Project description:Chavez2009 - a core regulatory network of OCT4 in human embryonic stem cells A core OCT4-regulated network has been identified as a test case, to analyase stem cell characteristics and cellular differentiation. This model is described in the article: In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach. Chavez L, Bais AS, Vingron M, Lehrach H, Adjaye J, Herwig R BMC Genomics, 2009, 10:314 Abstract: BACKGROUND: The transcription factor OCT4 is highly expressed in pluripotent embryonic stem cells which are derived from the inner cell mass of mammalian blastocysts. Pluripotency and self renewal are controlled by a transcription regulatory network governed by the transcription factors OCT4, SOX2 and NANOG. Recent studies on reprogramming somatic cells to induced pluripotent stem cells highlight OCT4 as a key regulator of pluripotency. RESULTS: We have carried out an integrated analysis of high-throughput data (ChIP-on-chip and RNAi experiments along with promoter sequence analysis of putative target genes) and identified a core OCT4 regulatory network in human embryonic stem cells consisting of 33 target genes. Enrichment analysis with these target genes revealed that this integrative analysis increases the functional information content by factors of 1.3 - 4.7 compared to the individual studies. In order to identify potential regulatory co-factors of OCT4, we performed a de novo motif analysis. In addition to known validated OCT4 motifs we obtained binding sites similar to motifs recognized by further regulators of pluripotency and development; e.g. the heterodimer of the transcription factors C-MYC and MAX, a prerequisite for C-MYC transcriptional activity that leads to cell growth and proliferation. CONCLUSION: Our analysis shows how heterogeneous functional information can be integrated in order to reconstruct gene regulatory networks. As a test case we identified a core OCT4-regulated network that is important for the analysis of stem cell characteristics and cellular differentiation. Functional information is largely enriched using different experimental results. The de novo motif discovery identified well-known regulators closely connected to the OCT4 network as well as potential new regulators of pluripotency and differentiation. These results provide the basis for further targeted functional studies. This model is hosted on BioModels Database and identified by: MODEL1305010000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Chickarmane2006 - Stem cell switch reversible Kinetic modeling approach of the transcriptional dynamics of the embryonic stem cell switch. This model is described in the article: Transcriptional dynamics of the embryonic stem cell switch. Chickarmane V, Troein C, Nuber UA, Sauro HM, Peterson C PLoS Computational Biology. 2006; 2(9):e123 Abstract: Recent ChIP experiments of human and mouse embryonic stem cells have elucidated the architecture of the transcriptional regulatory circuitry responsible for cell determination, which involves the transcription factors OCT4, SOX2, and NANOG. In addition to regulating each other through feedback loops, these genes also regulate downstream target genes involved in the maintenance and differentiation of embryonic stem cells. A search for the OCT4-SOX2-NANOG network motif in other species reveals that it is unique to mammals. With a kinetic modeling approach, we ascribe function to the observed OCT4-SOX2-NANOG network by making plausible assumptions about the interactions between the transcription factors at the gene promoter binding sites and RNA polymerase (RNAP), at each of the three genes as well as at the target genes. We identify a bistable switch in the network, which arises due to several positive feedback loops, and is switched on/off by input environmental signals. The switch stabilizes the expression levels of the three genes, and through their regulatory roles on the downstream target genes, leads to a binary decision: when OCT4, SOX2, and NANOG are expressed and the switch is on, the self-renewal genes are on and the differentiation genes are off. The opposite holds when the switch is off. The model is extremely robust to parameter changes. In addition to providing a self-consistent picture of the transcriptional circuit, the model generates several predictions. Increasing the binding strength of NANOG to OCT4 and SOX2, or increasing its basal transcriptional rate, leads to an irreversible bistable switch: the switch remains on even when the activating signal is removed. Hence, the stem cell can be manipulated to be self-renewing without the requirement of input signals. We also suggest tests that could discriminate between a variety of feedforward regulation architectures of the target genes by OCT4, SOX2, and NANOG. This model is hosted on BioModels Database and identified by: MODEL7957907314 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Chickarmane2006 - Stem cell switch irreversible Kinetic modeling approach of the transcriptional dynamics of the embryonic stem cell switch. This model is described in the article: Transcriptional dynamics of the embryonic stem cell switch. Chickarmane V, Troein C, Nuber UA, Sauro HM, Peterson C PLoS Computational Biology. 2006; 2(9):e123 Abstract: Recent ChIP experiments of human and mouse embryonic stem cells have elucidated the architecture of the transcriptional regulatory circuitry responsible for cell determination, which involves the transcription factors OCT4, SOX2, and NANOG. In addition to regulating each other through feedback loops, these genes also regulate downstream target genes involved in the maintenance and differentiation of embryonic stem cells. A search for the OCT4-SOX2-NANOG network motif in other species reveals that it is unique to mammals. With a kinetic modeling approach, we ascribe function to the observed OCT4-SOX2-NANOG network by making plausible assumptions about the interactions between the transcription factors at the gene promoter binding sites and RNA polymerase (RNAP), at each of the three genes as well as at the target genes. We identify a bistable switch in the network, which arises due to several positive feedback loops, and is switched on/off by input environmental signals. The switch stabilizes the expression levels of the three genes, and through their regulatory roles on the downstream target genes, leads to a binary decision: when OCT4, SOX2, and NANOG are expressed and the switch is on, the self-renewal genes are on and the differentiation genes are off. The opposite holds when the switch is off. The model is extremely robust to parameter changes. In addition to providing a self-consistent picture of the transcriptional circuit, the model generates several predictions. Increasing the binding strength of NANOG to OCT4 and SOX2, or increasing its basal transcriptional rate, leads to an irreversible bistable switch: the switch remains on even when the activating signal is removed. Hence, the stem cell can be manipulated to be self-renewing without the requirement of input signals. We also suggest tests that could discriminate between a variety of feedforward regulation architectures of the target genes by OCT4, SOX2, and NANOG. This model is hosted on BioModels Database and identified by: MODEL7957942740 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Chickarmane2008 - Stem cell lineage - NANOG GATA-6 switch In this work, a dynamical model of lineage determination based upon a minimal circuit, as discussed in PMID: 17215298 , which contains the Oct4/Sox2/Nanog core as well its interaction with a few other key genes is discussed. This model is described in the article: A computational model for understanding stem cell, trophectoderm and endoderm lineage determination. Chickarmane V, Peterson C PloS one. 2008, 3(10):e3478 Abstract: BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/ PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4-Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6. CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state. This model is hosted on BioModels Database and identified by: MODEL8389825246 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Chickarmane2008 - Stem cell lineage determination In this work, a dynamical model of lineage determination based upon a minimal circuit, as discussed in PMID: 17215298 , which contains the Oct4/Sox2/Nanog core as well its interaction with a few other key genes is discussed. This model is described in the article: A computational model for understanding stem cell, trophectoderm and endoderm lineage determination. Chickarmane V, Peterson C PloS one. 2008, 3(10):e3478 Abstract: BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/ PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4-Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6. CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state. This model is hosted on BioModels Database and identified by: MODEL8390025091 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Here, we performed RNA-interactome capture (RIC) on nuclear fractions from human embryonic stem cells (hESCs). The poly(A)+ RNA-bound proteome was determined by UV light-mediated cross-linking (CL) of RNAs to proteins in living cells, followed by nuclei isolation, oligo(dT) purification of poly(A)-RNA-protein complexes, and mass spectrometry analysis of captured proteins. As a control, we applied a similar strategy to non-cross-linked (non-CL) samples. RIC was performed in four independent biological replicates. This data accompanies the manuscript: "Uncovering the RNA-binding protein landscape in the pluripotency network of human embryonic stem cells". Abstract: "Embryonic stem cell (ESC) self-renewal and cell-fate decisions are driven by a broad array of molecular signals. While transcriptional regulators have been extensively studied in human ESCs (hESCs), the extent to which RNA-binding proteins (RBPs) contribute to human pluripotency remains unclear. Here, we carry out a proteome-wide screen and identify 810 proteins that directly bind RNA in hESCs. We reveal that RBPs are preferentially expressed in hESCs and dynamically regulated during exit from pluripotency and early lineage specification. Moreover, we show that nearly 200 RBPs are affected by knockdown of OCT4, a master regulator of pluripotency, several dozen of which are directly bound by this factor. Intriguingly, over 20 percent of the proteins detected in our study are putative DNA- and RNA-binding proteins (DRBPs), among them key transcription factors (TFs). Using fluorescently labeled RNA and seCLIP (single-end enhanced crosslinking and immunoprecipitation) experiments, we discover that the pluripotency-associated STAT3 and OCT4 TFs interact with RNA in hESCs and confirm the direct binding of STAT3 to the conserved NORAD long-noncoding RNA. Taken together, our findings indicate that RBPs have a more widespread role in human pluripotency than previously appreciated, reinforcing the importance of post-transcriptional regulation in stem cell biology".

			Action	DRS
	SRR1784100_1.fastq.gz	Fastqsanger.gz
	SRR1784100_2.fastq.gz	Fastqsanger.gz
	SRR1784110_1.fastq.gz	Fastqsanger.gz
	SRR1784110_2.fastq.gz	Fastqsanger.gz
	SRR1784101_1.fastq.gz	Fastqsanger.gz

Dataset Information

Mus musculus

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets