refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 733 results
Sort by

Filters

Technology

Platform

accession-icon SRP019189
Transcriptome and transposable element dynamics during PIWI regulation in Drosophila ovarian cell cultures
  • organism-icon Drosophila melanogaster
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

This study examines the regulatory capacity of the Piwi protein in the Drosophila OSS cell. Piwi CLIP-Seq, mRNA-Seq and nascent RNAseq datasets were integrated to determine how Piwi proteins where using piRNAs and binding interactions to regulate the expression of transcripts. We also sequenced the genomes of various OSS cell lines. Overall design: We first performed several replicates of a Piw CLIP-Seq experiment to isolate RNA fragments as CLIP-tags to discover which transcripts are preferentially bound by the Piwi protein. Then we performed several types of mRNA expression profiling experiments using several forms of mRNA-Seq library construction formats. Finally, we sequenced the genomes from various OSS cell lines. The genomic sequencing component of the study is represented by BioProject PRJNA240323. The genomic sequencing raw data have been deposited at SRA (SRP039565).

Publication Title

Transposable element dynamics and PIWI regulation impacts lncRNA and gene expression diversity in Drosophila ovarian cell cultures.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP020625
Holo-TFIID controls the magnitude of a transcription burst and fine-tuning of transcription.
  • organism-icon Drosophila melanogaster
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

TFIID is a central player in activated transcription initiation. Recent evidence suggests that the role and composition of TFIID is more diverse than previously understood. To investigate the effects of changing the composition of TFIID in a simple system we depleted TAF1 from Drosophila cells and determined the consequences on metal induced transcription at an inducible gene, Metallothionein B (MtnB). We observe a marked increase in the levels of both the mature message and pre-mRNA in TAF1 depleted cells. Under conditions of continued metal exposure, we show that TAF1 depletion increases the magnitude of the initial transcription burst, but has no effect on the timing of that burst. We also show that TAF1 depletion causes delay in the shut-off of transcription upon removal of the stimulus. Thus TAFs are involved in both establishing an upper limit of transcription during induction and efficiently turning the gene off once the inducer is removed. Using genomewide nascent-seq we identify hundreds of genes that are controlled in a similar manner indicating that the findings at this inducible gene are likely generalizable to a large set of promoters. There is a long-standing appreciation for the importance of the spatial and temporal control of transcription. Here we uncover an important third dimension of control, the magnitude of the response. Our results show that the magnitude of the transcriptional response to the same signaling event, even at the same promoter, can vary greatly depending on the composition of the TFIID complex in the cell. Overall design: Nascent RNA was sequenced from replicate samples of Drosophila S2 cells treated with double-stranded RNA directed against E. coli LacI (Control) or against Drosophlia TAF1 (experimental). Reads per kilo-base per million (RPKM) was determined for each gene and the control and experimental samples were compared to determine the genes that were affected by the depletion of TAF1.

Publication Title

Holo-TFIID controls the magnitude of a transcription burst and fine-tuning of transcription.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE27280
Pompe disease induced pluripotent stem cells for pathogenesis modeling, drug testing and disease marker identification
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pompe disease is caused by autosomal recessive mutations in the GAA gene, which encodes acid alpha-glucosidase. Although enzyme replacement therapy has recently improved patient survival greatly, the results in skeletal muscles and for advanced disease are still not satisfactory. Here, we report the derivation of Pompe disease induced pluripotent stem cells (PomD-iPSCs) and their potential for pathogenesis modeling, drug testing and disease marker identification. PomD-iPSCs maintained pluripotent features, and had low GAA activity and high glycogen content. Cardiomyocyte-like cells (CMLCs) differentiated from PomD-iPSCs recapitulated the hallmark Pompe disease pathophysiological phenotypes, including high levels of glycogen, abundant intracellular LAMP-1- or LC3-positive granules, and multiple ultrastructural aberrances. Drug rescue assessment showed that exposure of PomD-iPSC-derived CMLCs to rhGAA reversed the major pathologic phenotypes. Further, L-carnitine and 3- methyladenine treatment reduced defective cellular respiration and buildup of phagolysosomes, respectively, in the diseased cells. By comparative transcriptome analysis, we identified glycogen metabolism, lysosome and mitochondria related marker genes whose expression robustly correlated with the therapeutic effect of drug treatment in PomD-iPSC-derived CMLCs. Collectively, these results demonstrate that PomD-iPSCs are a promising in vitro disease model for development of novel therapeutic strategies for Pompe disease.

Publication Title

Human Pompe disease-induced pluripotent stem cells for pathogenesis modeling, drug testing and disease marker identification.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE48060
Transcriptome from circulating cells suggests dysregulated pathways associated with long-term recurrent events following first-time myocardial infarction.
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Whole-genome gene expression analysis has been successfully utilized to diagnose, prognosticate, and identify potential therapeutic targets for cardiovascular disease. However, the utility of this approach to identify outcome-related genes and dysregulated pathways following first-time myocardial infarction (AMI) remains unknown and may offer a novel strategy to detect affected expressome networks that predict long-term outcome. Whole-genome microarray and targeted cytokine expression profiling on blood samples from normal cardiac function controls and first-time AMI patients within 48-hours post-MI revealed expected differential gene expression profiles enriched for inflammation and immune-response pathways in AMI patients. To determine molecular signatures at the time of AMI that could prognosticate long-term outcomes, transcriptional profiles from sub-groups of AMI patients with (n=5) or without (n=22) any recurrent events over an 18-month follow-up were compared. This analysis identified 559 differentially expressed genes. Bioinformatic analysis of this differential gene set for associated pathways revealed 1) increasing disease severity in AMI patients is associated with a decreased expression of the developmental epithelial-to-mesenchymal transition, and 2) modulation of cholesterol transport genes that include ABCA1, CETP, APOA1, and LDLR is associated with clinical outcome. In conclusion, differentially regulated genes and modulated pathways were identified that predicted recurrent cardiovascular outcomes in first-time AMI patients. This cell-based approach for risk stratification in AMI warrants a larger study to determine the role of metabolic remodeling and regenerative processes required for optimal outcomes. A validated transcriptome assay could represent a novel, non-invasive platform to anticipate modifiable pathways and therapeutic targets to optimize long-term outcome for AMI patients.

Publication Title

Transcriptome from circulating cells suggests dysregulated pathways associated with long-term recurrent events following first-time myocardial infarction.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE35603
Network Biology of Tumor Stem-like Cells Identified a Regulatory Role of CBX5 in Lung Cancer
  • organism-icon Homo sapiens
  • sample-icon 74 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Mounting evidence points to a link between a cancer possessing stem-like properties and a worse prognosis. To understand the biology, a common approach is to integrate network biology with signal processing mechanics. That said, even with the right tools, predicting the risk for a highly susceptible target using only a handful of gene signatures remains very difficult. By compiling the expression profiles of a panel of tumor stem-like cells (TSLCs) originating in different tissues, comparing these to their parental tumor cells (PTCs) and the human embryonic stem cells (hESCs), and integrating network analysis with signaling mechanics, we propose that network topologically-weighted signaling processing measurements under tissue-specific conditions can provide scalable and predicable target identification.

Publication Title

Network biology of tumor stem-like cells identified a regulatory role of CBX5 in lung cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE22538
Differential expression for rice-gall midge interaction
  • organism-icon Oryza sativa
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

We exposed Kavya rice seedlings to different gall midge biotypes, GMB1 and GMB4M, which exhibit incompatible and compatible interactions, respectively.

Publication Title

A novel mechanism of gall midge resistance in the rice variety Kavya revealed by microarray analysis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE117239
Cellular and Molecular Changes in Psoriasis Lesions Inducedby Ustekinumab: Distinct Differences in Responders vs. Non responders
  • organism-icon Homo sapiens
  • sample-icon 322 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Ustekinumab provides clinical benefit to psoriasis patients, but precise cellular and molecular changes underlying its therapeutic utility are not yet fully understood. To assess differences between ustekinumab responders vs. non responders in modulating specific inflammatory pathways and provide reference data for exploring molecular effects of next-generation interleukin(IL)-17 and IL-23-antagonists in psoriasis.

Publication Title

Modulation of inflammatory gene transcripts in psoriasis vulgaris: Differences between ustekinumab and etanercept.

Sample Metadata Fields

Specimen part, Treatment, Subject, Time

View Samples
accession-icon GSE106992
Cellular and Molecular Changes in Psoriasis Lesions Induced by Ustekinumab: Distinct Differences in Responders vs. Non-Responders
  • organism-icon Homo sapiens
  • sample-icon 175 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A gene expression profiling sub-study was conducted in which skin biopsy samples (n=192) were collected for RNA extraction and hybridization to microarrays from patients with moderate-to-severe psoriasis who participated in ACCEPT, an IRB-approved Phase 3, multicenter, randomized trial.

Publication Title

Modulation of inflammatory gene transcripts in psoriasis vulgaris: Differences between ustekinumab and etanercept.

Sample Metadata Fields

Specimen part, Treatment, Subject, Time

View Samples
accession-icon GSE32924
Nonlesional atopic dermatitis skin is characterized by broad terminal differentiation defects and variable immune abnormalities
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Atopic dermatitis (AD) is a common inflammatory skin disease with a T(H)2 and T22 immune polarity. Despite recent data showing a genetic predisposition to epidermal barrier defects in some patients, a fundamental debate still exists regarding the role of barrier abnormalities versus immune responses in initiating the disease. An extensive study of nonlesional AD (ANL) skin is necessary to explore whether there is an intrinsic predisposition to barrier abnormalities, background immune activation, or both in patients with AD. We sought to characterize ANL skin by determining whether epidermal differentiation and immune abnormalities that characterize lesional AD (AL) skin are also reflected in ANL skin. We performed genomic and histologic profiling of both ANL and AL skin lesions (n = 12 each) compared with normal human skin (n = 10). We found that ANL skin is clearly distinct from normal skin with respect to terminal differentiation and some immune abnormalities and that it has a cutaneous expansion of T cells. We also showed that ANL skin has a variable immune phenotype, which is largely determined by disease extent and severity. Whereas broad terminal differentiation abnormalities were largely similar between involved and uninvolved AD skin, perhaps accounting for the background skin phenotype, increased expression of immune-related genes was among the most obvious differences between AL and ANL skin, potentially reflecting the clinical disease phenotype. Our study implies that systemic immune activation might play a role in alteration of the normal epidermal phenotype, as suggested by the high correlation in expression of immune genes in ANL skin with the disease severity index.

Publication Title

Nonlesional atopic dermatitis skin is characterized by broad terminal differentiation defects and variable immune abnormalities.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE96853
Characterization of transcriptomes of human iPSC-derived retinal lineages
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Retinal ganglion cells (RGCs) and retinal pigment epithelium (RPE) cells are two retinal cell types that are affected by the most prevalent retinal diseases leading to irreversible blindness, such as glaucoma affecting the former and age-related macular degeneration affecting the latter. One of the most promising approaches for the therapy of these diseases is via the autologous transplantation of RGC or RPE cells derived from the induced pluripotent stem cells (iPSCs). This emphasizes the importance of detailed characterization and understanding of the mechanisms of differentiation of iPSCs into retinal lineages on the genome-wide scale. Such information can be used to identify novel crucial regulators of differentiation, optimisation of differentiation protocols to make them more efficient and safe, identification of novel specific biomarker signatures of differentiated cells. In this study, we performed the genome-wide transcriptome analysis of terminally differentiated RGC and RPE lineages, as well as intermediate retinal progenitor cells (RPCs) of optic vesicles (OVs) derived from the human induced pluripotent stem cells (iPSCs). In our analysis we specifically focused on the classes of transcripts that encode regulators of gene expression, such as transcription factors, epigenetic factors, and components of signaling pathways.

Publication Title

Expression profiling of cell-intrinsic regulators in the process of differentiation of human iPSCs into retinal lineages.

Sample Metadata Fields

Specimen part

View Samples
...

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact