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accession-icon SRP078437
Read-through transcription as a general mechanism mediating methylation and silencing of intragenic CGIs [CAP-Seq]
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The human genome contains approximately 27,700 CpG islands (CGIs). Most are associated with promoters and their DNA is nearly always unmethylated. By contrast, CGIs lying within the bodies of genes usually become methylated during differentiation and development. CGIs also normally become methylated at X-inactivated and imprinted genes and abnormally methylated in genome rearrangements and in malignancy. In such circumstances, methylation of CGIs is often associated with RNA transcripts reading through these elements but the relationship of this RNA to methylation of CGIs is not clear. Here we investigated a previously described form of a-thalassemia caused by a genome rearrangement leading to abnormal transcription and DNA methylation of the CGI at the promoter of the a-globin gene. We show that transcription per se is responsible for DNMT3B-mediated methylation of the globin CGI, and that this is a general mechanism responsible for methylation of most intragenic CpG islands. Overall design: CapSeq was performed on day 7 in vitro differentiated EBs containing the human gene sequence of RHBDF1 with (RHBDF1+P; chr16:47,861-63,210, hg18) or without  (RHBDF1-P; chr16:47,911-60,819, hg18) its promoter in the a recombination mediated cassette exchange (RMCE) system established within the mouse a-globin locus (Lynch et al., 2012, DOI: 10.1038/emboj.2011.399 ) to map transcription initiation sites within the transgene. Please note that the Cap-seq methods captures the 5' end of any short RNA that was Capped, capturing both coding and non-coding RNA.

Publication Title

DNA methylation of intragenic CpG islands depends on their transcriptional activity during differentiation and disease.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP074601
The RNA-binding protein TTP is a global post-transcriptional regulator of feedback control in inflammation [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNA-binding proteins (RBPs) facilitate post-transcriptional control of eukaryotic gene expression at multiple levels. The RBP tristetraprolin (TTP/Zfp36) is a signal-induced phosphorylated anti-inflammatory protein guiding unstable mRNAs of pro-inflammatory proteins for degradation and preventing translation. Using iCLIP, we have identified numerous mRNA targets bound by wild-type TTP and by a non-MK2-phosphorylatable TTP mutant (TTP-AA) in 1h LPS-stimulated macrophages and correlated their interaction with TTP to changes at the level of mRNA abundance and translation in a transcriptome-wide manner. The close similarity of the transcriptome of TTP-deficient and TTP-expressing macrophages upon short LPS stimulation suggested an effective inactivation of TTP by MK2 under these conditions whereas retained RNA-binding capacity of TTP-AA to 3’UTRs caused profound changes in the transcriptome and translatome, altered NF-?B-activation and induced cell death. Increased TTP binding to the 3''UTR of feedback inhibitor mRNAs, such as Ier3, Dusp1 or Tnfaip3, in the absence of MK2-dependent TTP neutralization resulted in a strong reduction of their protein synthesis contributing to the deregulation of the NF-?B-signaling pathway. Taken together, our study uncovers a role for TTP in NF-?B-signaling and highlights the importance of fine-tuned TTP activity-regulation by MK2 in order to control feedback signaling during the inflammatory response. Overall design: Comparison of the transcriptomes of TTP knockout macrophages inducibly expressing GFP, GFP-TTP or GFP-TTP-AA (S52A, S178A) phosphorylation mutant during 1h LPS stimulation. 3 biological replicates per genotype and condition.

Publication Title

The RNA-binding protein TTP is a global post-transcriptional regulator of feedback control in inflammation.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE100112
B-cell activating factor (BAFF) stimulation of Burkitt Lymphoma cell line
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st), Illumina HiSeq 2000

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

Sample Metadata Fields

Cell line, Treatment

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accession-icon SRP108761
B-cell activating factor (BAFF) stimulation of Burkitt Lymphoma cell line [RNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

RNA-Seq profiling of Burkitt Lymphoma cell line (BL2) with B-cell activating factor (BAFF) for 24 hrs . The Burkitt Lymphoma cell line were either only cultured in cell culture medium supplemented with 10 mM HEPES at 1 × 106 cells/ml or additionally incubated with B-cell activating factor (BAFF) for 24 hrs Overall design: Two conditions of BL2 cells each in 3 replicates: 1. non-stimulated control (BL2), 2. Baff stimulated (BL2Baff)

Publication Title

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

Sample Metadata Fields

Treatment, Subject

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accession-icon GSE100111
B-cell activating factor (BAFF) stimulation of Burkitt Lymphoma cell line [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Microarray profiling of Burkitt Lymphoma cell line (BL2) with B-cell activating factor (BAFF) for 24 hrs .

Publication Title

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

Sample Metadata Fields

Cell line

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accession-icon GSE47796
CEMA, a platform to define cell states
  • organism-icon Homo sapiens
  • sample-icon 82 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

gene expression database and algorithm to define cell expression modules

Publication Title

Identifying gene expression modules that define human cell fates.

Sample Metadata Fields

Specimen part

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accession-icon SRP036130
Global transcriptional Analysis of Yap/Yki Orthologs in Drosophila melanogaster by RNA Seq
  • organism-icon Drosophila melanogaster
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Throughout Metazoa, developmental processes are controlled by a surprisingly limited number of conserved signaling pathways. Precisely how these signaling cassettes were assembled in early animal evolution remains poorly understood, as do the molecular transitions that potentiated the acquisition of their myriad developmental functions. Here we analyze the molecular evolution of the proto-oncogene YAP/Yorkie, a key effector of the Hippo signaling pathway that controls organ size in both Drosophila and mammals. Based on heterologous functional analysis of evolutionarily distant Yap/Yorkie orthologs, we demonstrate that a structurally distinct interaction interface between Yap/Yorkie and its partner TEAD/Scalloped became fixed in the eumetazoan common ancestor. We then combine transcriptional profiling of tissues expressing phylogenetically diverse forms of Yap/Yorkie with ChIP-seq validation in order to identify a common downstream gene expression program underlying the control of tissue growth in Drosophila. Intriguingly, a subset of the newly-identified Yorkie target genes are also induced by Yap in mammalian tissues, thus revealing a conserved Yap-dependent gene expression signature likely to mediate organ size control throughout bilaterian animals. Combined, these experiments provide new mechanistic insights while revealing the ancient evolutionary history of Hippo signaling. We sought to define the downstream target genes of selected Yap variants by performing RNA sequencing analysis (RNA-seq) on total RNA isolated from GMR-Gal4>Yap eye discs. Overall design: Transcriptional profiles were generated in triplicate from eye imaginal disks with either endogenous Yki, or GMR-Gal4 over-expressed Yki, Trichoplax Yap, Monosiga Yap, or Monisiga Yap+TEAD domain, using deep sequencing via Illumina Hi Seq.

Publication Title

Molecular evolution of the Yap/Yorkie proto-oncogene and elucidation of its core transcriptional program.

Sample Metadata Fields

Treatment, Subject

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accession-icon GSE30541
bFGF-selected Bone Marrow-derived Mesenchymal Stem Cells triggers the host response for bone regeneration
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The classical concept of bone marrow-derived mesenchymal stem cells (BM-MSC), intended as a uniform, broad potent population, is progressively being substituted by the idea that the bone marrow harbors heterogeneous populations of non-hematopoietic stem cells. This in vivo heterogeneity is also amplified by the different experimental strategies used to isolate/culture them. Among the exogenous factors described to affect MSC in vitro growth, basic-fibroblast growth factor (bFGF) is one of the most common growth factors used to expand stem cells. Moreover, it has been reported that its signaling is associated with the mainteinance of stemness of a variety of stem cells, included MSC. Using an ectopic model of bone regeneration, we have previously described that the implantation of cells with different commitment levels, differentially influences the capacity to recruit host cells, activating endogenous regenerative mechanisms. Due to its properties, we here demonstrate that the addition of bFGF to primary BM cultures, leads to the selection of specific subpopulations able to induce a different host regenerative response, when in vivo implanted in association with suitable ceramic scaffolds. Moreover, taking advantage of a multiparametric and comparative genomic and proteomic approach, it has been evaluated how different culture conditions combine to bring about appreciable changes in the secretome of the cells, that consequently influence their in vivo regenerative behaviour. The full comprehension of the regulatory mechanisms that rule the host response depending on the type and differentiative stage of the transplanted cells could help us to develop novel clinical strategies where host cells could directly contribute to regenerate the appropriate tissue.

Publication Title

The role of bFGF on the ability of MSC to activate endogenous regenerative mechanisms in an ectopic bone formation model.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE29819
Myocardial transcriptome analysis of human arrhythmogenic right ventricular cardiomyopathy (ARVC)
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy primarily of the right ventricle characterized through fibrofatty replacement of cardiomyocytes. The genetic etiology in ARVC patients is most commonly caused by dominant inheritance and high genetic heterogeneity. Though histological examinations of ARVC affected human myocardium reveals fibrolipomatous replacement, the molecular mechanisms leading to loss of cardiomyocytes are largely unknown.

Publication Title

Myocardial transcriptome analysis of human arrhythmogenic right ventricular cardiomyopathy.

Sample Metadata Fields

Sex, Age

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accession-icon GSE14334
Transcriptomic analysis of human lung development
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We decompose the genome-wide expression patterns in 38 embryonic human lung (53-154 days post conception/dpc) into their independent, dominant directions of transcriptomic sample variation in order togain global insight of the developing human lung transcriptome.The characteristic genes and their corresponding bioontologic attribute profile for the latter were identified. We noted the overrepresentation of lung specific attributes (e.g., surfactant proteins) traditionally associated with later developmental stages, and highly ranked attributes (e.g., chemokineimmunologic processes) not previously reported nor immediately apparent in an early lung development context. We defined the 3,223gene union of the characteristic genes of the 3 most dominant sources of variation as the developing lung characteristic subtranscriptome (DLCS). It may be regarded as the minimal gene set describing the essential biology of this process. The developing lung series in this transcriptomic variation perspectiveform a contiguous trajectory with critical time points that both correlate with the 2 traditional morphologic stages overlapping -154 dpc and suggest the existence of 2 novel phases within the pseudoglandular stage. To demonstrate that this characterization is robust, we showed that the model could be used to estimate the gestational age of independent human lung tissue samples with a median absolute error of 5 days, based on the DLCS of their lung profile alone. Repeating this procedure on the homologous transcriptome profiles of developing mouse lung 1419 dpc, we were able to recover their correct developmental chronology.

Publication Title

Transcriptomic analysis of human lung development.

Sample Metadata Fields

Sex, Disease, Race

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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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