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accession-icon SRP150322
RNA Sequencing to Identify Regulators of Axon Regeneration in Mouse Retinal Ganglion Cells
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: The goals of this study are to identify the transcriptional profile of retinal ganglion cells (RGCs) with the capacity to regenerate an axon, and contrast this profile with the profile of RGCs that cannot regenerate an axon. Methods: See sample pages for protocols for tissue preparation, RNA extraction and purification, library construction and data processing. Results: RNA from the 12 samples was sequenced to an average depth of 42 million reads. Genes were considered expressed if a gene had an expression of 1 count per million in 3 of the 12 samples. There were 13,406 genes that met this criterion. Conclusions: Our study represents the first analysis by NGS of highly-purified RGCs in the context of axonal injury Overall design: RGC mRNA profiles of melanopsin RGCs and ON-OFF Direction Selective Ganglion Cells (ooDSGCs) were generated by deep sequencing in triplicate, using Illumina HiSeq 2500.

Publication Title

Thrombospondin-1 Mediates Axon Regeneration in Retinal Ganglion Cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE7152
Melanoma cell lines involved in the p14ARF genotype analysis
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

35 Melanoma cell lines hybridized to Affymetrix Hu133_Plus 2 microarrays were analysed for genes differentially expressed between cell lines carrying wild-type p14ARF and those with mutant 14ARF. All of these cell lines contained wild-type p53 (so that the effects of p14ARF mutations could be analysed without contamination from p53).

Publication Title

Gene expression profiling in melanoma identifies novel downstream effectors of p14ARF.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE53029
L. dorsi muscle transcriptome study in pure and crossbred young Iberian pigs
  • organism-icon Sus scrofa
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

We studied the influence of genetic type (pure Iberian pigs vs crossbred with Duroc) on l.dorsi transcriptome

Publication Title

Longissimus dorsi transcriptome analysis of purebred and crossbred Iberian pigs differing in muscle characteristics.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE77126
The mdx mutation in the 129/Sv background results in a milder phenotype: Transcriptome comparative analysis searching for the protective factors
  • organism-icon Mus musculus
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Transcriptome analysis of hindlimb muscles from dystrophic mice.

Publication Title

The mdx Mutation in the 129/Sv Background Results in a Milder Phenotype: Transcriptome Comparative Analysis Searching for the Protective Factors.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon SRP116020
Transcriptomic response to 24-hour food deprivation in four hypothalamic nuclei in Snord116 deletion mice
  • organism-icon Mus musculus
  • sample-icon 43 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Mice with a congenital Snord116 deletion model aspects of the Prader-Willi Syndrome. In this study, we examine the gene expression changes in four hypothalamic nuclei across 24-hour food deprived versus ad libitum fed mice. Overall design: Using mice with paternal deletion of the Snord116 cluster, we laser-captured microdissected four hypothalamic nuclei for RNA sequencing: the ventromedial hypothalamus (VMH), arcuate nucleus (ARC), dorsomedial hypothalamus (DMH) and paraventricular nucleus (PVN). Samples were taken from male mice in either the fed or 24-hour fasted state.

Publication Title

Hypothalamic loss of Snord116 recapitulates the hyperphagia of Prader-Willi syndrome.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE52717
Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

Sample Metadata Fields

Specimen part, Disease, Cell line

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accession-icon GSE52712
Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells: Affymetrix array data
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accurate profiling of RNA expression of single cells is a valuable approach for broadening our understanding of cancer biology and mechanisms of dissemination, but requires the development of reliable methods for their molecular characterization. Here we evaluate a single cell methodology which generates microgram amounts of cDNA suitable for next generation sequencing (RNA-Seq), high throughput RT-qPCR and Affymetrix array analysis. The approach was tested by comparing expression profiles of amplified single MCF7 and MCF10A cells to profiles generated from unamplified RNA. The expression profiles were compared by Affymetrix-U133 arrays, RNA-Seq and high-density qPCR. There were strong cross-platform correlations of >80% and concordance between single cell and unamplified material of >70%. We exemplify the approach through analysis of rare sorted cancer initiating cells (CICs) derived from a NSCLC patient-derived xenograft. Populations of 10 cells from total tumour and two distinct subsets of CIC, putatively involved in primary tumor maintenance or metastasis formation were FACS sorted then directly amplified. CIC expression profiles strongly correlated with published stem-cell and epithelial-mesenchymal transition (EMT) signatures. Our results confirm the utility of the amplification system and our methodology to detect and distinguish RNA profiles in rare cell populations that inform on EMT and stem-cell characteristics. This GEO dataset comprises the Affymetrix U-133 Plus 2.0 data for MCF7 and MCF10A cDNA amplified from 1ng RNA and single cell samples.

Publication Title

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

Sample Metadata Fields

Disease, Cell line

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accession-icon GSE115313
Transcriptomics analysis of paired tumor and normal mucosa samples in a cohort of patients with colon cancer, with and without T2DM.
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This is a transcriptomics analysis contributing to a bigger project that tries to shed light on the role of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC). Here we present a gene expression screening of paired tumor and normal colon mucosa samples in a cohort of 42 CC patients, 23 of them with T2DM. Using gene set enrichment, we identified an unexpected overlap of pathways over-represented in diabetics compared to non-diabetics, both in tumor and normal mucosa, including diabetes-related metabolic and signaling processes. An integration with other -omic studies suggests that in diabetics, the local micro-environment in normal colon mucosa may be a factor driving field cancerization which may promote carcinogenesis. Several of these pathways converged on the tumor initiation axis TEAD/YAP-TAZ. Cell culture studies confirmed that high glucose concentrations upregulate this pathway in non-tumor colon cells. In conclusion, diabetes is associated to deregulation of cancer-related processes in normal colon mucosa adjacent to tissue which has undergone a malignant transformation. These data support the existence of the field of cancerization paradigm in diabetes and set a new framework to study link between diabetes and cancer.

Publication Title

Molecular evidence of field cancerization initiated by diabetes in colon cancer patients.

Sample Metadata Fields

Specimen part

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accession-icon GSE115329
Transcriptomics analysis of Colon tumor xenograft model in streptozotocin-induced diabetic mice
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This is a transcriptomics analysis contributing to a bigger project that tries to shed light on the role of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC). Here we present a gene expression screening of 7 colon tumor xenograft samples, 2 with diabetic mice and 5 with normal blood glucose levels. For xenograft model details see: Prieto I, et al. (2017) Colon cancer modulation by a diabetic environment: A single institutional experience. PLoS One 12(3):e0172300

Publication Title

Molecular evidence of field cancerization initiated by diabetes in colon cancer patients.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE32095
GPR120 mediates high-fat diet induced obesity
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Analysis of GPR120 which play roles for the fatty acid sensor in adipose tissue. Results provide insight into the transcriptional effects caused by the loss of the GPR120 proteins and provide further insight into their functions.

Publication Title

Dysfunction of lipid sensor GPR120 leads to obesity in both mouse and human.

Sample Metadata Fields

Specimen part, Treatment, 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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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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