Dataset Information

Three LIF-dependent signatures and gene clusters with atypical expression profiles, identified by transcriptome studies in mouse ES cells and early derivatives.

ABSTRACT:

Background

Mouse embryonic stem (ES) cells remain pluripotent in vitro when grown in the presence of the cytokine Leukaemia Inhibitory Factor (LIF). Identification of LIF targets and of genes regulating the transition between pluripotent and early differentiated cells is a critical step for understanding the control of ES cell pluripotency.

Results

By gene profiling studies carried out with mRNAs from ES cells and their early derivatives treated or not with LIF, we have identified i) LIF-dependent genes, highly expressed in pluripotent cells, whose expression level decreases sharply upon LIF withdrawal [Pluri genes], ii) LIF induced genes [Lifind genes] whose expression is differentially regulated depending upon cell context and iii) genes specific to the reversible or irreversible committed states. In addition, by hierarchical gene clustering, we have identified, among eight independent gene clusters, two atypical groups of genes, whose expression level was highly modulated in committed cells only. Computer based analyses led to the characterization of different sub-types of Pluri and Lifind genes, and revealed their differential modulation by Oct4 or Nanog master genes. Individual knock down of a selection of Pluri and Lifind genes leads to weak changes in the expression of early differentiation markers, in cell growth conditions in which these master genes are still expressed.

Conclusion

We have identified different sets of LIF-regulated genes depending upon the cell state (reversible or irreversible commitment), which allowed us to present a novel global view of LIF responses. We are also reporting on the identification of genes whose expression is strictly regulated during the commitment step. Furthermore, our studies identify sub-networks of genes with a restricted expression in pluripotent ES cells, whose down regulation occurs while the master knot (composed of OCT4, SOX2 and NANOG) is still expressed and which might be down-regulated together for driving cells towards differentiation.

SUBMITTER: Trouillas M

PROVIDER: S-EPMC2674464 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Three LIF-dependent signatures and gene clusters with atypical expression profiles, identified by transcriptome studies in mouse ES cells and early derivatives.

Trouillas Marina M Saucourt Claire C Guillotin Bertrand B Gauthereau Xavier X Ding Li L Buchholz Frank F Doss Michael Xavier MX Sachinidis Agapios A Hescheler Jurgen J Hummel Oliver O Huebner Norbert N Kolde Raivo R Vilo Jaak J Schulz Herbert H Boeuf Hélène H

BMC genomics 20090209

<h4>Background</h4>Mouse embryonic stem (ES) cells remain pluripotent in vitro when grown in the presence of the cytokine Leukaemia Inhibitory Factor (LIF). Identification of LIF targets and of genes regulating the transition between pluripotent and early differentiated cells is a critical step for understanding the control of ES cell pluripotency.<h4>Results</h4>By gene profiling studies carried out with mRNAs from ES cells and their early derivatives treated or not with LIF, we have identified ...[more]

PMID: 19203379

Similar Datasets

Project description:BackgroundThe abnormal expression of genes is an essential factor affecting the prognosis of cancer. RNA modification is a way of regulating post-transcriptional levels, including m6A, m5C, m1A RNA methylation. Studies have found that RNA methylation regulates tumorigenesis development and stem cell regeneration. However, there are few studies on lung adenocarcinoma. This study aims to explore the clinical value of RNA methylation for lung adenocarcinoma.MethodsWe summarized thirty-one RNA methylation regulators. The training set was obtained from The Cancer Genome Atlas (TCGA) database, and the test set was obtained from the Gene Expression Omnibus (GEO) database. The Wilcoxon test was used to analyze the expression of RNA methylation regulators. We constructed tumor subgroup models and risk models based on the expression of those regulators. Principal component analysis (PCA) and the receiver operating characteristic (ROC) confirmed the accuracy of the models. Real-time polymerase chain reaction (PCR) validates the results in vitro.ResultsMost RNA methylation regulators had distinct expressions in tumor tissues and adjacent tissues (P<0.05). All the models showed high predictive performance (AUC: 0.65-0.82), and the five-year survival of patients in each group was statistically different (P<0.05). The patients in the high-risk group were more likely to have a higher stage, more lymph node metastases, and distant metastases, showing a poor clinical outcome. Patients with high expression of NOP2 or HNRNP were more likely to have a poorly differentiated in vitro experiment.ConclusionsWith our study, we found that the expressions of most RNA methylation regulators were significantly different in cancer and para-cancerous tissues. Different molecular phenotypes constructed by RNA methylation regulators can be independent risk factors for the prognosis of lung adenocarcinoma. Our study demonstrates the critical role of RNA methylation in lung adenocarcinoma, and it is expected to supply a reference for the prognostic stratification and treatment strategy development of lung adenocarcinoma.

Dataset Information

Three LIF-dependent signatures and gene clusters with atypical expression profiles, identified by transcriptome studies in mouse ES cells and early derivatives.

Background

Results

Conclusion

Publications

Three LIF-dependent signatures and gene clusters with atypical expression profiles, identified by transcriptome studies in mouse ES cells and early derivatives.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets