Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Responsiveness of genes to manipulation of transcription factors in ES cells is associated with chromatin structure and tissue specificity

ABSTRACT: Background: In addition to determining static states of gene expression (high vs. low), it is important to characterize their dynamic status. For example, genes with H3K27me3 chromatin marks are not only suppressed but also poised for activation. However, the responsiveness of genes to perturbations has never been studied systematically. To distinguish gene responses to specific factors from responsiveness in general, it is necessary to analyze gene expression profiles of cells responding to a large variety of disturbances, and such databases did not exist before. Results: We estimated the responsiveness of all genes in mouse ES cells using our recently published database on expression change after controlled induction of 53 transcription factors (TFs) and other genes. Responsive genes (/N/ = 4746), which were readily upregulated or downregulated depending on the kind of perturbation, mostly have regulatory functions and a propensity to become tissue-specific upon differentiation. Tissue-specific expression was evaluated on the basis of published (GNF) and our new data for 15 organs and tissues. Non-responsive genes (/N/ = 9562), which did not change their expression much following any perturbation, were enriched in housekeeping functions. We found that TF-responsiveness in ES cells is the best predictor known for tissue-specificity in gene expression. Among genes with CpG islands, high responsiveness is strongly associated with H3K27me3 chromatin marks, and low responsiveness is associated with H3K36me3 chromatin, binding of E2F1, and GABP binding motifs in promoters. Conclusions: We thus propose the responsiveness of expression to perturbations as a new way to define the dynamic status of genes, which brings new insights into mechanisms of regulation of gene expression and tissue specificity. This SuperSeries is composed of the following subset Series: GSE19806: Responsiveness of genes to manipulation of transcription factors in ES cells is associated with histone modifications and tissue specificity (1 of 2) GSE19814: Responsiveness of genes to manipulation of transcription factors in ES cells is associated with histone modifications and tissue specificity (2 of 2) Refer to individual Series

ORGANISM(S): Mus musculus

SUBMITTER: Minoru Ko

PROVIDER: E-GEOD-22151 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Responsiveness of genes to manipulation of transcription factors in ES cells is associated with histone modifications and tissue specificity.

Sharov Alexei A AA Nishiyama Akira A Piao Yulan Y Correa-Cerro Lina S LS Amano Tomokazu T Thomas Marshall M Mehta Samir S Ko Minoru S H MS

BMC genomics 20110209

<h4>Background</h4>In addition to determining static states of gene expression (high vs. low), it is important to characterize their dynamic status. For example, genes with H3K27me3 chromatin marks are not only suppressed but also poised for activation. However, the responsiveness of genes to perturbations has never been studied systematically. To distinguish gene responses to specific factors from responsiveness in general, it is necessary to analyze gene expression profiles of cells responding ...[more]

PMID: 21306619

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Project description:BACKGROUND: In addition to determining static states of gene expression (high vs. low), it is important to characterize their dynamic status. For example, genes with H3K27me3 chromatin marks are not only suppressed but also poised for activation. However, the responsiveness of genes to perturbations has never been studied systematically. To distinguish gene responses to specific factors from responsiveness in general, it is necessary to analyze gene expression profiles of cells responding to a large variety of disturbances, and such databases did not exist before. RESULTS: We estimated the responsiveness of all genes in mouse ES cells using our recently published database on expression change after controlled induction of 53 transcription factors (TFs) and other genes. Responsive genes (N = 4746), which were readily upregulated or downregulated depending on the kind of perturbation, mostly have regulatory functions and a propensity to become tissue-specific upon differentiation. Tissue-specific expression was evaluated on the basis of published (GNF) and our new data for 15 organs and tissues. Non-responsive genes (N = 9562), which did not change their expression much following any perturbation, were enriched in housekeeping functions. We found that TF-responsiveness in ES cells is the best predictor known for tissue-specificity in gene expression. Among genes with CpG islands, high responsiveness is associated with H3K27me3 chromatin marks, and low responsiveness is associated with H3K36me3 chromatin, stronger tri-methylation of H3K4, binding of E2F1, and GABP binding motifs in promoters. CONCLUSIONS: We thus propose the responsiveness of expression to perturbations as a new way to define the dynamic status of genes, which brings new insights into mechanisms of regulation of gene expression and tissue specificity. Total RNA was isolated by TRIzol (Invitrogen) after 2 days. Cy3-CTP labeled sample targets were prepared with total RNA by Low RNA Input Fluorescent Linear Amplification Kit (Agilent). Cy5-CTP labeled reference target was produced from mixture of Stratagene Universal Mouse Reference RNA and MC1 cells RNA. Most samples were collected in 2 replications taken from different animals, except bone and fat, which had only one replication.

Project description:BACKGROUND: In addition to determining static states of gene expression (high vs. low), it is important to characterize their dynamic status. For example, genes with H3K27me3 chromatin marks are not only suppressed but also poised for activation. However, the responsiveness of genes to perturbations has never been studied systematically. To distinguish gene responses to specific factors from responsiveness in general, it is necessary to analyze gene expression profiles of cells responding to a large variety of disturbances, and such databases did not exist before. RESULTS: We estimated the responsiveness of all genes in mouse ES cells using our recently published database on expression change after controlled induction of 53 transcription factors (TFs) and other genes. Responsive genes (N = 4746), which were readily upregulated or downregulated depending on the kind of perturbation, mostly have regulatory functions and a propensity to become tissue-specific upon differentiation. Tissue-specific expression was evaluated on the basis of published (GNF) and our new data for 15 organs and tissues. Non-responsive genes (N = 9562), which did not change their expression much following any perturbation, were enriched in housekeeping functions. We found that TF-responsiveness in ES cells is the best predictor known for tissue-specificity in gene expression. Among genes with CpG islands, high responsiveness is associated with H3K27me3 chromatin marks, and low responsiveness is associated with H3K36me3 chromatin, stronger tri-methylation of H3K4, binding of E2F1, and GABP binding motifs in promoters. CONCLUSIONS: We thus propose the responsiveness of expression to perturbations as a new way to define the dynamic status of genes, which brings new insights into mechanisms of regulation of gene expression and tissue specificity Inhibitors of cell signaling are known to support the pluripotent state of embryonic stem cells (Ying et al. 2008, Nature 453, 519-523, PMID: 18497825). To characterize the effect of inhibitors on the gene expression we treated B6R(5) mouse ES cells (C57BL/6 strain) with FGFR inhibitor PD173074 (100 uM), MEK inhibitor PD98059 (25 uM),and GSK-3 inhibitor BIO (2 uM) 24 hr after plating. Cells were grown without feeders on gelatin coated, 6-well plates, 100,000 cells/well (10^4 cells/cm2), in complete ES medium at 37 0C; 5% CO2. Medium was changed daily. Inhibitors dissolved in DMSO were added 24 hr after plating and cells were harvested 48 hr after treatment (72 hr after plating). Control cells were treated with DMSO. Keywords: cell type comparison design,reference design Total RNA was isolated by TRIzol (Invitrogen) after 2 days. Cy3-CTP labeled sample targets were prepared with total RNA by Low RNA Input Fluorescent Linear Amplification Kit (Agilent). Cy5-CTP labeled reference target was Stratagene Universal Mouse Reference RNA.

Project description:The gold standard for examining pluripotency of stem cells is to see whether cells can contribute to entire body of animals. Here we show that the increased frequency of Zscan4 activation in mouse ES cells not only enhances, but also maintains their developmental potency in long-term cell culture. As the potency increases, even a whole animal can be produced from a single ES cell injected into 4N blastocyst at unusually high success rate. Although Zscan4-activated cells express genes that are also expressed in 2-cell stage mouse embryos, transiently Zscan4-activated state of ES cells is not associated with the high potency of ES cells. It is thus concluded that ES cells acquire higher potency by going through transient Zscan4 activation state more frequently than the regular state. Taken together, our results indicate that frequent activation of Zscan4 can rejuvenate pluripotent stem cells. MC1 ES cells (for pZscan4-Emerald transfection) and R26R6 ES cells (for pZscan4-Cre ERT2 transfection) were grown on gelatin in 6-well plate, 5x10^5cells in suspension were transfected with 1ug of linearized pZscan4-Emerald vector or pZscan4-Cre ERT2 vector using Effectene (QIAGEN) according manufacturer protocol, and plated in gelatin coated 100 mm dishes. Cells were selected with 5 ug/ml blasticidin, colonies were picked on the 8th day, expanded and frozen for further analysis. DNA microarray analysis of pZscan4-Emerald cells was carried out as described. In brief, universal Mouse Reference RNA (Stratagene) were labeled with Cy5-dye, mixed with Cy3-labeled samples, and used for hybridization on the NIA Mouse 44K Microarray v2.2 (manufactured by Agilent Technologies #014117). The intensity of each gene feature was extracted from scanned microarray images using Feature Extraction 9.5.1.1 software (Agilent Technologies). Microarray data analyses were carried out by using an application developed in-house to perform ANOVA and other analyses (NIA Array Analysis software; http://lgsun.grc.nia.nih.gov)

Project description:A network of transcription factors (TFs) determines cell identity, but identity can be altered by overexpressing a combination of TFs. In principle, this opens the possibility of achieving one of the goals of regenerative medicine generating the desired differentiated cells from pluripotent stem cells, such as embryonic stem (ES) cells and induced pluripotent stem (iPS) cells. However, choosing and verifying combinations of TFs for specific cell differentiation has been daunting due to a large number of possible combinations of ~2,000 TFs. Here we report an unbiased systematic approach identifying individual TFs that can direct efficient and rapid specific lineage differentiation. We start from a correlation matrix of global gene expression responses to the induction of single TFs and global gene expression profiles of a variety of tissues and organs. Based on the correlation matrix, we select TFs as examples and show that their overexpression differentiates ES cells into cells of specific organs, as predicted: Sfpi1 for blood cells, Hnf4a or Foxa1 for hepatocytes, and Ascl1 for neurons. Furthermore, we show that transfection of synthetic mRNAs of Sfpi1, Hnf4a, or Ascl1 generate correspondingly specific target cells. These results demonstrate both the wide-ranging utility of this approach to identify potent TFs for cell differentiation, and also the unanticipated capacity of single TFs to directly guide differentiation to specific lineage fates. Previously, we generated the global gene expression profiles obtained by overexpressing single TFs using the NIA mouse ES cell bank, which consists of 137 mouse ES cell lines carrying a doxycycline-regulatable TF. We then generated the correlation matrix by comparing TF-induced gene expression profiles and the expression profiles of a variety of cell types. TFs predicted by the correlation matrix for specific cell differentiation were selected and subjected to the detailed differentiation assays. ES cell lines were cultured in the GMEM with 1% FBS, 10% knockout serum (invitrogen), and LIF (Millipore). To induce differentiation, ES cell lines were cultured in the differentiation medium (DM) [(alpha minimal essential medium, aMEM) supplemented with 10% fetal calf serum and 5 × 10–5 M 2-mercaptoethanol] with or without doxycycline (1 g/ml). The following organ-specific cell culture media were also used: StemPro-34 Serum Free Media (invitrogen) for blood cells, Hepatocyte culture media kit (BD Biosciences) for hepatocytes, and NeuroCult differentiation kit (StemCell Technologies Inc) for neurons.

Project description:To decipher the structure and behaviors of the transcription factor (TF) network, we created 50 permanent mouse ES cell lines, in each of which one of the 50 transcription factors tagged with FLAG, is inserted into the doxycycline (dox)-repressible ROSA26 locus. Expression profiling reveals Cdx2 as the most potent inducer of transcriptome perturbation in ES cells, followed by Esx1, Sox9, Tcf3, Klf4, and Gata3. Immunoprecipitation (IP) with a FLAG-antibody in Cdx2-induced ES cells, identifies NuRD in CDX2-associated protein complexes; and chromatin-IP-sequencing identifies CDX2-binding sites predominantly in genes up-regulated by CDX2. Compendium analyses of Cdx2- and the other TF-inducible ES cells suggest a central role of the POU5F1/SOX2/NANOG protein complex in a swift-acting control mechanism to down-regulate a common set of genes at the beginning of multi-lineage ES cell differentiations. These ES cell lines will be a valuable resource to study biological networks in ES cells and mice. Keywords: dose response design,genetic modification design,individual genetic characteristic design,reference design,replicate design MC1 mouse ES cells derived from 129S6/SvEvTac were cultured in DMEM with 15% FBS and LIF on feeder cells. Cells were electroporated with linearlized pMWROSATcH and selected by hygromycine B. Knock-in for ROSA-TET locus in ES[MC1R(20)] cells was confirmed by southern blotting. For exchange vectors, PCR amplified ORFs were subcloned into pZhcSfi that was modified to express His6-FLAG tagged protein and puromycin resistant gene. ES[MC1R(20)] cells (passage 17) cultured on feeder cells were co-transfected with sequence verified exchange vector and pCAGGS-Cre and selected by puromycin in the presence of doxycycline. Isolated clones were tested for Venus expression, hygromycin B susceptibility, transgene RNA expression, genotyping for Cre mediated integration, karyotyping, western blotting using anti-FLAG antibody (Sigma-Aldrich) and mycoplasma contamination. ES cells (passage 25) were plated onto gelatin-coated dish. Doxycycline was removed through washing 3 times with PBS at 3 hours intervals. Total RNA was isolated by TRIzol (Invitrogen) after 2 days. Cy3-CTP labeled sample targets were prepared with total RNA by Low RNA Input Fluorescent Linear Amplification Kit (Agilent). Cy5-CTP labeled reference target was produced from mixture of Stratagene Universal Mouse Reference RNA and MC1 cells RNA.

Project description:Sweat glands play a fundamental role in thermal regulation in man, but the molecular mechanism of their development remains unknown. To initiate analyses, we compared the model of Eda mutant Tabby mice, in which sweat glands were not formed, to wild-type mice. We inferred developmental stages and critical genes based on observations at 7 time points spanning embryonic, postnatal and adult life. In wild-type footpads, sweat gland germs were detected at E17.5. The coiling of secretory portions started at postnatal day 1 (P1), and sweat gland formation was essentially complete by P5. Consistent with a controlled morphological progression, expression profiling revealed stage-specific gene expression changes. Similar to the development of hair follicles the other major skin appendage controlled by EDA sweat gland induction and initial progression was accompanied by Eda-dependent up-regulation of the Shh pathway. During the further development of sweat gland secretory portions, Foxa1 and Foxi1, not at all expressed in hair follicles, were progressively up-regulated in wild-type but not in Tabby footpads. Upon completion of wild-type development, Shh declined to Tabby levels, but Fox family genes remained at elevated levels in mature sweat glands. The results provide a framework for the further analysis of phased downstream regulation of gene action, possibly by a signaling cascade, in response to Eda. This SuperSeries is composed of the following subset Series: GSE14870: Requirement for Shh and Fox family genes at different stages in sweat gland development (E15.5) GSE14871: Requirement for Shh and Fox family genes at different stages in sweat gland development (E16.5) GSE14872: Requirement for Shh and Fox family genes at different stages in sweat gland development (E17.5) GSE14873: Requirement for Shh and Fox family genes at different stages in sweat gland development (P1) GSE14874: Requirement for Shh and Fox family genes at different stages in sweat gland development (P3) GSE14876: Requirement for Shh and Fox family genes at different stages in sweat gland development (P5) GSE14877: Requirement for Shh and Fox family genes at different stages in sweat gland development (Adult) To define target genes of Eda during sweat gland development, we carried out microarray experiments with mouse footpads that from 7 developmental time points including E15.5, E16.5, E17.5, P1, P3, P5 and 8 weeks of wild-type and Tabby mice. Refer to individual Series

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Responsiveness of genes to manipulation of transcription factors in ES cells is associated with chromatin structure and tissue specificity

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Responsiveness of genes to manipulation of transcription factors in ES cells is associated with histone modifications and tissue specificity.

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