A multi-scale approach reveals that NFkB cRel enforces a B-cell decision to divide.
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
SUBMITTER: Alexander Hoffmann
PROVIDER: E-GEOD-64156 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Shared Molecules
Only show the datasets with similarity scores above: 0.5
Threshold
0.5
Similar Datasets
Project description:We analysed a well-established fraction of mouse subcutaneous adipose-derived SVF cells that is generally considered to harbour adipose stem and progenitor cells (ASPCs). To study the molecular characteristics and the subpopulation structure of ASPCs, we performed three replicate scRNA-seq experiments. We collected Lin- (CD31- CD45- TER119-) CD29+ CD34+ SCA1+ cells from the mouse subcutaneous SVF of transgenic mice, in which red fluorescent protein (RFP) is induced in Dlk1-expressing cells upon feeding with tamoxifen. While CD29, CD34, and SCA1 are generally expected to enrich for stem cells, DLK1 has previously been suggested to specifically mark pre-adipocytes. The submission includes the raw data of all sequenced cells, while we only processed 208 high quality single cells. RFP status is indicated in the processed files.
2018-05-01 | E-MTAB-5802 | biostudies-arrayexpress
Project description:Long non-coding RNAs (lncRNAs) comprise a diverse class of transcripts that can regulate molecular and cellular processes in brain development and diseasee. LncRNAs exhibit cell type- and tissue-specific expression, but little is known about the expression and function of lncRNAs in the developing human brain. Here, we deeply profiled lncRNAs from polyadenylated and total RNA obtained from human neocortex at different stages of development and integrated this resource to analyze the transcriptomes of single cells. While lncRNAs were generally detected at low levels in whole tissues, single cell transcriptomics revealed that many lncRNAs are abundantly expressed in individual cells and are cell type-specific. Furthermore, we used CRISRPi to show that LOC646329, a lncRNA enriched in radial glia but detected at low abundance in tissues, regulates cell proliferation. The discrete and abundant expression of lncRNAs among individual cells has important implications for both their biological function and utility for distinguishing neural cell types. 16 Bulk Tissue Samples from GW13-23; 226 Single Cells from GW19.5-23.5 ------------------ bulk_tpm.polya.txt: bulk RNA-seq expression; using polyA full reference scell_ncounts.genes.thresh.txt: single cell RNA-seq expression; using polyA stringent reference; includes 50 GW16, GW21, GW21p3 cells previously analyzed (Pollen et. al. 2014) polya_RNA_stringent_ref.gtf: bulk RNA-seq polyA stringent transcriptome reference polya_RNA_full_ref.gtf: bulk RNA-seq polyA full transcriptome reference total_RNA_stringent_ref.gtf: bulk RNA-seq total stringent transcriptome reference total_RNA_full_ref.gtf: bulk RNA-seq total full transcriptome reference GW13_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW13_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW13_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW13_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_total_plus.bw: strand-specific bulk RNA-seq alignment signal
2016-03-28 | E-GEOD-71315 | biostudies-arrayexpress
Project description:We performed single-cell and bulk transcriptome profiling in two different human cell lines. We performed single-cell RNA sequencing in live and fixed cells. Single cell RNA sequencing of live and fixed cells, bulk RNA sequencing in two cell lines.
2015-03-01 | E-GEOD-66053 | biostudies-arrayexpress
Project description:In this study, we aimed to study the gene expression patterns at single cell level across the different cell cycle stages in mESC. We performed single cell RNA-Seq experiment on mESC that were stained with Hoechst 33342 and Flow cytometry sorted for G1, S and G2M stages of cell cycle. Single cell RNA-Seq was performed using Fluidigm C1 system and libraries were generated using Nextera XT (Illumina) kit.
2014-12-29 | E-MTAB-2805 | biostudies-arrayexpress
Project description:Dermal fibroblasts from human, rhesus macaque, mouse and rat, stimulated with dsRNA (poly I:C) in a time course of 0,4 and 8 hours, profiled using the Smart-seq2 protocol.<br>The innate immune response - the expression programme that is initiated once a pathogen is sensed - is known to be variable among responding cells, as well as to rapidly evolve in the course of mammal evolution. To study the transcriptional divergence and cell-to-cell variability of this response, we stimulated dermal fibroblast cells from two primates (human and macaque) and two rodents (mouse and rat) with dsRNA - a mimic of viral RNA that elicits a rapid innate immune response. Subsequently, we profiled the response using bulk RNA-seq, scRNA-seq and ChIP-seq across the four species and across different time points.
2018-07-06 | E-MTAB-6066 | biostudies-arrayexpress
Project description:Polycomb repressive complexes are important histone modifiers, which silence gene expression, yet there exists a subset of polycomb-bound genes actively transcribed by RNA polymerase II. To investigate the switching between polycomb-repressed and active states, we sequence mRNA from OS25 mouse embryonic stem cells cultured in serum/LIF. To validate our finding that polycomb modulates stochastic gene expression and transcriptional bursting, we perform knockout experiments and we sequence mRNA from Ring1A knockout (untreated) and Ring1A/B double knockout cells with constitutive Ring1A knockout and tamoxifen-inducible conditional Ring1B knockout.
2017-06-01 | E-MTAB-5661 | biostudies-arrayexpress
Project description:scRNA-seq analysis of RAW264.7 cells stimulated with 500ng/ml lipidA:Re595 for 3 hours.
2020-07-13 | E-MTAB-9219 | biostudies-arrayexpress
Project description:In this study, we evaluated clonal Waldenström macroglobulinemia cells with mapping of maturation stages of B cell lymphomagenesis concurrently with the innate and adaptive immune tumor microenvironment in active WM patients (newly diagnosed (NDWM, n = 19) and relapsed or relapsed/refractory (RRWM, n = 42) compared to 10 healthy donors (HD) by mass cytometry.
2022-12-13 | PXD038388 | Pride
Project description:Single-cell expression profiling by RNA-Seq promises to exploit cell-to-cell variation in gene expression to reveal regulatory circuitry governing cell differentiation and other biological processes. Here, we describe Monocle, a novel unsupervised algorithm for ordering cells by progress through differentiation that dramatically increases temporal resolution of expression measurements. This reordering unmasks switch-like changes in expression of key regulatory factors, reveals sequentially organized waves of gene regulation, and exposes regulators of cell differentiation. A functional screen confirms that a number of these regulators dramatically alter the efficiency of myoblast differentiation, demonstrating that single-cell expression analysis with Monocle can uncover new regulators even in well-studied systems. We selected primary human myoblasts as a model system of cell differentiation to investigate whether ordering cells by progress revealed new regulators of the process. We sequenced RNA-Seq libraries from each of several hundred cells taken over a time-course of serum-induced differentiation. Please note that this dataset is a single-cell RNA-Seq data set, and each cell comes from a capture plate. Thus, each well of the plate was scored and flagged with several QC criteria prior to library construction, which are provided as sample characteristics; CONTROL indicates that this library is a off-chip tube control library constructed from RNA of approximately 250 cells and 'DEBRIS' indicates that the well contained visible debris (and may or may not include a cell). Libraries marked DEBRIS thus cannot be confirmed to come from a single cell.
2014-03-23 | E-GEOD-52529 | biostudies-arrayexpress
Project description:The growth plate, which comprises sequentially differentiated cell layers, is a critical structure for bone elongation and regeneration. Although several key regulators in growth plate development have been identified using primarily genetic perturbation, the systematic understanding is still limited. Here we used single cell RNA-seq to interrogate gene expression profiles of 217 single cells from growth plates, and developed the bioinfromatics pipeline Sinova to de-novo reconstruct physiological growth plate development in both temporal and spatial high-resolution. Our unsupervised model not only confirmed prior knowledge but also enabled systematic discovery of novel genes, potential signal pathways and surface markers CD9/CD200 to precisely depict the development. Sinova further identified effective transcriptional factor portfolio directing growth plate maturation, which was cross-validated experimentally using an in-vitro EGFP-Col10a screening system. Our case demonstrated systematic reconstructing of molecular cascades of a developmental process from single-cell profiling, and the workflow is readily transferable to other physiological scenarios. 217 single-cell RNA-seq for cell isolated from mouse growth plate at postnatal day7
2016-06-14 | E-GEOD-76157 | biostudies-arrayexpress