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Homo sapiens
8 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
HnRNPLL was identified as a critical regulator of CD45 alternative splicing in a lentiviral shRNA screen. RNAi-mediated depletion of hnRNPLL eliminated the activation-induced induced transition from the CD45RA to the CD45RO isoform. HnRNPLL is induced during the process of T cell activation, raising the possibility that it regulates a broad program of alternative splicing in activated T cells. To test this possibility and to identify additional potential targets of hnRNPLL, we performed exon array analysis on RNA isolated from five cellular conditions: 1) activated peripheral CD4+ T cells, 2) peripheral CD4+ T cells infected with a control shRNA directed against GFP, 3) peripheral CD4+ T infected with an shRNA directed against hnRNPLL, 4) nave cord blood CD4+ T cells, and 5) cord blood CD4+ T cells that had been activated with anti-CD3 and anti-CD28 for 24 hours. The RNA was hybridized to Affymetrix human exon arrays and the hybridization signals were analyzed with XRAYTM software (Biotique). Using stringent filters for non-expressed probesets, we identified 132 genes that showed significant alternative exon usage (p<0.01) in response to hnRNPLL knockdown, but not in response to shGFP infection. Of these 132 genes, 36 also showed significant alternative exon usage in response to activation of cord blood cells, which results in an approximate 5-fold increase in hnRNPLL expression. We thus conclude that induction of hnRNPLL represents a mechanism by which cells can rapidly shift their transcriptomes during the process of T cell activation.
Publication Title
Regulation of CD45 alternative splicing by heterogeneous ribonucleoprotein, hnRNPLL.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
In order to identify genes with differential gene expression or alternative splicing between the groups LL-sh4, uninfected, and shGFP we study 6 hybridizations on the Human Exon 1.0 ST array using mixed model analysis of variance. 842 genes with significant gene expression differences between the groups and 1118 genes with significant exon-group interaction (a symptom of alternative splicing) were found, including 192 genes with both gene and possible splicing differences (p<0.01). Contingency table analysis of the set of studied genes and a dataset of known pathways and gene classifications revealed that the set of alternatively spliced and expressed genes were found to be significantly over-represented in groups of the GOMolFn, GOProcess, GOCellLoc, and Pathway classes (p<0.01).
Publication Title
Regulation of CD45 alternative splicing by heterogeneous ribonucleoprotein, hnRNPLL.
Sample Metadata Fields
No sample metadata fields
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GSE11832- Homo sapiens
- 2 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
In order to identify genes with differential gene expression or alternative splicing between the groups naive and activated we study 4 hybridizations on the Human Exon 1.0 ST array using mixed model analysis of variance. 1904 genes with significant gene expression differences between the groups and 1603 genes with significant exon-group interaction (a symptom of alternative splicing) were found, including 427 genes with both gene and possible splicing differences (p<0.01). Contingency table analysis of the set of studied genes and a dataset of known pathways and gene classifications revealed that the set of alternatively spliced and expressed genes were found to be significantly over-represented in groups of the GOMolFn, GOProcess, GOCellLoc, and Pathway classes (p<0.01).
Publication Title
Regulation of CD45 alternative splicing by heterogeneous ribonucleoprotein, hnRNPLL.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 14 Downloadable Samples
NextSeq 500
Description
We used RNA sequencing to characterize gene expression of dendritic cells from mouse lymph node that, based on LIPSTIC labeling, underwent interaction with CD4+ T cells. Overall design: Antigen pulsed dendritic cells (DCs) were transferred into recipient mice, followed by antigen specific CD4+ T cells. Forty-eight hours after T cell transfer, endogenous dendritic cells were isolated by facs sorting from mouse lymph node and analyzed based on their in vivo LIPSTIC labeling.
Publication Title
Monitoring T cell-dendritic cell interactions in vivo by intercellular enzymatic labelling.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Mus musculus
- 30 Downloadable Samples
- Affymetrix HT Mouse Genome 430A Array (htmg430a)
Description
Individual genetic variation affects gene expression and cell phenotype by acting within complex molecular circuits, but this relationship is still largely unknown. Here, we combine genomic and meso-scale profiling with novel computational methods to detect genetic variants that affect the responsiveness of gene expression to stimulus (responsiveness QTLs) and position them in circuit diagrams. We apply this approach to study individual variation in transcriptional responsiveness to three different pathogen components in the model response of primary bone marrow dendritic cells (DCs) from recombinant inbred mice strains. We show that reQTLs are common both in cis (affecting a single target gene) and in trans (pleiotropically affecting co-regulated gene modules) and are specific to some stimuli but not others. Leveraging the stimulus-specific activity of reQTLs and the differential responsiveness of their associated targets, we show how to position reQTLs within the context of known pathways in this regulatory circuit. For example, we find that a pleiotropic trans-acting genetic factor in chr1:129-165Mb affects the responsiveness of 35 anti-viral genes only during an anti-viral like stimulus. Using RNAi we uncover RGS16 the likely causal gene in this interval, and an activator of the antiviral response. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in other complex circuits in primary mammalian cells.
Publication Title
Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli.
Sample Metadata Fields
Age, Specimen part
View Samples- Mus musculus
- 8 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Hematopoietic stem and progenitor cells (Lineagelo ScaI+ c-Kit+) were sorted 4 weeks post pIpC injection. RNA was extracted using TRIZOL and RNEASY RNA extraction kit. RNA was then amplified using NUGEN Pico amplification kit, fragmented and hybridized on Mouse Expression Array 430 2.0. Signal normalization was performed by RMA method. Data were analyzed using GSEA across the complete list of genes ranked by signal-to-noise ratio.
Publication Title
Musashi-2 controls cell fate, lineage bias, and TGF-β signaling in HSCs.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 169 Downloadable Samples
- Affymetrix HT Human Genome U133A Array (hthgu133a)
Description
We defined the major transcriptional responses in primary human bronchial epithelial cells (HBECs) after either infection with influenza or treatment with relevant ligands. We used four different strategies, each highlighting distinct aspects of the response. (1) cells were infected with the wild-type PR8 influenza virus that can mount a complete replicative cycle. (2) cells were transfected with viral RNA (vRNA) isolated from influenza particles. This does not result in the production of viral proteins or particles and identifies the effect of RNA-sensing pathways (e.g., RIG-I.). (3) Cells were treated with interferon beta (IFNb), to distinguish the portion of the response which is mediated through Type I IFNs. (4) Cells were infected with a PR8 virus lacking the NS1 gene (DNS1). The NS1 protein normally inhibits vRNA- or IFNb-induced pathways, and its deletion can reveal an expanded response to infection.
Publication Title
A physical and regulatory map of host-influenza interactions reveals pathways in H1N1 infection.
Sample Metadata Fields
Specimen part, Disease, Time
View Samples- Homo sapiens
- 30 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
We analyzed the transcriptomes of human dendritic cells and macrophages derived from monocytes using MCSF + IL-4 + TNFa, or IL-34 + IL-4 + TNFa, or dendritic cells derived from monocytes using GMCSF + IL-4.
Publication Title
Aryl Hydrocarbon Receptor Controls Monocyte Differentiation into Dendritic Cells versus Macrophages.
Sample Metadata Fields
Specimen part, Treatment, Subject
View Samples- Homo sapiens
- 16 Downloadable Samples
- Illumina HiSeq 2500
Description
We performed single-cell RNA-seq on CD14+ monocytes isolated from the blood of healthy donors. Using the 10x chromium technology, we analyzed 425 and 431 cells from 2 individual donors. Overall design: Peripheral Blood Mononuclear Cells (PBMC) were prepared by centrifugation on a Ficoll gradient. Blood CD14+ monocytes were isolated from healthy donors' PBMC by positive selection using magnetic beads. Monocytes were 93-95% CD14+CD16- as assessed by flow cytometry. Cellular suspensions (1700 cells) were loaded on a 10X Chromium instrument (10X Genomics) according to manufacturer's protocol.
Publication Title
Aryl Hydrocarbon Receptor Controls Monocyte Differentiation into Dendritic Cells versus Macrophages.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 6 Downloadable Samples
- Illumina Genome Analyzer II
Description
Regulation of RNA levels is critical for the response to external stimuli and determined through the interplay between RNA production, processing and degradation. Despite the centrality of these processes, most global studies of RNA regulation do not distinguish their separate contributions and relatively little is known about how they are temporally integrated. Here, we combine metabolic labeling of RNA with advanced RNA quantification assays and computational modeling to estimate RNA transcription and degradation during the response of immune dendritic cells (DCs) to pathogens, a critical and tightly regulated step in innate immunity. We find that transcription regulation plays a major role in shaping most temporal changes in RNA levels, but that changes in degradation rate are important for shaping sharp ‘peaked’ responses. We find that transcription changes precede corresponding RNA changes by a small lag (15-30 min), which is shorter for induced than for repressed genes. Massively parallel sequencing of the entire RNA population – including non-polyadenylated transcripts – allows us to estimate RNA processing, and identify specific groups of transcripts, mostly cytokines and transcription factors, undergoing enhanced mRNA maturation. This suggests an additional role for splicing in regulating mRNA maturation. Our method provides a new quantitative approach to study key steps in the integrative process of RNA regulation. Overall design: Sequencing of 4sU-labeled RNA taken from a 7 samples time-series (one sample every 1 hour) during the response of DCs to LPS stimulation. 4-thiouridine was added 45 minutes prior to sample collection. Data presented here for six timepoints: 0, 1, 3-6 hrs. 2hr timepoint not included.
Publication Title
Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells.
Sample Metadata Fields
No sample metadata fields
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