Dataset Information

MicroRNA expression profiling of human myeloid precursors

ABSTRACT: Hemopoiesis entails a series of hierarchically organized events that proceed throughout cell specification and terminates with cell differentiation. Commitment needs the transcription factors effort that, in concert with microRNAs, drives cell fate specification, answering to promiscuous patterns of gene expression by turning on lineage-specific genes and repressing alternate lineage transcripts. Therefore microRNAs and mRNAs cooperate to direct cell fate decisions. We obtained microRNAs profiles from human CD34+ hemopoietic progenitor cells and in-vitro differentiated erythroblasts, megakaryoblasts, monoblasts and myeloblasts precursors and we analyzed them together with the gene expression profiles of the same populations. We found that for most part of microRNAs specifically up-regulated in one single cell progeny an inverse correlation between microRNAs and down-regulated putative targets expression levels occurs. We chose hsa-mir-299-5p as a model to get further insights into the possible biological relevance of this microRNAs-mRNAs expression integrated analytical approach and we asked if the forced expression of a single lineage-specific microRNA is able to control the cell fate of CD34+ progenitors grown in multilineage culture conditions. Gain and loss of-function experiments established that mir-299-5p regulates hemopoietic progenitors fate modulating reciprocally megakaryocytic-granulocytic versus erythroid-monocytic differentiation and has at least two genuine targets, the transcription factors CTCF and SOX4.

ORGANISM(S): Homo sapiens

PROVIDER: GSE17586 | GEO | 2010/03/31

SECONDARY ACCESSION(S): PRJNA118517

REPOSITORIES: GEO

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Project description:Hemopoiesis entails a series of hierarchically organized events that proceed throughout cell specification and terminates with cell differentiation. Commitment needs the transcription factors effort that, in concert with microRNAs, drives cell fate specification, answering to promiscuous patterns of gene expression by turning on lineage-specific genes and repressing alternate lineage transcripts. Therefore microRNAs and mRNAs cooperate to direct cell fate decisions. We obtained microRNAs profiles from human CD34+ hemopoietic progenitor cells and in-vitro differentiated erythroblasts, megakaryoblasts, monoblasts and myeloblasts precursors and we analyzed them together with the gene expression profiles of the same populations. We found that for most part of microRNAs specifically up-regulated in one single cell progeny an inverse correlation between microRNAs and down-regulated putative targets expression levels occurs. We chose hsa-mir-299-5p as a model to get further insights into the possible biological relevance of this microRNAs-mRNAs expression integrated analytical approach and we asked if the forced expression of a single lineage-specific microRNA is able to control the cell fate of CD34+ progenitors grown in multilineage culture conditions. Gain and loss of-function experiments established that mir-299-5p regulates hemopoietic progenitors fate modulating reciprocally megakaryocytic-granulocytic versus erythroid-monocytic differentiation and has at least two genuine targets, the transcription factors CTCF and SOX4. CD34+ hematopoietic progenitor cells were transfected with the Amaxa Nucleofector Device, using the Human CD34 Cell Nucleofection Kit, accordingly to the manufacturer’s instructions (Amaxa Biosystem, Cologne, Germany), and 5µg of either the Pre-miR miRNA Precursor Molecule—Negative Control # 1 (NC1) or the hsa-mir-299-5p Pre-miR miRNA Precursor Molecule (299-5p) (Ambion, Austin, TX, USA) and pulsed with the program U-008. The dataset is composed of three independent paired experiment of 299-5p gain of-function (three hsa-299-5p Pre-miR miRNA Precursor Molecule nucleoporated samples and three paired Pre-miR miRNA Precursor Molecule—Negative Control # 1 transfected ones).

Project description:deBack2012 - Lineage Specification in Pancreas Development This model of two neighbouring pancreas precursor cells, describes the exocrine versus endocrine lineage specification process. To account for the tissue scale patterns, this couplet model has been extended to hundreds of coupled cells. This model is described in the article: On the role of lateral stabilization during early patterning in the pancreas de Back W., Zhou JX, Brusch L J. R. Soc. Interface 6 February 2013 vol. 10 no. 79 20120766 Abstract: The cell fate decision of multi-potent pancreatic progenitor cells between the exocrine and endocrine lineages is regulated by Notch signalling, mediated by cell–cell interactions. However, canonical models of Notch-mediated lateral inhibition cannot explain the scattered spatial distribution of endocrine cells and the cell-type ratio in the developing pancreas. Based on evidence from acinar-to-islet cell transdifferentiation in vitro, we propose that lateral stabilization, i.e. positive feedback between adjacent progenitor cells, acts in parallel with lateral inhibition to regulate pattern formation in the pancreas. A simple mathematical model of transcriptional regulation and cell–cell interaction reveals the existence of multi-stability of spatial patterns whose simultaneous occurrence causes scattering of endocrine cells in the presence of noise. The scattering pattern allows for control of the endocrine-to-exocrine cell-type ratio by modulation of lateral stabilization strength. These theoretical results suggest a previously unrecognized role for lateral stabilization in lineage specification, spatial patterning and cell-type ratio control in organ development. This model is hosted on BioModels Database and identified by: MODEL1211010000 . 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.

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MicroRNA expression profiling of human myeloid precursors

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