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accession-icon GSE60447
Stretch-dependent genes in vascular smooth muscle cells
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Vascular smooth muscle cells (VSMCs) respond to biomechanical stretch with specific changes in gene expression which govern the phenotype of these cells. The mechanotransducer zyxin is a

Publication Title

Loss of the mechanotransducer zyxin promotes a synthetic phenotype of vascular smooth muscle cells.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP144201
Brain vascular transcriptomes of mouse hyperglycemia mutants and controls
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose:To take a comprehensive effort in characterizing the brain vasculature gene expression upon hyperglycemia. Methods: We extracted mRNA from brain microvasculature fragments isolated from a genetic mouse model of hyperglycemia (Ins2-AKITA) and WT mice and analyzed their transcriptome with RNA sequencing The samples were sequenced on an Illumina HiSeq 2500 sequencer at the SNP&SEQ sequencing facility (Science for Life laboratory (SciLifeLab), Uppsala sequencing node). The reads were aligned to the Ensembl mouse gene assembly (NCBIM37) using Tophat2 software (version 2.0.4). The duplicated reads were removed using the picard tool (version 1.92). To identify the genes significantly enriched in the pericyte samples as compared with microvascular samples, statistical tests were performed using the Cufflinks tool (version 2.2.1) Results: Twenty-three genes were significantly regulated in mutant when compared to WT (False Discovery Rate < 0.05) Overall design: The microvascular RNA from two male heterozygous Ins2-AKITA mice and three littermate wild-type controls were processed and sequenced on the Illumina HiSeq 2500 platform in the sequencing facility in Uppsala University.

Publication Title

Prolonged systemic hyperglycemia does not cause pericyte loss and permeability at the mouse blood-brain barrier.

Sample Metadata Fields

Sex, Specimen part, Subject

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accession-icon GSE15242
Genotype and time of day shape the Populus drought response
  • organism-icon Populus x canadensis, Populus maximowiczii x populus nigra
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Poplar Genome Array (poplar)

Description

As exposure to episodic drought can impinge significantly on forest health and the establishment of productive tree plantations, there is great interest in understanding the mechanisms of drought response in trees. The ecologically dominant and economically important genus Populus, with its sequenced genome, provides an ideal opportunity to examine transcriptome level changes in trees in response to a drought stimulus. The transcriptome level drought response of two commercially important hybrid Populus clones (P. deltoides P. nigra, DN34, and P. nigra P. maximowiczii, NM6) was characterized over a diurnal period using a 4 2 2 completely randomized factorial ANOVA experimental design (four time points, two genotypes, and two treatment conditions) using Affymetrix Poplar GeneChip microarrays. Notably, the specific genes that exhibited changes in transcript abundance in response to drought differed between the genotypes and/or the time of day that they exhibited their greatest differences. This study emphasizes the fact that it is not possible to draw simple, generalized conclusions about the drought response of the genus Populus on the basis of one species, nor on the basis of results collected at a single time point. The data derived from our studies provide insights into the variety of genetic mechanisms underpinning the Populus drought response, and provide candidates for future experiments aimed at understanding this response across this economically and ecologically important genus.

Publication Title

Genotype and time of day shape the Populus drought response.

Sample Metadata Fields

Age, Specimen part, Treatment

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accession-icon GSE14680
Expression data from multiple myeloma cells overexpressing CS1 versus CS1 knockdown
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to detail the global programme of gene expression underlying CS1-regulated biological processes including increased cell adhesion and cell proliferation.

Publication Title

CS1 promotes multiple myeloma cell adhesion, clonogenic growth, and tumorigenicity via c-maf-mediated interactions with bone marrow stromal cells.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE21664
Gene expression data of interleukin-7-dependent and BCR-ABL1-transformed pre-B cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

This analysis focused on identifying factors that protect pre-B cells against DNA double strand break (DSB)-mediated DNA damage stress during pre-B cell differentiation. Differentiation of pre-B cells including immunoglobulin light chain gene recombination were performed by withdrawal of interleukin-7 (IL-7) from IL-7-dependent murine pre-B cells or by inhibition of the BCR-ABL1 kinase activity in BCR-ABL1-transformed pre-B cells.

Publication Title

BCL6 is critical for the development of a diverse primary B cell repertoire.

Sample Metadata Fields

Specimen part

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accession-icon GSE110104
pre-B cells from normal control, preleukemic, fully leukemic and fully leukemic, nilotinib-treated P190 BCR/ABL transgenic mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Precursor B-lineage acute lymphoblastic leukemia (pre-B ALL) can be subdivided into different categories based on genetic abnormalities.

Publication Title

Pre-B cell receptor-mediated cell cycle arrest in Philadelphia chromosome-positive acute lymphoblastic leukemia requires IKAROS function.

Sample Metadata Fields

Specimen part

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accession-icon GSE23743
Effect of imatinib on philadelphia chromosome positive acute lymphoblastic leukemia
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

The Philadelphia chromosome (Ph) encodes the oncogenic BCR-ABL1 tyrosine kinase, which defines a subset of acute lymphoblastic leukemia (ALL) with a particularly unfavorable prognosis. In this study, the tyrosine kinase inhibitor imatinib was used for pharmacological inhibition of BCR-ABL1. Gene expression profiles of Ph+ ALL cell lines were analyzed in response to imatinib treatment.

Publication Title

BCL6 enables Ph+ acute lymphoblastic leukaemia cells to survive BCR-ABL1 kinase inhibition.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE24493
Effect of Imatinib on chronic myelogenous leukemia
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The Philadelphia chromosome (Ph) encodes the oncogenic BCR-ABL1 tyrosine kinase, which is present in almost every patient with chronic myeloid leukemia. In this study, the tyrosine kinase inhibitor Imatinib was used for pharmacological inhibition of BCR-ABL1. Gene expression profiles of CML cell lines were analyzed in response to Imatinib treatment.

Publication Title

BCL6 enables Ph+ acute lymphoblastic leukaemia cells to survive BCR-ABL1 kinase inhibition.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP108034
Single cell RNA-seq of mouse brain astrocyte transcriptomes
  • organism-icon Mus musculus
  • sample-icon 250 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

By analyzing 250 astrocyte single cell transcriptomes from adult brain, we provide gene expresssion profile of brain astrocyte Overall design: We chose adult mice about 3 months old and analysed single cells in the brain. We chose a methodology based on fluorescence-activated cell sorting (FACS) into 384-well plates followed by the SmartSeq2 methodology.

Publication Title

Single-cell RNA sequencing of mouse brain and lung vascular and vessel-associated cell types.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP142465
Profiling of lung tumor-infiltrating CD8 T cells according to their expression status of CD39
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Human tumors are infiltrated by various immune cells, including CD8 T cells. CD8 T cells express unique receptors that can recognize peptides at the host's cells, including tumor cells. After probing the antigen specificity of ex-vivo tumor-infiltrating CD8 T cells from human tumors, we hypothesized that expression of CD39 was correlated with tumor-specificity. The present experiment aims at better characterizing ex-vivo CD39+ vs CD39- CD8 T cells. Overall design: CD39- and CD39+ CD8 T cells were FACS sorted from 8 fresh tumor samples and their RNA extracted for transcriptomic profiling.

Publication Title

Bystander CD8<sup>+</sup> T cells are abundant and phenotypically distinct in human tumour infiltrates.

Sample Metadata Fields

Specimen part, Subject

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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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