Long Non-coding RNAs Control Hematopoietic Stem Cell (HSC) Function (RNA-Seq)
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE53928 | GEO | 2014/12/30
SECONDARY ACCESSION(S): PRJNA233992
REPOSITORIES: GEO
Similar Datasets
Project description:Long non-coding RNAs (lncRNAs) have recently emerged as new players in gene expression regulation. Whether and how lncRNAs might control hematopoietic stem cell (HSC) function remains largely unknown. Here, we profiled the transcriptome of purified long-term HSCs by deep RNA-sequencing and identified thousands of un-annotated transcripts of which 323 are predicted to be lncRNAs. Comparison of their expression in differentiated lineages represented by B cells (B220+) and Granulocytes (Gr1+), revealed that 159 are likely to be HSC-specific. Knockdown of two such non-coding genes (LincHSC-1 and LincHSC-2) indicated that they regulate HSC lineage differentiation, possibly via targeting cell cycle regulators and chromatin modification enzymes. Taken together, we comprehensively identify lncRNAs in HSC and show to examples that play important roles in HSC function.
2015-03-13 | GSE66819 | GEO
Project description:Long non-coding RNAs (lncRNAs) have recently emerged as new players in gene expression regulation. Whether and how lncRNAs might control hematopoietic stem cell (HSC) function remains largely unknown. Here, we profiled the transcriptome of purified long-term HSCs by deep RNA-sequencing and identified thousands of un-annotated transcripts of which 323 are predicted to be lncRNAs. Comparison of their expression in differentiated lineages represented by B cells (B220+) and Granulocytes (Gr1+), revealed that 159 are likely to be HSC-specific. Knockdown of two such non-coding genes (LincHSC-1 and LincHSC-2) indicated that they regulate HSC lineage differentiation, possibly via targeting cell cycle regulators and chromatin modification enzymes. Taken together, we comprehensively identify lncRNAs in HSC and show to examples that play important roles in HSC function.
2014-12-30 | GSE63276 | GEO
Project description:During adult bone marrow hematopoiesis, extremely rare and dormant hematopoietic stem cells (HSCs) harbor the highest self-renewal activity within all blood cells. They give rise to active HSCs, which generate multipotent progenitors (MPPs) which differentiate into lineage-committed progenitors and subsequently mature cells. While HSCs are characterized by long-term self-renewal capacity, quiescence and multipotency, MPPs show steadily decreasing self-renewal activity, are cycling but are thought to maintain multipotency. To establish a comprehensive genome-wide landscape of expressed transcripts, we performed a quantitative transcriptome analysis by next-generation sequencing (RNA-seq) of seven ex vivo FACS-sorted mouse HSC/progenitor populations. Eleven-fold coverage of the genome was achieved, revealing quantification of > 27,000 mRNA species of which 589 long non-coding RNAs (lncRNAs) were quantified. A profile of 79 differentially expressed lncRNAs in HSC-MPPs was identified suggesting a role for these RNA species in HSC/progenitor biology. Expression clusters of transcription factors and cell adhesion molecules are identified between the different cell populations. Dormant HSCs, as identified by label-retaining assays, showed a highly differential expression profile compared to active HSCs. In addition to >200 differentially expressed cell surface receptors and lncRNAs, processes including metabolism, development, immune response, signaling (TGFb, Kit, senescence/autophagy) are distinct between the two types of HSCs. In addition, using whole cell proteome analysis of FACS-sorted HSCs and MPP1, >6,000 proteins were identified by quantitative tandem mass spectrometry. Quantification of these proteins confirmed the close relationship between these cell types also seen in their transcript profile and revealed processes such as energy metabolism, immune response and cell cycle to be modulated along early lineage progression. While MPP1/2 still show multilineage potential in reconstitution experiments, a strong lineage bias and low self-renewal potential is observed in mice reconstituted with MPP3/4. These functional differences are accompanied by complex changes in their transcriptome and is also revealed by principal component analysis. In summary, the global mRNA, lncRNA and proteome signatures uncovered here and which are complemented by functional assays, provide a comprehensive and searchable resource of the molecular make-up of the entire HSC/progenitor population present in the bone marrow. These data will provide the basis for a global understanding of stem cell biology in the adult blood system. The uploaded dataset corresponds to the quantitative proteomic comparison of HSC and MPP1, which was done in three biological replicates. Data analysis: MS raw data files were processed with MaxQuant (version 1.3.0.5) (Cox and Mann 2008). Enzyme specificity was set to trypsin/P and a maximum of two missed cleavages were allowed. Cysteine carbamidomethylation and methionine oxidation were selected as fixed and variable modifications, respectively. The derived peak list was searched using the built-in Andromeda search engine (version 1.3.0.5) in MaxQuant against the Uniprot mouse database (2013.02.20) containing 75,721 proteins to which 247 frequently observed contaminants as well as reversed sequences of all entries had been added. Initial maximal allowed mass tolerance was set to 20 ppm for peptide masses, followed by 6 ppm in the main search, and 0.5 Dalton for fragment ion masses. The minimum peptide length was set to six amino acid residues and three labeled amino acid residues were allowed. A 1% false discovery rate (FDR) was required at both the protein level and the peptide level. In addition to the FDR threshold, proteins were considered identified if they had at least one unique peptide. The protein identification was reported as an indistinguishable “protein group” if no unique peptide sequence to a single database entry was identified. The ‘match between runs’ was enabled for consecutive peptide fractions with a 2 minutes time window. The iBAQ algorithm was used for estimation of the abundance of different proteins within a single sample (proteome) (Schwanhausser 2011). For evaluation of differential protein expression between HSC and MPP1, statistical analysis was performed for the proteins quantified in all three replicates using the Limma package in R/Bioconductor (Gentleman 2004, Smyth 2004). After fitting a linear model to the data, an empirical Bayes moderated t-test was used for the protein ratios, which were weighted on log10(summed peptide intensities) in order to capture the effect that the statistical spread of unregulated proteins is much more focused for highly abundant proteins than for low abundance ones (Cox 2008). P-values were then adjusted for multiple testing with Benjamini and Hochberg's method and proteins with an adjusted p-value lower than 0.1 were considered to be differentially expressed between HSC and MPP1. Associated transcriptomics data has been deposited at ArrayExpress with accession E-MTAB-2262.
2014-08-21 | PXD000572 | Pride
Project description:Using bone marrow cells of GFP:Gfi1 knock in mice, we separated Gfi1-high and Gfi1-low expressing cells in the classical CD11b+, GR1-low monocytic cell fraction. We sorted CD11b+, GR1-low GFP:Gfi1-high and low cells as well as CD11b+, GR1-high granulocytes and CD11b-high, GR1-intermediate cells from Gfi1-knock-out mice for further analysis. We used Affymetrix Mouse Genome 430A 2.0 arrays (GPL8321) The study should determine how Gfi1 regulates the cell fate of monocytes/granulocytes in mice
2012-12-19 | E-GEOD-35970 | biostudies-arrayexpress
Project description:Six-weeks old (C57Bl6, Cx3cr1gfp/+) mice were intraperitonealy infected with a low number (1.104) of L. monocytogenes (EGDe strain) in exponential growth phase (bacteria were grown in BHI at 108/ml, and diluted 10.000x in PBS immediately before injection). Group of three mice were euthanized, before infection. Peritoneal cells were recovered by peritoneal lavage. Cells from individual mice were stained with antibodies to CD11b (PECy7), Gr1 (APC), NK1.1, B220 and CD3 (PE), and F4/80 (biotin-conjugated followed by streptavidinpacific blue) for sorting. Gr1- monocytes were purified as NK1.1- CD3- B220- CD11b+ F4/80low Gr1-, gfphigh; Gr1+ monocytes were purified as NK1.1- CD3- B220- CD11b+ F4/80low Gr1+, gfpint; and polymorphonuclear cells were purified as NK1.1- CD3- B220- CD11b+ F4/80- Gr1high, gfp-. 1.103 cells from each mice, time point, and phenotype were purified by facs sorting according to their phenotype. Samples were kept at 4°C before and during the sort. Cells were directly sorted in the SuperAmp Lysis Buffer (Miltenyi Biotec, Bergisch Gladbach, Germany) using a FACS Aria cell-sorter (BD biosciences).
2011-01-08 | E-MEXP-2545 | biostudies-arrayexpress
Project description:Using bone marrow cells of GFP:Gfi1 knock in mice, we separated Gfi1-high and Gfi1-low expressing cells in the classical CD11b+, GR1-low monocytic cell fraction. We sorted CD11b+, GR1-low GFP:Gfi1-high and low cells as well as CD11b+, GR1-high granulocytes and CD11b-high, GR1-intermediate cells from Gfi1-knock-out mice for further analysis. We used Affymetrix Mouse Genome 430A 2.0 arrays (GPL8321)
2012-12-19 | GSE35970 | GEO
Project description:Background: Long non-coding RNAs (lncRNAs) are increasingly implicated as gene regulators and may ultimately be more numerous than protein-coding genes in the human genome. Despite large numbers of reported lncRNAs, reference annotations are likely incomplete due to their lower and tighter tissue-specific expression compared to mRNAs. An unexplored factor potentially confounding lncRNA identification is inter-individual expression variability. Here, we characterize lncRNA natural expression variability in human primary granulocytes. Results: We annotate granulocyte lncRNAs and mRNAs in RNA-seq data from ten healthy individuals, identifying multiple lncRNAs absent from reference annotations, and use this to investigate three known features (higher tissue-specificity, lower expression, and reduced splicing efficiency) of lncRNAs relative to mRNAs. Expression variability was examined in seven individuals sampled three times at one or more than one month intervals. We show that lncRNAs display significantly more inter-individual expression variability compared to mRNAs. We confirm this finding in 2 independent human datasets by analyzing multiple tissues from the GTEx project and lymphoblastoid cell lines from the GEUVADIS project. Using the latter dataset we also show that including more human donors into the transcriptome annotation pipeline allows identification of an increasing number of lncRNAs, but minimally affects mRNA gene number. Conclusions: A comprehensive annotation of lncRNAs is known to require an approach that is sensitive to low and tight tissue-specific expression. Here we show that increased inter-individual expression variability is an additional general lncRNA feature to consider when creating a comprehensive annotation of human lncRNAs or proposing their use as prognostic or disease markers. We used PolyA+ RNA-seq data from human primary granulocytes of 10 healthy individuals to de novo annotate lncRNAs and mRNAs in this cell type and ribosomal depleted (total) RNA-seq data from seven of these individuals sampled three times to analyze lncRNA amd mRNA expression variability
2016-01-05 | E-GEOD-70390 | biostudies-arrayexpress
Project description:To figure out the role of long non-coding RNA LINP1 in cSCC and the underlying mechanism, RNA transcriptome sequencing was performed to globally characterize LINP1-regulated transcriptome changes. LINP1 knockdown by RNA interference in HSC-1 cells. HSC-1 cells treated with siNC served as control.
2023-03-22 | GSE197844 | GEO
Project description:Low-C was performed upon human cord-blood long-term hematopoietic stem cells (LT-HSC) and short-term hematopoietic stem cells (ST-HSC). This was used to demonstrate that chromatin conformation changes associated with LT-HSC activation are enriched in ST-HSC.
| EGAS00001004744 | EGA
Project description:Normal myeloid lineage cell populations (C57BL/6 mice, aged 4-10 weeks, male or female) with three distinct immunophenotypes were prospectively isolated and characterized. In preparation for FACS sorting, bone marrow cells were separated into c-kit+ and c-kit- fractions using an AutoMACS device. C-kit+ cells were further fractionated based on Gr1 and Mac1 expression, and absence of lineage antigen expression (B220, TER119, CD3, CD4, CD8 and IL7Rα), by cell sorting. C-kit+ Gr1+ Mac1lo/- and c-kit+ Gr1+ Mac1+ displayed cytologic features of undifferentiated hematopoietic cells or myeloblasts, whereas c-kit- Gr1+ Mac1+ cells were mature neutrophils.
2009-02-06 | GSE13693 | GEO