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accession-icon SRP128490
RNA sequencing to study transcriptomic changes in DLD-1 (colorectal adenocarcinoma) cells exposed to soft polyacrylamide matrices (~2 kPa and ~55 kPa) for short time scale of 90 minutes
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Aim: To examine transcriptional changes in DLD-1 cells exposed to softer matrices (2 kPa and 55 kPa) and identify the chromosomes that are enriched with maximmally deregulated genes Methods: DLD-1 cells (otherwise growing on stiff tissue culture plastic substrates) were exposed to softer matrices for 90 minutes and to collagen coated glass coverslips (served as control) served as control) Results: RNA sequencing revealed nearly equivalent transcriptional deregulation in cells on both the polyacrylamide matrices (783 genes up and 872 genes down on 2 kPa, 649 genes up and 783 genes down on 55 kPa) when compared to cells on glass. Additionally, GO classification revealed that unique sets of transcriptionally deregulated genes (log fold=2) belonged to pathways associated with transcription regulation, chromatin organization, cell cycle and DNA damage/repair Results: We identified chromosomes 1, 2, 3, 6, 7, 10, 12, 14, 17 and 19 to be maximally enriched with the deregulated genes on softer matrices (log fold=2), while chromosomes 13, 18 and 21 showed minimal enrichment of deregulated genes. We also examined the spatial organization of chromosome 1, 18 and 19 territories in cells on softer matrices (using 3D-FISH) and observed that these chromosomes were mislocalized away from their conserved nuclear locations Conclusions: Our study reports the transcriptomic changes in DLD-1 cells upon lowering of extracellular substrate stiffnes and its impact on the spatial positioning of chromosome territories Overall design: RNA Seq profiles for DLD-1 cells on soft polyacrylamide matrices of ~2 kPa and ~55 kPa (reference - glass) were generated across 2 independent biological replicates using Illumina HiSeq platform

Publication Title

Emerin modulates spatial organization of chromosome territories in cells on softer matrices.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE11467
Crosstalk between Estrogen and TNFalpha in MCF-7 Breast Cancer Cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Study was carried out to examine how E2 and TNFa together influence gene expression in breast cancer cells compared to either factor alone.

Publication Title

Positive cross-talk between estrogen receptor and NF-kappaB in breast cancer.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP150686
Understanding Early Stage Myelodysplastic Syndrome Pathobiology
  • organism-icon Mus musculus
  • sample-icon 94 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Delineating key HSC regulators is of significant interest for informing the treatment of hematologic malignancy. While HSC activity is enhanced by overexpression of SKI, the transforming growth factor-beta (TGFß) signaling antagonist corepressor, its requirement in HSC is unknown. Here we reveal a profound defect in Ski-/- HSC fitness but not specification. Transcriptionally, Ski-/- HSC exhibited striking upregulation of TGFb superfamily signaling and splicing alterations. As these are both common aspects of myelodysplastic-syndrome (MDS) pathobiology with prognostic value, we investigated the role of SKI in MDS. A SKI­-correlated gene signature defines a subset of low-risk MDS patients with active TGFß signaling and deregulated RNA splicing (e.g. CSF3R). The apparent paradox of Ski-/- HSC sharing molecular aspects of MDS with elevated SKI-mRNA is resolved by miR-21 targeting of SKI in MDS. We conclude that miR-21-mediated loss of SKI contributes to early stage MDS pathogenesis by activating TGFß signaling and alternative splicing while hindering HSC fitness. Overall design: Single cell RNA seq of transplanted fetal liver-derived hematopoietic stem cells

Publication Title

<i>SKI</i> controls MDS-associated chronic TGF-β signaling, aberrant splicing, and stem cell fitness.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE112485
Microarray expression data from FVB mice with induced hepatoblastoma (liver tumors)
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Hepatoblastoma (HB) is the most common pediatric liver tumor, and there are no targeted therapies available for children with HB. We have previously developed a murine model of HB which is driven by coactivation of the oncogenes YAP1 and -catenin (CTNNB1) [Tao J, Calvisi D, Ranganathan S, et al. Gastroenterology, 2014 Sep; 147(3): 690701]. We used the Sleeping Beauty transposase system combined with hydrodynamic tail vein injection to deliver plasmids containing mutant activated forms of YAP1 (YAP S127A) and -catenin (N90 -catenin) to a small number of pericentral hepatocytes. We have shown that these few transformed hepatocytes proliferate and dedifferentiate, eventually forming histologically heterogeneous tumors that resemble various subtypes of human HB (which is also highly heterogeneous), including areas of well-differentiated fetal, crowded fetal, embryonal, and blastemal HB. Our goal was to investigate how coactivation of YAP1 and -catenin drive the dedifferentiation of hepatocytes into hepatoblast-like tumor cells over time, leading to HB tumors. In order to measure changes in gene expression during tumorigenesis in our model, we used an Affymetrix microarray to analyze isolated RNA from wild type FVB mouse livers, mouse HB tumor tissue, and non-tumor liver tissue adjacent to HB tumors.

Publication Title

Hepatocyte-Derived Lipocalin 2 Is a Potential Serum Biomarker Reflecting Tumor Burden in Hepatoblastoma.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP091899
Rat testis
  • organism-icon Rattus norvegicus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

This is a whole transcriptome sequencing data of rat testis. YY1 gene was knocked down in Experimental animals under Sertoli cell specific and puberty specific promoter. These knockdown animals were compared with the control animals.

Publication Title

An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE37458
Expression data from WT and VAChT KDHOM ventricles
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

VAChT KDHOM mice have a 70% decrease in the vesicular acetylcholine transporter (VAChT) and this leads to a systemic decrease in ACh release and cardiac dysfunction.

Publication Title

An analysis of the myocardial transcriptome in a mouse model of cardiac dysfunction with decreased cholinergic neurotransmission.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE32260
Relationship between DNMT1-RNA interactions, DNA methylation and gene expression
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

DNMT1-interacting RNAs block gene-specific DNA methylation.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE32153
Expression data from WT HL60 cells
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We used the microarray analysis to detail the gene expression profile from the leukemic cell line HL-60

Publication Title

DNMT1-interacting RNAs block gene-specific DNA methylation.

Sample Metadata Fields

Cell line

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accession-icon SRP009094
RIPSEQ DNMT1 HL60
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Identification of the all RNA species associated with DNMT1. Using a comparative genome-scale approach we identified and correlated the RNA species physically associated with DNMT1 and proximal to the annotated genes to the methylation status of the corresponding loci and expression levels of the respective genes. This comparative approach delineated the first -DNMT1 centered- 'epitranscriptome' map, a comprehensive map cross-referencing DNMT1-interacting transcripts to (i) DNA methylation and (ii) gene expression profile. Overall design: Relationship between DNMT1-RNA interactions, DNA methylation and gene expression

Publication Title

DNMT1-interacting RNAs block gene-specific DNA methylation.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE62632
Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons.

Sample Metadata Fields

Specimen part

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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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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