MiR expression profiling of mouse hematopoietic stem and progenitor populations
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
SUBMITTER: Curt Civin
PROVIDER: E-GEOD-49170 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a comprehensive map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (~100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach identifies several interaction networks comprising a “stemness” signature in the most primitive hematopoietic stem cell (HSC) populations, as well as “myeloid” patterns associated with two branches of myeloid development. Six populations of mouse hematopoietic stem and progenitors have been analyzed (LT-HSC, ST-HSC, MPP, CMP, GMP, MEP). 2-3 replicates are included for each sample.
2013-07-24 | E-GEOD-49167 | biostudies-arrayexpress
Project description:Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a comprehensive map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (~100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach identifies several interaction networks comprising a “stemness” signature in the most primitive hematopoietic stem cell (HSC) populations, as well as “myeloid” patterns associated with two branches of myeloid development. Six populations of mouse hematopoietic stem and progenitors have been analyzed (LT-HSC, ST-HSC, MPP, CMP, GMP, MEP). 2-3 replicates are included for each sample.
2013-07-24 | E-GEOD-49169 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-02-20 | E-GEOD-52555 | biostudies-arrayexpress
Project description:Mammals express thousands of long noncoding (lnc) RNAs, a few of which are shown to function in tissue development. However, the entire repertoire of lncRNAs and the extent to which they regulate biological processes in different tissues and species are not defined. Indeed, most lncRNAs are not conserved between species, raising questions about function. We used RNA-Seq to identify lncRNAs in primary murine fetal liver erythroblasts expressing the lineage marker TER119, megakaryocytes (CD41+) cultured from embryonic day (E) 14.5 murine fetal liver and megakaryocyte erythroid progenitors (MEPs) isolated from mouse bone marrow. We identified 683 and 594 polyadenylated lncRNAs expressed in red blood cell (erythroid) precursors of mice and humans, respectively. More than one half of erythroid lncRNAs are un-annotated, emphasizing the opportunity for new discovery through studies of specialized cell types. We analyzed the expression of these identified lncRNAs in several hematopoietic compartments using a custom microarray to identify erythroid-specific lncRNAs that were robustly expressed in both fetal liver and adult erythroid cells as targets for knockdown. Over 90% of fetal liver erythroid lncRNAs detected using RNA-seq were expressed in adult erythroblasts measured on the microarray. Analysis of the murine erythroid lncRNA transcriptome indicates that ~75% arise from promoters and 25% from enhancers, many of which are regulated by the key erythroid transcription factors GATA1 and SCL/TAL1. Erythroid lncRNA expression is largely conserved among 8 different mouse strains, yet only 15% of mouse lncRNAs are expressed in humans and vice versa, reflecting dramatically greater species-specificity than coding genes. We investigated potential functions of 21 relatively abundant erythroid-specific murine lncRNAs (both conserved and non-conserved) by RNA interference in primary mouse erythroid precursors, and identified 7 whose knockdown inhibited features of terminal erythroid maturation including cell size reduction and enucleation. Strikingly, at least 6 of the 7 lncRNAs have no detectable expression in human erythroblasts, demonstrating that lack of conservation between mammalian species does not predict lack of function. These results reflect marked evolutionary differences between protein-coding genes and lncRNAs and indicate that the latter exert tissue- and species-specific roles in development. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A custom Agilent microarray was designed to interrogate expression levels of long noncoding RNAs identified using RNA-seq in several different hematopoietic progenitor and differentiated cell populations. LncRNA gene definitions and RNA-seq data used to identify long noncoding RNAs are deposited in GEO with the accession numbers GSE51667 and GSE40522 respectively. The Agilent eArray platform was used to customize the SurePrint G3 Mouse GE 8x60K microarray to add 3 custom-designed probes (60nt length) each against several categories of genes, namely pseudogene, genes with small RNA overlap, low stringency lncRNAs and high stringency lncRNAs . We interrogated 7 types of hematopoietic cells, HSC, CMP, MEP, GMP, early and late erythroblasts and granulocytes. Expression measurements were determined at least in duplicate for all samples and in triplicate for most samples.
2014-02-20 | E-GEOD-51892 | biostudies-arrayexpress
Project description:A critical problem in biology is understanding how cells choose between self-renewal and differentiation. To generate a comprehensive view of the mechanisms controlling early hematopoietic precursor self-renewal and differentiation, we used systems-based approaches and murine EML multipotential hematopoietic precursor cells as a primary model. EML cells give rise to a mixture of self-renewing Lin-SCA+CD34+ cells and partially differentiated non-renewing Lin-SCA-CD34- cells in a cell autonomous fashion. We identified and validated the HMG box protein TCF7 as a key regulator in this self-renewal/differentiation switch, and it operates in the absence of canonical Wnt signaling. We found that TCF7 is the most downregulated transcription factor when CD34+ cells switch into CD34- cells using RNA-Seq. We subsequently identified the target genes bound by TCF7 using ChIP-Seq. We show that TCF7 binds to Runx1 (Aml1) promoter region, and RUNX1 and TCF7 co-regulate. Gene Set Enrichment Analysis suggests that TCF7 primarily acts as a positive regulator of genes preferentially expressed in CD34+ cells. Consistent with this possibility, knocking-down TCF7 represses many up-regulated genes in Lin-CD34+ cells. Finally a network of up-regulated transcription factors of CD34+ cells which defines the self-renewing state was constructed. These studies in EML cells demonstrate fundamental cell-intrinsic properties of the switch between self-renewal and differentiation, and yield valuable insights for manipulating HSCs and other differentiating systems. The gene expression changes when TCF7 is knocked-down by shRNA in Lin-SCA+CD34+ cells were identified by microarray analysis of one control and two experimental samples.
2012-03-29 | E-GEOD-30068 | biostudies-arrayexpress
Project description:Rare dormant hematopoietic stem cells (dHSCs) reside at the top of the blood hierarchy harboring the highest long-term reconstitution capacity. Here, we present the global transcriptome of ex vivo isolated mouse multipotent dormant hematopoietic stem cells (dHSC), active HSCs (aHSCs) and multipotent progenitor cells (MPP1) as revealed by next-generation sequencing (RNA-seq) at the population level.
2017-05-18 | E-MTAB-4549 | biostudies-arrayexpress
Project description:The conserved RNA-binding protein Musashi1 (MSI1) has emerged as a key oncogenic factor in numerous solid tumors, including glioblastoma. However, its mechanism of action has not yet been established comprehensively. We set out to map its impact on the transcriptome in U251 cells using RNA-seq and iCLIP. Examination of gene expression and splicing changes upon KD of Musashi1 in U251 cells and link to iCLIP-identified Musashi1 RNA binding sites
2015-06-29 | E-GEOD-68800 | biostudies-arrayexpress
Project description:Hematopoietic stem cells (HSCs) must exhibit tight regulation of both self-renewal and differentiation to maintain homeostasis of the hematopoietic system as well as to avoid aberrations in growth that may result in leukemias or other disorders. In this study, we sought to understand the molecular basis of lineage determination, with particular focus on factors that influence megakaryocyte/erythrocyte-lineage commitment, in hematopoietic stem and progenitor cells. We used intracellular flow cytometry to identify two novel hematopoietic progenitor populations within the mouse bone-marrow cKit(+) Lineage (-) Sca1(+) (KLS) Flk2 (+) compartment that differ in their protein-level expression of GATA1, a critical megakaryocyte/erythrocyte-promoting transcription factor. GATA1-high repopulating cells exhibited the cell surface phenotype KLS Flk2(+ to int), CD150(int), CD105(+), cMPL(+), and were termed "FSE cells." GATA1-low progenitors were identified as KLS Flk2(+), CD150(-), and cMPL(-), and were termed "Flk(+) CD150(-) cells." FSE cells had increased megakaryocyte/platelet potential in culture and transplant settings and exhibited a higher clonal frequency of colony-forming unit-spleen activity compared with Flk(+) CD150(-) cells, suggesting functional consequences of GATA1 upregulation in promoting megakaryocyte and erythroid lineage priming. Activation of ERK and AKT signal-transduction cascades was observed by intracellular flow cytometry in long-term HSCs and FSE cells, but not in Flk(+) CD150(-) cells in response to stimulation with thrombopoietin, an important megakaryocyte-promoting cytokine. We provide a mechanistic rationale for megakaryocyte/erythroid bias within KLS Flk2(+) cells, and demonstrate how assessment of intracellular factors and signaling events can be used to refine our understanding of lineage commitment during early definitive hematopoiesis.
| S-EPMC4100980 | biostudies-literature
Project description:RNA debranching enzyme (hDBR1) is the only known enzyme to turn over lariat intron RNA during splicing. We compared the transcriptome differences between hDBR1 overexpressed and control Calu6 and 293T cells, to see its general effect on RNA splicing.
2017-01-25 | E-MTAB-5347 | biostudies-arrayexpress
Project description:Next-generation sequencing (NGS) technology applications like RNA-sequencing (RNA-seq) have dramatically expanded the potential for novel genomics discoveries, but the proliferation of various platforms and protocols for RNA-seq has created a need for reference data sets to help gauge the performance characteristics of these disparate methods. Here we describe the results of the ABRF-NGS Study on RNA-seq, which leverages replicate experiments across multiple sites using two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). These results show high (R2 >0.9) intra-platform consistency across test sites, high inter-platform concordance (R2 >0.8) for transcriptome profiling, and a large set of novel splice junctions observed across all platforms. Also, we observe that protocols using ribosomal RNA depletion can both salvage degraded RNA samples and also be readily compared to polyA-enriched fractions. These data provide a broad foundation for standardization, evaluation and improvement of RNA-seq methods. Two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). Please note that the samples were named following the ABRF-Platform-Site-Sample-Replicate# format. For example, ABRF-454-CNL-A-1 means Sample A was run on 454 platform at Cornell and this is the first replicate, and ABRF-454-CNL-A-2 means the same exact sample was ran with same machine at same location and is 2nd replicate.
2014-05-14 | E-GEOD-48033 | biostudies-arrayexpress