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accession-icon GSE146110
The role of lncRNA Lassie in endothelial cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

The vascular endothelium forms a physical barrier between blood and the surrounding tissue. Its constant exposure to haemodynamic shear stress controls endothelial barrier function which is of major importance for vascular homeostasis. The role of long non-coding RNAs (lncRNAs) in this process remains elusive. Here we identify the shear stress-induced lncRNA LASSIE (linc00520) as a stabilizer of adherens junctions (AJs) in endothelial cells (ECs), that is indispensable for normal endothelial barrier function and shear stress sensing. Silencing of LASSIE in ECs resulted in impaired cell survival, loss of cell-cell contacts and failure to align in the direction of flow. RNA affinity purification followed by mass spectrometry identified several junction proteins associated with LASSIE, including the endothelial adhesion protein PECAM-1 and intermediate filament (IF) protein nestin. Proteomic analysis of VE-cadherin-associated proteins showed that LASSIE silencing reduces VE-cadherin interaction with nestin and microtubule (MT)-associated cytoskeletal proteins. We confirmed that LASSIE silencing results in a decreased connection between VE-Cadherin and the cytoskeleton, resulting in loss of barrier function and shear stress sensing. Together, this study identifies the shear stress-induced lncRNA LASSIE as a critical link between AJs and the IF cytoskeleton, which is indispensable for normal EC junction stabilization and shear stress sensing.

Publication Title

Long non-coding RNA LASSIE regulates shear stress sensing and endothelial barrier function.

Sample Metadata Fields

Specimen part

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accession-icon GSE61279
Transcriptome and Epigenome analysis of fetal and adult liver samples
  • organism-icon Homo sapiens
  • sample-icon 106 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genetic and epigenetic regulation of gene expression in fetal and adult human livers.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE61276
Transcriptome analysis of fetal and adult liver samples
  • organism-icon Homo sapiens
  • sample-icon 106 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Genome wide expression analysis of 92 adult and 14 fetal liver samples

Publication Title

Genetic and epigenetic regulation of gene expression in fetal and adult human livers.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE33822
Transcriptome Atlases Of Mouse Brain Reveals Differential Expression Across Brain Regions And Genetic Backgrounds
  • organism-icon Mus musculus
  • sample-icon 96 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Assessed steady-state transcription in whole brain and two more specific brain regions.

Publication Title

Transcriptome atlases of mouse brain reveals differential expression across brain regions and genetic backgrounds.

Sample Metadata Fields

Treatment

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accession-icon GSE44555
Multiple tissue expression data from inbreds and F1 of CAST, PWK, and WSB
  • organism-icon Mus musculus
  • sample-icon 384 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

We create catalogues of genes showing significant strain, parent-of-origin, dominance, sex effect in inbreds and reciprocal F1 hybrids of three wild-derived strains (CAST, PWK, WSB) across 4 different tissues (brain, kidney, liver, and lung)

Publication Title

Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE22297
Pre-Collaborative Cross liver gene expression
  • organism-icon Mus musculus
  • sample-icon 157 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The Collaborative Cross (CC) recombinant inbred panel was conceived as an ideal resource for mammalian system genetics. The pre-CC is a proof-of-concept experiment involving CC lines that have undergone at least five generations of inbreeding. Siblings from these lines were each involved in one of four distinct phenotyping arms, then genotyped on a high-density Affymetrix platform. The genetic profile of these emerging lines reveals high diversity, balanced allele frequencies, and well-distributed recombination all ideal qualities for a mapping panel. We have mapped white spot, a discrete trait; body weight, a highly polygenic complex trait; and more than 11,000 liver gene expression traits. These analyses provide a glimpse of the potential mapping power and resolution of the CC.

Publication Title

Genetic analysis of complex traits in the emerging Collaborative Cross.

Sample Metadata Fields

Specimen part

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accession-icon SRP174051
TNF induces Glucocorticoid Resistance by reshaping the GR Nuclear Cofactor Profile: Investigation of TNF mediated effects on the GR mediated gene expression
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina 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

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accession-icon GSE48836
Transcript profiling of ERF115 transgenic Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE30192
Effect of 5-azacytidine on gene expression in C2C12 myoblasts
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Mesenchymal progenitor cells can be differentiated in vitro into myotubes that exhibit many characteristic features of primary mammalian skeletal muscle fibers. However, in general, they do not show the functional excitation-contraction coupling or the striated sarcomere arrangement typical of mature myofibers. Epigenetic modifications have been shown to play a key role in regulating the progressional changes in transcription necessary for muscle differentiation. In this study, we demonstrate that treatment of murine C2C12 mesenchymal progenitor cells with 10 M of the DNA methylation inhibitor 5-azacytidine (5AC) promotes myogenesis, resulting in myotubes with enhanced maturity as compared to untreated myotubes. Specifically, 5AC treatment resulted in the upregulation of muscle genes at the myoblast stage while at later stages nearly 50 % of the 5AC-treated myotubes displayed a mature, well-defined sarcomere organization as well as spontaneous contractions that coincided with action potentials and intracellular calcium transients. Both the percentage of striated myotubes and their contractile activity could be inhibited by 20 nM TTX, 10 M ryanodine and 100 M nifedipine, suggesting that action potential-induced calcium transients are responsible for these characteristics. Our data suggest that genomic demethylation induced by 5AC overcomes an epigenetic barrier that prevents untreated C2C12 myotubes from reaching full maturity.

Publication Title

Epigenetics: DNA demethylation promotes skeletal myotube maturation.

Sample Metadata Fields

Cell line, Treatment

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accession-icon SRP048603
RNA-sequencing of the GSI treatment of the CUTLL1 cell line
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

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

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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