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SRP041767
Mus musculus
12 Downloadable Samples
Illumina HiSeq 2000
Description
Purpose: Our lab has previously shown that Scleraxis (Scx) is require for proper valve development in vivo. In order to fully explore gene networks regulated by Scx during the vital stages of valve remodeling , high throughput RNA-squencing was performed. Results:There were a total of 18,810 genes were detected. A total of 864 genes were differentially expressed Scx null AVC regions: 645 being upregulated and 217 downregulated. Overall design: In this data set, we include expression data from atrioventricular canal (AVC) regions from Scx null and wild-type littermate controls at embryonic day 15.5. A total of 6 samples were analyzed; 3 valve regions from E15.5 Scx-/- mice, and 3 from E15.5 Scx+/+ wild-type littermate controls. Differential expression read counts are ranked based on p-value (<0.05).
Publication Title
RNA-seq analysis to identify novel roles of scleraxis during embryonic mouse heart valve remodeling.
Sample Metadata Fields
No sample metadata fields
View Samples- Arabidopsis thaliana
- 9 Downloadable Samples
Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
This experiment was set up in order to identify the (direct) transcriptional targets of the Ethylene Response Factor 115 (ERF115) transcription factor. Because ERF115 expression occurs in quiescent center (QC) cells and strong effects on the QC cells were observed in ERF115 overexpression plants, root tips were harvested for transcript profiling in order to focus on root meristem and QC specific transcriptional targets.
Publication Title
ERF115 controls root quiescent center cell division and stem cell replenishment.
Sample Metadata Fields
Age, Specimen part
View Samples- Mus musculus
- 12 Downloadable Samples
- Illumina Genome Analyzer
Description
Glucocorticoid resistance (GCR) is defined as an unresponsiveness to the anti-inflammatory properties of glucocorticoids (GCs) and their receptor, the glucocorticoid receptor (GR). It is a serious problem in the management of inflammatory diseases and occurs frequently. The strong pro-inflammatory cytokine TNF induces an acute form of GCR, not only in mice, but also in several cell lines, e.g. in the hepatoma cell line BWTG3, as evidenced by impaired Dexamethasone (Dex)-induced GR-dependent gene expression. We report that TNF has a significant and broad impact on the transcriptional performance of GR, but no impact on nuclear translocation, dimerization or DNA binding capacity of GR. Proteome-wide proximity-mapping (BioID), however, revealed that the GR interactome is strongly modulated by TNF. One GR cofactor that interacts significantly less with the receptor under GCR conditions is p300. NF?B activation and p300 knockdown both reduce transcriptional output of GR, whereas p300 overexpression and NF?B inhibition revert TNF-induced GCR, which is in support of a cofactor reshuffle model. This hypothesis is supported by FRET studies. This mechanism of GCR opens new avenues for therapeutic interventions in GCR diseases Overall design: Examination of GR induced gene expression in 4 conditions (1 control: NI and 3 treated: DEX, TNF, TNFDEX) starting from 3 biological replicates
Publication Title
TNF-α inhibits glucocorticoid receptor-induced gene expression by reshaping the GR nuclear cofactor profile.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Subject
View Samples- Homo sapiens
- 6 Downloadable Samples
- IlluminaHiSeq2000
Description
To understand how haploinsufficiency of progranulin (PGRN) protein causes frontotemporal dementia (FTD), we created induced pluripotent stem cells (iPSC) from patients carrying the GRNIVS1+5G>C mutation (FTD-iPSCs). FTD-iPSCs were fated to cortical neurons, the cells most affected in FTD and known to express PGRN. Although generation of neuroprogenitors was unaffected, their further differentiation into neurons, especially CTIP2-, FOXP2- or TBR1-TUJ1 double positive cortical neurons, was significantly decreased in FTD-neural progeny. Zinc finger nuclease-mediated introduction of PGRN cDNA into the AAVS1 locus corrected defects in cortical neurogenesis, demonstrating that PGRN haploinsufficiency causes inefficient cortical neuron generation. RNAseq analysis confirmed reversal of altered gene expression profile following genetic correction. Wnt signaling pathway, one of the top defective pathways in FTD-iPSC-derived neurons coupled with its reversal following genetic correction, makes it an important candidate. Therefore, we demonstrate for the first time that PGRN haploinsufficiency hampers corticogenesis in vitro. Overall design: We profiled 6 samples: two biological replicates for 3 conditions. Condition 1 consists of neuronal progeny derived from human Embryonic Stem Cells. Condition 2 consists of neuronal progeny derived from induced pluripotent stem cells generated from patients carrying PGRN mutation. Condition 3 consists of neuronal progeny derived from induced pluripotent stem cells generated from patients carrying PGRN mutation, genetically modified to correct the PGRN defect.
Publication Title
Restoration of progranulin expression rescues cortical neuron generation in an induced pluripotent stem cell model of frontotemporal dementia.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 6 Downloadable Samples
- Illumina HiSeq 2000
Description
We sequenced mRNA from 6 samples of FACsorted telencephalons from E14.5 Sip1|Nkx2-1 knockout and WT|Nkx2-1 control mouse embryos to find differentially expressed genes in the absence of the transcription factor Sip1. Overall design: Examination of mRNA levels in 3 control and 3 Sip1|Nkx2-1 knockout samples
Publication Title
Directed migration of cortical interneurons depends on the cell-autonomous action of Sip1.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Homo sapiens
- 12 Downloadable Samples
- IlluminaHiSeq2000
Description
Genetic studies in T-cell acute lymphoblastic leukemia have uncovered a remarkable complexity of oncogenic and loss-of-function mutations. Amongst this plethora of genetic changes, NOTCH1 activating mutations stand out as the most frequently occurring genetic defect, identified in more than 50% of T-cell acute lymphoblastic leukemias, supporting an essential driver role for this gene in T-cell acute lymphoblastic leukemia oncogenesis. In this study, we aimed to establish a comprehensive compendium of the long non-coding RNA transcriptome under control of Notch signaling. For this purpose, we measured the transcriptional response of all protein coding genes and long non-coding RNAs upon pharmacological Notch inhibition in the human T-cell acute lymphoblastic leukemia cell line CUTLL1 using RNA-sequencing. Similar Notch dependent profiles were established for normal human CD34+ thymic T-cell progenitors exposed to Notch signaling activity in vivo. In addition, we generated long non-coding RNA expression profiles (array data) from GSI treated T-ALL cell lines, ex vivo isolated Notch active CD34+ and Notch inactive CD4+CD8+ thymocytes and from a primary cohort of 15 T-cell acute lymphoblastic leukemia patients with known NOTCH1 mutation status. Integration of these expression datasets with publically available Notch1 ChIP-sequencing data resulted in the identification of long non-coding RNAs directly regulated by Notch activity in normal and malignant T-cell context. Given the central role of Notch in T-cell acute lymphoblastic leukemia oncogenesis, these data pave the way towards development of novel therapeutic strategies that target hyperactive Notch1 signaling in human T-cell acute lymphoblastic leukemia. Overall design: CUTLL1 cell lines were treated with Compound E (GSI) or DMSO (solvent control). Cells were collected 12 h and 48 h after treatment. This was performed for 3 replicates. RNA-sequencing was performed on these samples.
Publication Title
The Notch driven long non-coding RNA repertoire in T-cell acute lymphoblastic leukemia.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 15 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
The goal of this study was to gain insight into the molecular heterogeneity of capillary endothelial cells derived from different organs by microarray profiling of freshly isolated cells and identify transcription factors that may determine the specific gene expression profile of endothelial cells from different tissues. The study focused on heart endothelial cells and presents a validated signature of 31 genes that are highly enriched in heart endothelial cells. Within this signature 5 transcription factors were identified and the optimal combination of these transcription factors was determined for specification of the heart endothelial fingerprint.
Publication Title
Meox2/Tcf15 heterodimers program the heart capillary endothelium for cardiac fatty acid uptake.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 15 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers.
Sample Metadata Fields
Treatment
View Samples- Homo sapiens
- 15 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
8 neuroblastoma (NB) cell lines (CLB-GA, IMR-32, SH-SY5Y, N206, CHP-902R, LAN-2, SK-N-AS, SJNB-1) were profiled on the Affymetrix HGU-133plus2,0 platform before and after treatment with DAC (2'-deoxy-5-azacytidine) to investigate the influence on expression after inhibiting DNA-methylation
Publication Title
Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers.
Sample Metadata Fields
Treatment
View Samples- Homo sapiens
- 24 Downloadable Samples
- Illumina HiSeq 2500
Description
Purpose: The goal of this study is to identify host genes whose expression is perturbed in primary CD4+ T cells by histone deacetylase (HDAC) inhibitors (HDACi) SAHA and RMD, which have different potencies and specificities for various HDACs. The study aims to evaluate the effects of SAHA and RMD that may promote or inhibit reactivation of HIV provirus out of latency. Methods: Peripheral blood mononuclear cells were collected from 4 HIV-seronegative donors. CD4+ T cells were isolated and utilized to generate an in vitro model of latent HIV infection (model developed in the Spina laboratory and previously described in Spina et al., 2013). Mock-infected cells were cultured in parallel to evaluate effects of SAHA and RMD that may be dependent on the exposure of cells to virus. Following generation of the model, cells were treated with SAHA, RMD or their solvent dimethyl sulfoxide (DMSO) for 24 hours. Mock-infected cells were treated in parallel. The experiment had 4 biological replicates, 6 conditions for each, for a total of 24 samples. ERCC spikes (Thermo Fisher Scientific, Inc.) were added to cell lysates based on cell number in each sample (10 ul of 1:800 dilution per million cells). Mix 1 was used for DMSO- and mix 2 for SAHA- and RMD-treated cells. After all samples were collected, RNA was extracted and subjected to deep sequencing by Expression Analysis, Inc. Sequence reads that passed quality filters were mapped using Tophat (human genome) or Bowtie (ERCC spikes and HIV) and counted using HTSeq. ERCC spikes with the same concentration in mixes 1 and 2 were utilized to remove unwanted technical variation. Any human gene which did not achieve at least 1 count per million reads in at least 4 samples or any ERCC that did not achieve at least 5 reads in at least 4 samples was discarded. Differential gene expression analysis was performed using library EdgeR in Bioconductor R. National Center for Biotechnology Information (NCBI) HIV-1 Human Interaction Database was then searched for genes that have been implicated in controlling HIV latency. EdgeR output was used to extract expression information of the genes of interest from the NCBI database to identify genes implicated in HIV latency that were modulated by SAHA and RMD. The resulting lists were manually curated to verify relevance to HIV latency, using the Description column of the NCBI database, as well as available PubMed references. Results: Using a custom built data analysis pipeline, ~100 million reads per sample were mapped to the human genome (build hg38). After applying filtering criteria, 16058 human transcripts, 19 ERCC spikes transcripts, and HIV NL4-3 transcripts were identified with the Tophat/Bowtie and HTSeq workflow. Differential expression analysis was performed between SAHA or RMD-treated and DMSO-treated cells. In addition, differential modulation of gene expression by SAHA and RMD in the model of HIV latency and mock-infected cells was assessed using EdgeR. In mock-infected cells, SAHA upregulated 3,971 genes and downregulated 2,940 genes; RMD upregulated 5,068 genes and downregulated 4,050 genes. In the model of HIV latency, SAHA upregulated 3,498 genes and downregulated 2,904 genes; RMD upregulated 5,116 genes and downregulated 4,053 genes (FDR < 0.05). SAHA modulated 6, and RMD 11 genes differentially between mock-infected cells and the model of HIV latency. Following search of the NCBI HIV-1 Human Interaction Database, 27 genes upregulated and 29 downregulated in common between SAHA and RMD were found to be relevant to regulation of HIV latency; 31 were up- and 32 downregulated by RMD only; and 6 were up- and 2 were downregulated by SAHA only. Conclusions: This study demonstrates that SAHA and RMD, which have different potencies and specificities for HDACs, modulate a set of overlapping genes implicated in regulation of HIV latency. Some of these genes may be explored as additional host targets for improving the outcomes of “shock and kill” strategies. Overall design: Transcriptomic profiling of the in vitro model of HIV latency and mock-infected cells treated with SAHA, RMD or the solvent DMSO (N=4 donors) by deep sequencing at Expression Analysis, Inc.
Publication Title
Long non-coding RNAs and latent HIV - A search for novel targets for latency reversal.
Sample Metadata Fields
Specimen part, Treatment, Subject
View Samples