transitions of cell states are encoded by regulatory programs in the genome sequence. However, this regulatory code has not yet been exploited to guide the identification of cellular states from single-cell RNA-seq data. Here we describe a computational resource, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), for the simultaneous reconstruction of gene regulatory networks (GRNs) and the identification of stable cell states, using single-cell RNA-seq data. SCENIC outperforms existing approaches at the level of cell clustering and transcription factor identification. Importantly, we show that cell state identification based on GRNs is robust towards batch-effects and technical-biases. We applied SCENIC to a compendium of single-cell data from the mouse and human brain and demonstrate that the proper combinations of transcription factors, target genes, enhancers, and cell types can be identified. Moreover, we used SCENIC to map the cell state landscape in melanoma and identified a gene regulatory network underlying a proliferative melanoma state driven by MITF and STAT and a contrasting network controlling an invasive state governed by NFATC2 and NFIB. We further validated these predictions by showing that two transcription factors are predominantly expressed in early metastatic sentinel lymph nodes. In summary, SCENIC is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach. SCENIC is generic, easy to use, and flexible, and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs. Availability: SCENIC is available as an R workflow based on three new R/Bioconductor packages: GENIE3, RcisTarget and AUCell. As scalable alternative to GENIE3, we also provide GRNboost, paving the way towards the network analysis across millions of single cells.

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.

Deciphering the transcription factor-microRNA-target gene regulatory network associated with graphene oxide cytotoxicity

2018 ◽  
Vol 12 (9) ◽  
pp. 1014-1026 ◽  
Author(s):  
Masoumeh Farahani ◽  
Mostafa Rezaei–Tavirani ◽  
Hakimeh Zali ◽  
Afsaneh Arefi Oskouie ◽  
Meisam Omidi ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Graphene Oxide ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Target Gene ◽  
Microrna Target ◽  
Gene Regulatory

scholarly journals Deciphering the genetic links between NAFLD and co-occurring conditions using a liver gene regulatory network

2021 ◽  
Author(s):  
Sreemol Gokuladhas ◽  
William Schierding ◽  
Roan Eltigani Zaied ◽  
Tayaza Fadason ◽  
Murim Choi ◽  
...  
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Complex Traits ◽  
Target Genes ◽  
Specific Gene ◽  
Fat Percentage ◽  
Alcoholic Fatty Liver ◽  
Regulatory Interactions ◽  
Hepatic Diseases ◽  
Gene Regulatory

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a multi-system metabolic disease that co-occurs with various hepatic and extra-hepatic diseases. The phenotypic manifestation of NAFLD is primarily observed in the liver. Therefore, identifying liver-specific gene regulatory interactions between variants associated with NAFLD and multimorbid conditions may help to improve our understanding of underlying shared aetiology. Methods: Here, we constructed a liver-specific gene regulatory network (LGRN) consisting of genome-wide spatially constrained expression quantitative trait loci (eQTLs) and their target genes. The LGRN was used to identify regulatory interactions involving NAFLD-associated genetic modifiers and their inter-relationships to other complex traits. Results and Conclusions: We demonstrate that MBOAT7 and IL32, which are associated with NAFLD progression, are regulated by spatially constrained eQTLs that are enriched for an association with liver enzyme levels. MBOAT7 transcript levels are also linked to eQTLs associated with cirrhosis, and other traits that commonly co-occur with NAFLD. In addition, genes that encode interacting partners of NAFLD-candidate genes within the liver-specific protein-protein interaction network were affected by eQTLs enriched for phenotypes relevant to NAFLD (e.g. IgG glycosylation patterns, OSA). Furthermore, we identified distinct gene regulatory networks formed by the NAFLD-associated eQTLs in normal versus diseased liver, consistent with the context-specificity of the eQTLs effects. Interestingly, genes targeted by NAFLD-associated eQTLs within the LGRN were also affected by eQTLs associated with NAFLD-related traits (e.g. obesity and body fat percentage). Overall, the genetic links identified between these traits expand our understanding of shared regulatory mechanisms underlying NAFLD multimorbidities.

scholarly journals Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters

2019 ◽  
Author(s):  
Joanna Mitchelmore ◽  
Nastasiya Grinberg ◽  
Chris Wallace ◽  
Mikhail Spivakov
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Statistical Power ◽  
Target Genes ◽  
Allelic Variation ◽  
Regulatory Function ◽  
Regulatory Sequences ◽  
Distal Enhancer ◽  
Association Testing ◽  
Gene Regulatory

AbstractIdentifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritising such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines (LCLs) and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal over 1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localise to the promoter regions of other genes, supporting the notion of ‘epromoters’: dual-action CRMs with promoter and distal enhancer activity.

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 Distinct Posttranscriptional Mechanisms Regulate the Activity of the Zn Finger Transcription Factor Lame duck during Drosophila Myogenesis

2006 ◽  
Vol 26 (4) ◽  
pp. 1414-1423 ◽  
Author(s):  
Hong Duan ◽  
Hanh T. Nguyen
Keyword(s):  
Skeletal Muscle ◽  
Transcription Factor ◽  
Posttranslational Modifications ◽  
Target Genes ◽  
Nuclear Translocation ◽  
Protein Activity ◽  
Downstream Target ◽  
Muscle Formation ◽  
Lame Duck ◽  
Fusion Competent Myoblasts

ABSTRACT Skeletal muscle formation in Drosophila melanogaster requires two types of myoblasts, muscle founders and fusion-competent myoblasts. Lame duck (Lmd), a member of the Gli superfamily of transcription factors, is essential for the specification and differentiation of fusion-competent myoblasts. We report herein that appropriate levels of active Lmd protein are attained by a combination of posttranscriptional mechanisms. We provide evidence that two different regions of the Lmd protein are critical for modulating the balance between its nuclear translocation and its retention within the cytoplasm. Activation of the Lmd protein is also tempered by posttranslational modifications of the protein that do not detectably change its subcellular localization. We further show that overexpression of Lmd protein derivatives that are constitutively nuclear or hyperactive results in severe muscle defects. These findings underscore the importance of regulated Lmd protein activity in maintaining proper activation of downstream target genes, such as Mef2, within fusion-competent myoblasts.

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