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accession-icon GSE43270
Genome wide-DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2), Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE43191
Genome wide-DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients (gene expression)
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2), Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

The aim of this study is to identify, for the first time, the genome-wide DNA methylation profiles of human articular chondrocytes from OA and healtly cartilage samples.

Publication Title

Genome-wide DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon SRP014142
Identification of new microRNAs in paired normal and tumor breast tissue suggests a dual role for the ERBB2/Her2 gene
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer, Illumina Genome Analyzer II

Description

To comprehensively characterize microRNA (miRNA) expression in breast cancer, we performed the first extensive next-generation sequencing expression analysis of this disease. We sequenced small RNA from tumors with paired samples of normal and tumor-adjacent breast tissue. Our results indicate that tumor identity is achieved mainly by variation in the expression levels of a common set of miRNAs rather than by tissue-specific expression. We also report 361 new, well-supported miRNA precursors. Nearly two-thirds of these new genes were detected in other human tissues and 49% of the miRNAs were found associated with Ago2 in MCF7 cells. Ten percent of the new miRNAs are located in regions with high-level genomic amplifications in breast cancer. A new miRNA is encoded within the ERBB2/Her2 gene and amplification of this gene leads to overexpression of the new miRNA, indicating that this potent oncogene and important clinical marker may have two different biological functions. In summary, our work substantially expands the number of known miRNAs and highlights the complexity of small RNA expression in breast cancer. Overall design: Sequencing of approximately 18-35 nt small RNAs from paired samples of normal, tumor and tumor-adjacent tissue for five breast cancer patients

Publication Title

Identification of new microRNAs in paired normal and tumor breast tissue suggests a dual role for the ERBB2/Her2 gene.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE7696
Glioblastoma from a homogenous cohort of patients treated within clinical trial
  • organism-icon Homo sapiens
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of 80 glioblastoma specimen of patients treated within clinical trials and 4 samples of "normal" brain tissue (non-tumoral). The data was used to identify factors of resistance to a chemoradiation therapy protocol of radiotherapy and concomitant and adjuvant temozolomide (alkylating agent).

Publication Title

Stem cell-related "self-renewal" signature and high epidermal growth factor receptor expression associated with resistance to concomitant chemoradiotherapy in glioblastoma.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Treatment, Subject

View Samples
accession-icon GSE63059
Expression data from Pin1 inhibitor ATRA and Pin1 knockdown
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

ATRA was identified as a Pin1 inhibitor via fluorescence polarization-based high throughput screening. We performed microarray expression profiling to demonstrate the similarity between ATRA and Pin1 KD at the genome-wide level

Publication Title

Active Pin1 is a key target of all-trans retinoic acid in acute promyelocytic leukemia and breast cancer.

Sample Metadata Fields

Disease, Disease stage, Cell line, Treatment

View Samples
accession-icon SRP054971
Ribosome profiling and RNA sequencing of MCF10A-ER-Src and fibroblast cell transformation
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We applied ribosome profiling and RNA sequencing to examine gene expression regulation during oncogenic cell transformation. One model involves normal mammary epithelial cells (MCF10A) containing ER-Src. Treatment of such cells with tamoxifen rapidly induces Src, thereby making it possible to kinetically follow the transition between normal and transformed cells. The other model consists of three isogenic cell lines derived from primary fibroblasts in a serial manner (Hahn et al., 1999). EH cell is immortalized by overexpression of telomerase (hTERT), and exhibits normal fibroblast morphology. EL cell expresses hTERT along with both large and small T antigens of Simian virus 40, and it displays an altered morphology but is not transformed. ELR cell expresses hTERT, T antigens, and an oncogenic derivative of Ras (H-RasV12). Overall design: Ribosome profiling and RNA sequencing in two cancer cell models

Publication Title

Many lncRNAs, 5'UTRs, and pseudogenes are translated and some are likely to express functional proteins.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP129440
Smart-seq2 analysis of larval zebrafish habenula from the gng8-GFP transgenic line
  • organism-icon Danio rerio
  • sample-icon 1138 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The identification of cell types and marker genes is critical for dissecting neural development and function, but the size and complexity of the brain has hindered the comprehensive discovery of cell types. We combined single-cell RNA-seq with anatomical brain registration to create a comprehensive map of the zebrafish habenula, a conserved forebrain hub involved in pain processing and learning. Single-cell transcriptomes of ~13000 habenular cells (>4x coverage) identified 18 neuronal types and dozens of marker genes. Registration of marker genes onto a common reference atlas created a rich resource for anatomical and functional studies and enabled the mapping of active neurons onto neuronal types following aversive stimuli. Strikingly, despite brain growth and functional maturation, cell types were retained between the larval and adult habenula. This study provides a gene expression atlas to dissect habenular development and function and offers a general framework for the comprehensive characterization of other brain regions. Overall design: gng8-GFP zebrafish heads were dissected, dissociated and FAC sorted into 96 well plates. Single cell libraries were generated in batches of 384 cells using Smart-seq2. A total of 22 gng8-GFP fish were dissected in 3 batches and 384 cells were processed from each using Smart-seq2.

Publication Title

Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP186866
Progressive dosage compensation during Drosophila embryogenesis is reflected by gene arrangement on the X chromosome [RNA-seq]
  • organism-icon Drosophila melanogaster
  • sample-icon 52 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

In D. melanogaster males, X chromosome monosomy is compensated by chromosome-wide transcription activation. We found that complete dosage compensation during embryogenesis takes surprisingly long. Although the activating Dosage Compensation Complex (DCC) associates with the chromosome and acetylates histone H4 early, many genes are not compensated. Acetylation levels on gene bodies continue to increase for several hours after gastrulation in parallel with progressive compensation. Constitutive genes are compensated earlier than developmental genes. Remarkably, later compensation correlates with longer distances to DCC binding sites. This time-space relationship suggests that DCC action on target genes requires maturation of the active chromosome compartment. Overall design: RNA-seq in 8 embryonic stages in total 54 single embryos.

Publication Title

Progressive dosage compensation during Drosophila embryogenesis is reflected by gene arrangement.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP042091
Genome-wide expression profiles in young and old mouse liver [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Aging is accompanied by physiological impairments, which, in insulin-responsive tissues, including the liver, predispose individuals to metabolic disease. However, the molecular mechanisms underlying these changes remain largely unknown. Here, we analyze genome-wide profiles of RNA and chromatin organization in the liver of young (3 months) and old (21 months) mice. Transcriptional changes suggest that de-repression of the nuclear receptors PPARa, PPAR?, and LXRa in aged mouse liver leads to activation of targets regulating lipid synthesis and storage, whereas age-dependent changes in nucleosome occupancy are associated with binding sites for both known regulators (forkhead factors and nuclear receptors) and for novel candidates associated with nuclear lamina (Hdac3 and Srf) implicated to govern metabolic function of aging liver. Winged-helix factor Foxa2 and nuclear receptor co-repressor Hdac3 exhibit reciprocal binding pattern at PPARa targets contributing to gene expression changes that lead to steatosis in aged liver. Overall design: Genome-wide expression profiles (RNA-Seq) from young (3 months) and old (21 months) mouse livers

Publication Title

Changes in nucleosome occupancy associated with metabolic alterations in aged mammalian liver.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP055996
Spatial reconstruction of single-cell gene expression
  • organism-icon Danio rerio
  • sample-icon 1138 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. Overall design: We generated single-cell RNA-seq profiles from dissociated cells from developing zebrafish embryos (late blastula stage - 50% epiboly)

Publication Title

Spatial reconstruction of single-cell gene expression data.

Sample Metadata Fields

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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