Increased expression of the Zn-finger transcription factor BTEB1 in human endometrial cells is correlated with distinct cell phenotype, gene expression patterns, and proliferative responsiveness to serum and TGF-β1

2001 ◽  
Vol 181 (1-2) ◽  
pp. 81-96 ◽  
Author(s):  
Xue-Lian Zhang ◽  
Frank A. Simmen ◽  
Frank J. Michel ◽  
Rosalia C.M. Simmen
2019 ◽  
Author(s):  
Alexandra Grubman ◽  
Gabriel Chew ◽  
John F. Ouyang ◽  
Guizhi Sun ◽  
Xin Yi Choo ◽  
...  

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. SCI-10-SCI-10
Author(s):  
John Stamatoyannopoulos

Abstract Regulatory elements control the anatomic and cellular contexts, timing, and magnitude of gene expression patterns. Under the ENCODE and Roadmap Epigenomics Projects, human regulatory DNA has been mapped using a variety of approaches in over 300 cell and tissue types and developmental states. Collectively, the human genome encodes several million regulatory elements, most of which are located at some distance from promoters. The vast majority of these elements exhibit exquisite cell-and lineage-selective activation patterns, providing novel insights into the coordination of gene expression patterns. Genomic footprinting is a new and powerful technology that enables simultaneous profiling of the occupancy of hundreds of sequence-specific transcription factors within regulatory regions. These profiles in turn enable construction of transcription factor regulatory networks that are providing new insights into how cell-and lineage-specific gene expression programs arise. Hundreds of genetic variants associated with a wide range of hematological traits and disorders localize within regulatory regions. Many such variants disrupt specific transcription factor-DNA interactions, exposing pathophysiologically relevant transcriptional regulatory pathways. Disclosures: No relevant conflicts of interest to declare.


2015 ◽  
Vol 65 (3-4) ◽  
pp. 193-207 ◽  
Author(s):  
Aiyun Wen ◽  
Feng You ◽  
Peng Sun ◽  
Jun Li ◽  
Dongdong Xu ◽  
...  

The present study aims to elucidate the different expression patterns and possible roles of Doublesex and Mab-3-related transcription factor 1 (dmrt1), dmrt4, SRY-related transcription factor 9 (sox9) and cytochrome P450 aromatase 19a (cyp19a) during gonadal differentiation in olive flounder, Paralichthys olivaceus. We first analyzed the gene expression patterns in tissues using RT-PCR, which indicated dmrt1, sox9 and cyp19a were sex-related genes with sexual dimorphic expression. The quantitative expression changes of these three genes together with dmrt4 during gonadal differentiation were further examined using real-time RT-PCR. The results showed that dmrt1 was scarcely expressed in the primitive gonad and during following periods of gonadal differentiation. Its expression increased rapidly in the differentiating testis. Dmrt4 was strongly expressed in primitive gonads and much less expressed during following periods of gonadal differentiation. Its expression became strong in differentiating testes. While sox9 was highly expressed in the primitive gonad, it was expressed with fluctuations during following periods of gonadal differentiation. Cyp19a started expressing in primitive gonads, and its expression quantity fluctuated during latter periods of gonadal differentiation, but was strongly expressed in the early stage of differentiating ovaries. Results of in situ hybridization showed that dmrt4 and sox9 transcripts were both mainly localized in spermatocytes and our results suggested these four sex-related genes might be involved in gonadal differentiation through their synergistic effects in flounder.


2018 ◽  
Vol 136 (5) ◽  
pp. 709-727 ◽  
Author(s):  
Mariet Allen ◽  
Xue Wang ◽  
Daniel J. Serie ◽  
Samantha L. Strickland ◽  
Jeremy D. Burgess ◽  
...  

2015 ◽  
Author(s):  
Konstantin N Kozlov ◽  
Vitaly V Gursky ◽  
Ivan V Kulakovskiy ◽  
Maria G Samsonova

Background: The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. Results: We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and the set, from which the site of interest was left out. Conclusions: The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays. Keywords: transcription; thermodynamics; reaction-diffusion; drosophila


2021 ◽  
Vol 12 ◽  
Author(s):  
Nazia Parveen ◽  
Sangeeta Dhawan

Pancreatic beta cells play a central role in regulating glucose homeostasis by secreting the hormone insulin. Failure of beta cells due to reduced function and mass and the resulting insulin insufficiency can drive the dysregulation of glycemic control, causing diabetes. Epigenetic regulation by DNA methylation is central to shaping the gene expression patterns that define the fully functional beta cell phenotype and regulate beta cell growth. Establishment of stage-specific DNA methylation guides beta cell differentiation during fetal development, while faithful restoration of these signatures during DNA replication ensures the maintenance of beta cell identity and function in postnatal life. Lineage-specific transcription factor networks interact with methylated DNA at specific genomic regions to enhance the regulatory specificity and ensure the stability of gene expression patterns. Recent genome-wide DNA methylation profiling studies comparing islets from diabetic and non-diabetic human subjects demonstrate the perturbation of beta cell DNA methylation patterns, corresponding to the dysregulation of gene expression associated with mature beta cell state in diabetes. This article will discuss the molecular underpinnings of shaping the islet DNA methylation landscape, its mechanistic role in the specification and maintenance of the functional beta cell phenotype, and its dysregulation in diabetes. We will also review recent advances in utilizing beta cell specific DNA methylation patterns for the development of biomarkers for diabetes, and targeting DNA methylation to develop translational approaches for supplementing the functional beta cell mass deficit in diabetes.


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2210-2210
Author(s):  
H. Jiang ◽  
C. Wade-Harris ◽  
L. Baxi ◽  
M. S. Cairo

Abstract It has been recognized that dysfunction of CB immunity is in part due to the immaturity of the neonatal immune system (Cairo, Blood, 1997). However, biological pathways and molecular mechanisms associated with the immaturity of CB immunity are still poorly understood. Recently we have utilized oligonucleotide microarray to examine gene expression profiling of CB versus APB Mo and have demonstrated significant differential gene expression patterns, including surface molecules, cytokines, signaling molecules, transcription factors and apoptotic genes (Jiang/Cairo, et al, J. of Immunol., 2004). We sought to examine whether there are differential expressed genes occurred in Mo-derived CB versus APB DC and their impact on DC mediated T cell activity. Briefly, Mo were purified from fresh CB or APB and cultured for 8 days with GM-CSF and IL-4 (immature DC (iDC)) and LPS for mature DC (mDC). mRNA was isolated and oligonucleotide microarray was carried out (Affymetrix, U133A). Data was analyzed by Microarray Suite Version 5.0 (Affymetrix) and GeneSpring 5.0 software (Silicon Genetics). Selected genes were analyzed by RT-PCR (SuperScript, Invetrogen). We identified gene expression patterns that were significantly lower in CB versus APB DC including surface molecules HLA-DQA1 (4F), HLA-DRB3 (5F), HLA-DRB4 (5.5F), CD80 (3F), CD38 (3.8F); cytokine/chemokine genes IL-1b (2.5F), IL6 (2.9F), IL12B (3.5F), CXCL10 (6.6F); immunoregulatory genes ISG20 (11F), IFI27 (7.6F), TNFSF10 (4.5F), SOCS3 (2.5F). Moreover, several transcription factor genes whose proteins may involve in the activation of expression of these immune regulator genes were also differentially expressed (IRF-5 (3F), IRF7 (3F), MAD (6.3F)). We therefore compared CB versus APB DC antigen presentation activity to APB CD8 T cells by ELISPOT assay for interferon-r (IFNr) production (BD Pharmagen). Briefly, the purified CD8 T cells (MHC HLA A2) were incubated with CB or APB DC that were loaded without or with influenza peptide onto ELISPOT plate (Larsson, et al, J. of Immunol., 2000). The ELISPOT plates were developed, scanned and quantitated by an ELISPOT reader (C.T.L. Technology). Our results demonstrated that, although CB or APB mDC had allogeneic effects, influenza peptide loaded CB mDC was not able to induce CD8 T cells to produce IFNr while APB mDC loaded with influenza peptide strongly induced CD8 T cells to produce IFNr. This stimulatory effect of APB mDC on CD8 T cells to produce IFNr was 3.5 fold greater than that of CB mDC. We further examined DC antigen presentation activity to CD4 T cells and observed that APB-DC had stronger effects on CD4 T cell proliferation (3 fold for mDC vs. iDC) compared with CB-DC (only 1.5 fold for mDC vs. iDC) by CFSE assay (Molecular Probe). We postulate that decreased expression of specific surface molecules and other genes resulting in lower surface protein expression in CB DC may in part be responsible for the lack of initiation of signaling events from cell surface to trigger CB-DC to stimulate activation of CD8 and CD4 T cells. The decreased expression of transcription factor genes may also in part be responsible for the lower expressed surface molecule genes. Furthermore, these decreased expressed genes in other molecular categories in LPS-CB vs. APB DC may also partially be responsible for differential innate and adaptive immune function and properties of CB vs. APB.


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