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accession-icon SRP068021
Single cell RNAseq of electrophysiologically characterized neurons of the hippocampus
  • organism-icon Mus musculus
  • sample-icon 103 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Recent advances in single-cell RNAseq technologies are enabling new cell type classifications. For neurons, electrophysiological properties traditionally guide cell type classification but correlating RNAseq data with electrophysiological parameters has been difficult. Here we demonstrate RNAseq of electrophysiologically and synaptically characterized individual, patched neurons in the hippocampal CA1-region and subiculum, and relate the resulting transcriptome data to their electrical and synaptic properties. In this analysis, we explored the hypothesis that precise combinatorial interactions between matching cell-adhesion and signaling molecules shape synapse specificity. In analyzing interneurons and pyramidal neurons that are synaptically connected, we identified two independent, developmentally regulated networks of interacting genes encoding cell-adhesion, exocytosis and signal-transduction molecules. In this manner, our data allow postulating a presumed cell-adhesion and signaling code, which may explain neuronal connectivity at the molecular level. Our approach enables correlating electrophysiological with molecular properties of neurons, and suggests new avenues towards understanding synaptic specificity. Overall design: These data include 15 tissue samples (including 3 independent replicas in 5 developmental stages) as well as 93 single-cell samples (including CA1 cholecystokinin, parvalbumin, and pyramidal neurons as well as subiculum burst and regular firing pyramidal neurons).

Publication Title

Single-cell RNAseq reveals cell adhesion molecule profiles in electrophysiologically defined neurons.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon GSE26325
Gene expression profiles of Hodgkins lymphoma cell lines with different sensitivity to cytotoxic drugs
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

By using high-density DNA microarrays, we analyzed the gene-expression profile of Hodgkin's lymphoma cell lines.

Publication Title

Gene expression profiles of Hodgkin's lymphoma cell lines with different sensitivity to cytotoxic drugs.

Sample Metadata Fields

Cell line

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accession-icon GSE51669
Expression data from the stomach of mice treated with dexamethasone.
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Glucocorticoids are used for the treatment of inflammatory conditions but they also cause many side-effects.

Publication Title

Glucocorticoids induce gastroparesis in mice through depletion of l-arginine.

Sample Metadata Fields

Treatment, Time

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accession-icon GSE32473
Gene expression is differently affected by pimecrolimus and betamethasone in lesional skin of atopic dermatitis.
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Topical corticosteroids and calcineurin inhibitors are well known treatments of atopic dermatitis (AD), but differ in their efficacy and side effects. A study in AD patients has demonstrated that betamethasone valerate (BM) though clinically more efficient impaired skin barrier repair in contrast to pimecrolimus. Objective: The present study elucidates the mode of action of topical BM and pimecrolimus cream in AD.

Publication Title

Gene expression is differently affected by pimecrolimus and betamethasone in lesional skin of atopic dermatitis.

Sample Metadata Fields

Specimen part

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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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