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accession-icon SRP032669
m6A RNA Methylation Is Regulated by MicroRNAs and Promotes Reprogramming to Pluripotency
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

N6-methyladenosine (m6A) has been recently identified as a conserved epitranscriptomic modification of eukaryotic mRNAs, but its features, regulatory mechanisms, and functions in cell reprogramming are largely unknown. Here, we report m6A modification profiles in the mRNA transcriptomes of four cell types with different degrees of pluripotency. Comparative analysis reveals several features of m6A, especially gene- and cell-type-specific m6A mRNA modifications. We also show that microRNAs (miRNAs) regulate m6A modification via a sequence pairing mechanism. Manipulation of miRNA expression or sequences alters m6A modification levels through modulating the binding of METTL3 methyltransferase to mRNAs containing miRNA targeting sites. Increased m6A abundance promotes the reprogramming of mouse embryonic fibroblasts (MEFs) to pluripotent stem cells; conversely, reduced m6A levels impede reprogramming. Our results therefore uncover a role for miRNAs in regulating m6A formation of mRNAs and provide a foundation for future functional studies of m6A modification in cell reprogramming. Overall design: m6A-seq in ESC, iPSC, NSC and sertoli cells.

Publication Title

m(6)A RNA methylation is regulated by microRNAs and promotes reprogramming to pluripotency.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP117703
RNA-seq expression analysis of mouse liver treated with locked nucleic acids (LNAs) that inhibit mmu-miR-802-5p and mmu-miR-1948-5p
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Total RNA-seq analysis of mouse liver following LNA treatment in vivo to identify mRNA targets of mmu-miR-802-5p and mmu-miR-1948-5p. Overall design: Male and female 9-wk ICR mice were injected with LNAs complementary to mmu-miR-1948-5p and mmu-miR-802-5p, respectively. Liver RNA was analyzed by RNA-seq 3 days or 6 days after LNA treatment.

Publication Title

Functional Roles of Sex-Biased, Growth Hormone-Regulated MicroRNAs miR-1948 and miR-802 in Young Adult Mouse Liver.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Treatment, Subject

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accession-icon GSE14071
mRNA stability influences the temporal order of inflammatory gene induction
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The inflammatory response plays out over time in a reproducible and organized manner after an initiating stimulus. Here we showed that the genes activated in cultured mouse fibroblasts in response to the proinflammatory cytokine tumor necrosis factorcan be divided roughly into three groups, each with different induction kinetics. Whereas differential transcription is important in determining the grouping of these genes, differential mRNA stability also exerted strong influence in some cases overriding that of transcriptional control elements on the temporal order of gene expression. mRNA transcripts expressed early after TNF stimulation have abundant AU-rich elements in their 3'-untranslated regions whereas those expressed later are contain fewer AU-rich sequences. Thus mRNA stability and transcriptional control, two intrinsic characteristics of genes, control the kinetics of proinflammatory cytokine-induced gene expression.

Publication Title

The stability of mRNA influences the temporal order of the induction of genes encoding inflammatory molecules.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP170614
RNAseq of control OT-I cells and Eomes-overexpressing OT-I cells
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

High amount of Eomes might drive T cell exhaustion. In order to understand how Eomes contributes to exhaustion of CD8+ T cell in the TME, we conducted transcriptional analysis of control OT-I cells and Eomes-overexpressing OT-I cells Overall design: Eomes was cloned into a retroviral expression vector (RVKM) which also encodes an IRES-hCD2 cassette. This vector was transfected into Pheonix to package retrovirus. The empty vector was used as a control. CD8+ T cells were isolated from spleen and lymph nodes of OT-I mice using Dynabeads Flowcomp mouse CD8 kit (Invitrogen). Then the cells were stimulated with SIINFEKL peptide (OVA257-264) at 2.5 ng/mL in the presence of 10U/mL IL-2 for 24 hr. Retroviral supernatants were harvested, filtered, and supplemented with 6µg/mL polybrene. OT-I T cell cultures were spinduced with the retroviral supernatant for 90 min at 1800 rpm, 32ºC. 48 hr later, hCD2+ cells were sorted prior to re-stimulation. hCD2+ OT-I cells were plated at 40,000 cells/well in 96-well plates and re-stimulated with 2.5ng/mL OVA with 10U/mL IL-2 for 3 days before harvested for RNAseq analysis. Total RNA was extracted from re-stimulated control or Eomes-overexpressing OT-I cells and sent to BGI Genomics for library construction. The library products were sequenced via Illumina Hiseq4000 by BGI Genomics. The sequencing reads were filtered by SOAPnuke without quality problems. Genome mapping was done by HISAT. Clean reads were mapped to the mm10 reference genome using Bowtie2, and gene expression indicated by RPKM (Reads Per Kilobases per Million reads) was calculated by RSEM. Differentially expressed genes (DEG) were detected with PoissonDis by at least 1.5 fold change and FDR lower than 0.01.

Publication Title

High Levels of Eomes Promote Exhaustion of Anti-tumor CD8<sup>+</sup> T Cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE39744
Expression of Data from EHMT1 siRNA transfected HeLa cell treated with TNF
  • organism-icon Homo sapiens
  • sample-icon 3 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 to identify TNF-induced genes that are negatively regulated by EHMT1

Publication Title

EHMT1 protein binds to nuclear factor-κB p50 and represses gene expression.

Sample Metadata Fields

Cell line

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accession-icon SRP055140
Gene expression profile of intact and hypophysectomized adult male and female mouse liver
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Gene expression in intact and hypophysectomized adult mouse liver was assayed by RNA-seq analysis of total liver RNA, as part of a study of growth hormone regulation of hepatic lincRNAs. Overall design: Eight independent pools: two intact males, two intact females, two hypophysectomized males and two hypophysectomized females, comprised of total RNA isolated from 3-5 individual livers / pool, were prepared and used for unstranded RNA-seq.

Publication Title

Hepatic Long Intergenic Noncoding RNAs: High Promoter Conservation and Dynamic, Sex-Dependent Transcriptional Regulation by Growth Hormone.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE46565
Contribution of CBX4 to cumulus oophorus cell phenotype in mice, and attendant effects in cumulus cell cloned embryos
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Cumulus oophorus cells play an essential role in oocyte development. CBX4 is a member of the Polycomb complex, which plays a role in regulating cellular differentiation.

Publication Title

Contribution of CBX4 to cumulus oophorus cell phenotype in mice and attendant effects in cumulus cell cloned embryos.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP055143
Gene expression profile of hepatic lincRNAs in male mouse liver using nuclear RNA-Seq
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Gene expression in adult male mouse liver was assayed by nuclear RNA-seq, as part of a study of hepatic lincRNAs. Overall design: Three independent pools, comprised of nuclear RNA isolated from 4 individual male livers per pool, were prepared and used for RNA-seq.

Publication Title

Hepatic Long Intergenic Noncoding RNAs: High Promoter Conservation and Dynamic, Sex-Dependent Transcriptional Regulation by Growth Hormone.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP055141
Gene expression profile of hepatic lincRNAs in female mouse liver using nuclear RNA-Seq
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Gene expression in adult female mouse liver was assayed by nuclear RNA-seq, as part of a study of hepatic lincRNAs. Overall design: Three independent pools, comprised of nuclear RNA isolated from 4 individual livers per pool, were prepared and used for unstranded RNA-seq.

Publication Title

Hepatic Long Intergenic Noncoding RNAs: High Promoter Conservation and Dynamic, Sex-Dependent Transcriptional Regulation by Growth Hormone.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP052976
Expression and transcriptional regulation dynamics of hepatic lincRNAs
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Gene expression in adult male and female mouse liver was assayed by RNA-seq, as part of a study on hepatic lincRNAs. Overall design: Total liver RNA was prepared from 12 individual male and 12 individual female mice. Four independent pools, comprised of RNA isolated from 6 individual male or female livers (2 pooled biological replicates for each sex) were then prepared and used for RNA-seq.

Publication Title

Hepatic Long Intergenic Noncoding RNAs: High Promoter Conservation and Dynamic, Sex-Dependent Transcriptional Regulation by Growth Hormone.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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