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GSE40452
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
- 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
View Samples- Mus musculus
- 2 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Analysis of baseline gene expression in bone marrow derived dendritic cells (BMDC) from female CBA/J (CBA) and C57BL/6 (BL/6) mice. Results provide insight into strain-dependent differences in gene expression.
Publication Title
CD209a expression on dendritic cells is critical for the development of pathogenic Th17 cell responses in murine schistosomiasis.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 656 Downloadable Samples
- IlluminaHiSeq2500
Description
We introduced genome-wide pooled CRISPR-Cas9 libraries into primary mouse dendritic cells (DCs) to identify genes that control the induction of tumor necrosis factor (TNF) by bacterial lipopolysaccharide (LPS), a key process in the host response to pathogens, mediated by the TLR4 pathway. We found many of the known regulators of TLR4 signaling, as well as dozens of previously unknown candidates that we validated. Overall design: We used stain base phenotype (staining for TNF) in order to search for negative and positive regulators of LPS response in differentiated BMDCs
Publication Title
A Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 28 Downloadable Samples
- Illumina HiSeq 2500
Description
Protein expression is regulated by production and degradation of mRNAs and proteins, but their specific relationships remain unknown. We combine measurements of protein production and degradation and mRNA dynamics to build a quantitative genomic model of the differential regulation of gene expression in LPS stimulated mouse dendritic cells. Changes in mRNA abundance play a dominant role in determining most dynamic fold changes in protein levels. Conversely, the preexisting proteome of proteins performing basic cellular functions is remodeled primarily through changes in protein production or degradation, accounting for over half of the absolute change in protein molecules in the cell. Thus, the proteome is regulated by transcriptional induction of novel cellular functions and remodeling of preexisting functions through the protein life cycle. Overall design: Mouse primary dendritic cells were treated with LPS or mock stimulus and profiled over a 12-hour time course. Cells were grown in M-labeled SILAC media, which was replaced with H-labeled SILAC media at time 0. Aliquots were taken at 0, 0.5, 1, 2, 3, 4, 5, 6, 9, and 12 hours post-stimulation and added to equal volumes of a master mix of unlabeled (L) cells for the purpose of normalization. RNA-Seq was performed at 0, 1, 2, 4, 6, 9, and 12 hours post-stimulation.
Publication Title
Immunogenetics. Dynamic profiling of the protein life cycle in response to pathogens.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 9 Downloadable Samples
- Illumina Genome Analyzer IIx
Description
Dynamic binding of transcription factors to DNA elements specifies gene expression and cell fate, in both normal physiology and disease. To date, our understanding of mammalian gene regulation has been hampered by the difficulty of directly measuring in vivo binding of large numbers of transcription factors to DNA. Here, we develop a high-throughput indexed Chromatin ImmunoPrecipitation (iChIP) method coupled to massively parallel sequencing to systematically map protein-DNA interactions. We apply iChIP to reconstruct the physical regulatory landscape of a mammalian cell, by building genome-wide binding maps for 29 transcription factors (TFs) and chromatin marks at four time points following stimulation of primary dendritic cells (DCs) with pathogen components. Using over 180,000 TF-DNA interactions in these maps, we derive an initial dynamic physical model of a mammalian cell regulatory network. Our data demonstrates that transcription factors vary substantially in their binding dynamics, genomic localization, number of binding events, and degree of interaction with other factors. Further, many of the TF-DNA interactions at stimulus-activated genes are established during differentiation and maintained in a poised state. Functionally, the TFs are organized in a hierarchy of different types: Cell differentiation factors bind most of the genes and remain largely unchanged during the stimulation. A second set of TFs bind already in the un-stimulated and preferentially target induced genes. A third set consists of TF that bind mainly after the stimuli and target specific gene functions. Together these factors determine the magnitude and timing of stimulus induced gene expression. Our method, which allowed us to map routinely temporal binding profiles of dozens of TFs, provides a foundation for future understanding of the mammalian regulatory code. Overall design: A study of dynamic binding of transcription factors in an immune cell following pathogen stimulation
Publication Title
A high-throughput chromatin immunoprecipitation approach reveals principles of dynamic gene regulation in mammals.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 36 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Organophosphorus compounds may induce neurotoxicity through mechanisms other than the cholinergic pathway, which need to be unraveled by a comprehensive and systematic approach such as genome-wide gene expression analysis.
Publication Title
Toxicogenomic studies of human neural cells following exposure to organophosphorus chemical warfare nerve agent VX.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus, Homo sapiens
- 22 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Cross-species comparative gene expression profiling was performed to identify differentially expressed genes conserved in aggressive B lymphomas.
Publication Title
Identification of candidate B-lymphoma genes by cross-species gene expression profiling.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 20 Downloadable Samples
- IlluminaHiSeq1000
Description
Transcriptome analysis by RNAseq of leukemia model promoted by MLL-Af4 or MLL-AF9 fusion proteins. We find each fusion protein promotes a specific gene signature correlating to those identified in patients Overall design: Human CD34+ hematopoietic stem and progenitor cells were transduced with retrovirus expressing MLL-Af4 or MLL-AF9. Transduced cells were transplanted into immunodeficient mice to induce lymphoid leukemia or placed in myeloid in vitro culture. CD19+ lymphoid leukemia cells (3 AF9, 6 Af4), control health CD19+CD34+ proB cells (n=3) and 4 pairs of Af4 and AF9 CD33+CD19- myeloid culture cells were collected for RNA-seq
Publication Title
Instructive Role of MLL-Fusion Proteins Revealed by a Model of t(4;11) Pro-B Acute Lymphoblastic Leukemia.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 17 Downloadable Samples
- IlluminaHiSeq2000
Description
Lung cancer is the leading cause of cancer related mortality worldwide, with non-small cell lung cancer (NSCLC) as the most prevalent form. Despite advances in treatment options including minimally invasive surgery, CT-guided radiation, novel chemotherapeutic regimens, and targeted therapeutics, prognosis remains dismal. Therefore, further molecular analysis of NSCLC is necessary to identify novel molecular targets that impact prognosis and the design of new-targeted therapies. In recent years, tumor “activated/reprogrammed” stromal cells that promote carcinogenesis have emerged as potential therapeutic targets. However, the contribution of stromal cells to NSCLC is poorly understood. Here, we show increased numbers of bone marrow (BM)-derived hematopoietic cells in the tumor parenchyma of NSCLC patients compared with matched adjacent non-neoplastic lung tissue. By sorting specific cellular fractions from lung cancer patients, we compared the transcriptomes of intratumoral myeloid compartments within the tumor bed with their counterparts within adjacent non-neoplastic tissue from NSCLC patients. The RNA sequencing of specific myeloid compartments (immature monocytic myeloid cells and polymorphonuclear neutrophils) identified differentially regulated genes and mRNA isoforms, which were inconspicuous in whole tumor analysis. Genes encoding secreted factors, including osteopontin (OPN), chemokine (C-C motif) ligand 7 (CCL7) and thrombospondin 1 (TSP1) were identified, which enhanced tumorigenic properties of lung cancer cells indicative of their potential as targets for therapy. This study demonstrates that analysis of homogeneous stromal populations isolated directly from fresh clinical specimens can detect important stromal genes of therapeutic value. Overall design: We sorted pure populations of the immature monocytic myeloid cells (IMMCs), neutrophils (Neu), and epithelial cells (Epi) from tumors and adjacent lung tissues of stage I-III lung adenocarcinoma patients. RNA samples (totally 17 samples) were sequenced: from tumor IMMC (n=3), Neu (n=2), Epi (n=2); from adjacent lung IMMC (n=3), Neu (n=4), Epi (n=3).
Publication Title
Identification of Reprogrammed Myeloid Cell Transcriptomes in NSCLC.
Sample Metadata Fields
No sample metadata fields
View Samples