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accession-icon GSE29515
The transcriptional program controlled by Runx1 during early hematopoietic development
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

The transcriptional programme controlled by Runx1 during early embryonic blood development.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE29112
The transcriptional program controlled by Runx1 during early hematopoietic development (expression data)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Transcription factors have long been recognised as powerful regulators of mammalian development, yet it is largely unknown how individual key regulators operate within wider regulatory networks. Here we have used a combination of global gene expression and chromatin-immunoprecipitation approaches across four ES-cell-derived populations of increasing haematopoietic potential to define the transcriptional programme controlled by Runx1, an essential regulator of blood cell specification. Integrated analysis of these complementary genome-wide datasets allowed us to construct a global regulatory network model, which suggested that core regulatory circuits are activated sequentially during blood specification, but will ultimately collaborate to control many haematopoietically expressed genes. Using the CD41/integrin alpha 2b gene as a model, cellular and in vivo studies showed that CD41 is controlled by both early and late circuits in fully specified blood cells, but initiation of CD41 expression critically depends on a later subcircuit driven by Runx1. Taken together, this study represents the first global analysis of the transcriptional programme controlled by any key haematopoietic regulator during the process of early blood cell specification. Moreover, the concept of interplay between sequentially deployed core regulatory circuits is likely to represent a design principle widely applicable to the transcriptional control of mammalian development.

Publication Title

The transcriptional programme controlled by Runx1 during early embryonic blood development.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon SRP126788
Single-cell RNA-sequencing reveals distinct populations of glucagon-like peptide-1 producing cells in the mouse upper small intestine
  • organism-icon Mus musculus
  • sample-icon 288 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Enteroendocrine L-cells release hormones that control metabolism and appetite and are targets under investigation for the treatment of diabetes and obesity. Understanding L-cell diversity and expression profiles is critical for identifying target receptors that will translate into altered hormone secretion. We performed single cell RNA sequencing of mouse L-cells from the upper small intestine to distinguish cellular populations, revealing that L-cells form 3 major clusters: a group with typical characteristics of classical L-cells, including high expression of Gcg and Pyy; a cell type overlapping with Gip-expressing K-cells; and a unique cluster expressing Tph1 and Pzp that was predominantly located in duodenal villi and co-produced 5HT. Expression of G-protein coupled receptors differed between clusters, suggesting the cell types are differentially regulated, and would be differentially targetable. Our findings support the emerging concept that many enteroendocrine cell populations are highly overlapping, with individual cells producing a range of peptides previously assigned to distinct cell types. Overall design: Single cell RNA sequencing of mouse duodenal L-cells cells

Publication Title

Single-cell RNA-sequencing reveals a distinct population of proglucagon-expressing cells specific to the mouse upper small intestine.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE68529
Functionally distinct subsets of lineage-biased multipotent progenitors control blood production in normal and regenerative conditions
  • organism-icon Mus musculus
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

To identify the molecular characterisitics of parallel lineage-biased MPP populations arising from hematopoietic stem cells (HSC) we conducted genome-wide analyses of hematopoietic stem, progenitor and mature myeloid cell populations using Affymetrix Gene ST1.0 arrays.

Publication Title

Functionally Distinct Subsets of Lineage-Biased Multipotent Progenitors Control Blood Production in Normal and Regenerative Conditions.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE38681
Lyl-1 knockout vs wildtype Lymphoid Primed Multipotent Progenitors (LMPPs)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We compared gene expression differences in Lyl-1 knockout vs wildtype LMPPs

Publication Title

The transcription factor Lyl-1 regulates lymphoid specification and the maintenance of early T lineage progenitors.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP113285
RNA-sequencing of Mbd3-null and control haematopoietic stem cell and lymphoid progenitor cell populations
  • organism-icon Mus musculus
  • sample-icon 78 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To determine the role of Mbd3/NuRD in lymphopoiesis, gene expression in purified populations of Mbd3-deleted and control lymphoid progenitor cells was analysed using RNA-seq. Overall design: Mbd3-deficient and control lymphoid progenitors were isolated from mouse bone marrow by flow cytometry, including haematopoietic stem cells (HSCs), lymphoid-primed multipotent progenitors (LMPPs), all-lymphoid progenitors (ALPs) and B cell-biased lymphoid progenitors (BLPs). RNA-seq was performed on 100 HSCs or 150 cells from the other populuations, using the previously described smartseq2 protocol for RNA-seq of small numbers of cells (Picelli et al. (2014) Nature protocols 9:171).

Publication Title

Mbd3/NuRD controls lymphoid cell fate and inhibits tumorigenesis by repressing a B cell transcriptional program.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Subject

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accession-icon SRP093722
Molecular reprogramming of granulocyte/macrophage progenitor (GMP) clusters upon 5-Fluorouracil (5-FU) treatment
  • organism-icon Mus musculus
  • sample-icon 574 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA Seq and bioinformatic analysis are used to study what processes are important for the molecular reprogramming of GMPs after 5-FU treatment. Samples were collected at different time points (0, 8, 10, 12 and 14 days post treatment) Overall design: Single cell RNA sequencing of GMP cells upon 5-FU treatment

Publication Title

Myeloid progenitor cluster formation drives emergency and leukaemic myelopoiesis.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject, Time

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accession-icon SRP006435
RNA sequencing reveals two major classes of gene expression levels in metazoan cells
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprising of lowly expressed and putatively non-functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. Similar observations are made in other data sets, including sources such as Drosophila. Overall design: RNA-seq data of two biological replicates of murine Th2 cells.

Publication Title

Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP159572
The pluripotency factor NANOG controls primitive hematopoiesis and directly regulates Tal1.
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Progenitors of the first hematopoietic cells in the mouse arise in the early embryo from Brachyury-positive multipotent cells in the posterior-proximal region of the epiblast, but the mechanisms that specify primitive blood cells are still largely unknown. Pluripotency factors maintain uncommitted cells of the blastocyst and embryonic stem cells in the pluripotent state. However, little is known about the role played by these factors during later development, despite their being expressed in the postimplantation epiblast. Using a dual transgene system for controlled expression at postimplantation stages, we found that Nanog blocks primitive hematopoiesis in the gastrulating embryo, resulting in a loss of red blood cells and downregulation of erythropoietic genes. Accordingly, Nanog deficient embryonic stem cells are prone to erythropoietic differentiation. Moreover, Nanog expression in adults prevents the maturation of erythroid cells. By analysis of previous data for NANOG binding during stem cell differentiation and CRISPR/Cas9 genome editing, we found that Tal1 is a direct NANOG target. Our results show that Nanog regulates primitive hematopoiesis by directly repressing critical erythroid lineage specifiers. Overall design: MEPs mRNA profiles of adult mice Nanog-tg treated and untreated with doxycycline were generated by deep sequencing, in triplicate, using Illumina GAIIx.

Publication Title

The pluripotency factor NANOG controls primitive hematopoiesis and directly regulates <i>Tal1</i>.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP047290
Molecular signatures of heterogeneous stem cell populations are resolved by linking single cell functional assays to single cell gene expression
  • organism-icon Mus musculus
  • sample-icon 96 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The discovery of significant heterogeneity in the self-renewal durability of adult haematopoietic stem cells (HSCs) has challenged our understanding of the molecules involved in population maintenance throughout life. Gene expression studies in bulk populations are difficult to interpret since multiple HSC subtypes are present and HSC purity is typically less than 50% of the input cell population. Numerous groups have therefore turned to studying gene expression profiles of single HSCs, but again these studies are limited by the purity of the input fraction and an inability to directly ascribe a molecular program to a durable self-renewing HSC. Here we combine single cell functional assays with flow cytometric index sorting and single cell gene expression assays to gain the first insight into the gene expression program of HSCs that possess durable self-renewal. This approach can be used in other stem cell systems and sets the stage for linking key molecules with defined cellular functions. Overall design: single-cell RNA-Seq of haematopoietic stem cells

Publication Title

Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations.

Sample Metadata Fields

No sample metadata fields

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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