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accession-icon SRP018317
AGO-PAR-CLIP of DG75 and BCBL-1
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

AGO-PAR-CLIP was employed to identify microRNA binding sites in BCBL-1, a Kaposi's sarcoma-associated herpesvirus (KSHV) infected B-cell line and DG75, a KSHV negative B-cell line as a control. By using our novel computational method (PARma) and differential analysis of PAR-CLIP data, highly accurate target sites of KSHV microRNAs can be defined. Overall design: Examination of microRNA target sites in two different cell lines using replicate PAR-CLIP experiments

Publication Title

PARma: identification of microRNA target sites in AGO-PAR-CLIP data.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE10026
High resolution gene expression profiling for simultaneous analysis of RNA synthesis, abundance and decay
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 112 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Conserved principles of mammalian transcriptional regulation revealed by RNA half-life.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE10011
Expression data from NIH-3T3 cells used for half-life determination
  • organism-icon Mus musculus
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Data from tc-, nt- and p-RNA as well as 1 and 2h of actinomycin-D treatment (5g/ml) of NIH-3T3 cells used to determine half-lives. RNA was labeled for 15, 30 or 60 minutes with 4-thiouridine. After preparation of tc-RNA, thiol-labeled RNA was biotinylated using biot-HPDP and subsequently tc-RNA was separated into nt- and p-RNA using streptavidin coated magnetic beads. All three fractions were used for microarray analysis. For actinomycin-D experiments only tc-RNA was used prepared from cell before and 1 an 2h after addition of act-D.

Publication Title

Conserved principles of mammalian transcriptional regulation revealed by RNA half-life.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE9973
Half-life determination for human B-cells (BL41)
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

RNA was labeled in BL41 cells by culturing cells for 60 min in media containing 100M 4sU. Tc-RNA was separated into nt- and p-RNA. All three RNA subsets were subjected to microarray analysis. Only probe sets providing present calls in all RNA samples/subsets were included into the analysis

Publication Title

Conserved principles of mammalian transcriptional regulation revealed by RNA half-life.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE34204
Genome-wide survey of mRNA stability in human B-lymphoblastoid cell lines
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Transcript abundance results from the balance between transcription and mRNA decay, and varies pervasively in humans. We have examined the effect of DNA variation on mRNA half-life differences by conducting a genome-wide survey of mRNA stability in seven human HapMap lymphoblastoid cell lines (LCLs). We determined the mRNA half-life for each gene from the ratio of 4-thio-uridine (4sU)-labeled nascent RNAs to total RNAs. 5,145 (46%) of 11,132 analyzed genes showed inter-individual mRNA half-life differences at a false discovery rate, FDR<0.05. As previously reported, we found transcription to be the main factor influencing transcript abundance. Although mRNA half-life explained only ~6% of transcript abundance on average, it explained ~16% for the subset of genes (~10%) showing inter-individual mRNA half-life differences (P<0.001). We confirmed previously reported correlations of mRNA half-life with transcript length, 3-UTR length, and number of exon-junctions per kb of transcript. The number of miRNA targets in 3-UTRs was negatively correlated with half-life (P=2.210-16), a new observation that is consistent with the role of miRNA in inducing mRNA degradation. Notably, coding GC and GC3 content showed positive correlations with mRNA half-life in genes with inter-individual mRNA half-life differences, implying a role of mRNA stability in shaping synonymous codon usage bias. Consistently, G or C alleles of coding SNPs were found associated with longer mRNA half-life (P=0.021). As expected, we also found that nonsense SNPs were associated with shorter mRNA half-life (P=0.009). Our results strongly suggest that inter-individual mRNA stability differences are widespread and affected by DNA sequence and composition variation.

Publication Title

Genome-wide survey of interindividual differences of RNA stability in human lymphoblastoid cell lines.

Sample Metadata Fields

Disease, Cell line

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accession-icon GSE9975
newly transcribed RNA (nt-RNA) for IFN alpha and gamma time course
  • organism-icon Mus musculus
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Expression data from NIH-3T3 cells treated with mock, 100 U/ml IFN alpha or 100 U/ml gamma for 1 or 3h on nt-RNA labeled for 30-60 min at different times of interferon treatment

Publication Title

High-resolution gene expression profiling for simultaneous kinetic parameter analysis of RNA synthesis and decay.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP045214
Wide-spread disruption of transcription termination in HSV-1 infection: Next-generation sequencing of translational activityd by ribosome profiling
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Primary human foreskin fibroblasts (HFF) were infected with wild-type simplex virus 1 (HSV-1) strain 17 at a multiplicity of infection (MOI) of 10. Ribosome profiling was performed at various times during infection with minor modification to the protocol described in Stern-Ginossar N et al., Science 2012 Overall design: Ribosome profiling was performed a 0, 1, 2, 4, 6 and 8 h post infection. Two biological replicates were analysed.

Publication Title

Widespread disruption of host transcription termination in HSV-1 infection.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE9977
Expression data from NIH-3T3 cells treated with mock, 100 U/ml IFN alpha or 100 U/ml gamma for 1or 3h
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Differential gene expression caused by 1h and 3h of IFN alpha or gamma treatment was analyzed in total cellular RNA of NIH-3T3 cells compared to mock

Publication Title

High-resolution gene expression profiling for simultaneous kinetic parameter analysis of RNA synthesis and decay.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE20674
Nascent mRNA profiling of LPS-stimulated mouse macrophages
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

To identify transcriptionally regulated genes in primary mouse macrophages stimulated with LPS with high sensitivity, we isolated nascent RNA following metabolic labelling with 4-thiouridine during the last 35 min before cell harvest, as recently described (Dolken et al. 2008 RNA 14:1959-72). Microarray analyses of nascent RNA identified substantially more probe sets as up-regulated after 45 min of LPS stimulation than parallel analyses of total cellular RNA. In contrast, 4.5 h after stimulation, up-regulated genes in total and nascent RNA largely overlapped. This approach therefore allowed a much more sensitive detection of early changes in transcription, and the respective genes are likely to be direct targets of LPS-regulated transcription factors.

Publication Title

The phosphoproteome of toll-like receptor-activated macrophages.

Sample Metadata Fields

Specimen part

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accession-icon GSE30457
Dissecting primary (translation independent) from secondary (translation dependent) IFN-mediated differential gene expression
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

NIH-3T3 cells were pretreated for 15 min with either DMSO (mock) or cycloheximide followed by addition of either mock, 100 U/ml IFNalpha or 100 U/ml IFNgamma for 1h. During the last 30 min, 500 M 4-thiouridine was added to cell culture medium. Total cellular RNA was isolated using Trizol reagent and nascent RNA was purified as described (Dlken et al. RNA 2008) . Three replicates of nascent RNA were analyzed by Affymetrix Mouse Gene ST 1.0 arrays

Publication Title

Deciphering the modulation of gene expression by type I and II interferons combining 4sU-tagging, translational arrest and in silico promoter analysis.

Sample Metadata Fields

Cell line

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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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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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