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accession-icon SRP022764
Quantitative single-cell RNA-seq
  • organism-icon Mus musculus
  • sample-icon 236 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Purpose: We applied cDNA molecule counting using unique molecular identifiers combined with high-throughput sequencing to study the transcriptome of individual mouse embryonic stem cells, with spike-in controls to monitor technical performance. We further examined transcriptional noise in the embryonic stem cells. Overall design: One 96-well plate of single-stranded cDNA libraries generated from 96 single R1 mouse embryonic stem cells sequenced on two lanes, and one 96-well plate of the same libraries further amplified by 9 PCR cycles sequenced on one lane.

Publication Title

Quantitative single-cell RNA-seq with unique molecular identifiers.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP060744
Single-cell RNA sequencing of aspirates from cortical neurons after patch clamp recording
  • organism-icon Mus musculus
  • sample-icon 83 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We obtained full transcriptome data from single cortical neurons after whole-cell patch-clamp recording (termed “Patch-seq”). By applying “Patch-seq” to cortical neurons, we reveal a close link between biophysical membrane properties and genes coding for neurotransmitter receptors and channels, including well-established and hitherto undescribed subtypes. Overall design: RNA sequencing was performed on a total of 83 individual cells

Publication Title

Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33538
Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miRs targets is a considerable bioinformatic challenge of great importance for inferring the miRs function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methodsit identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs function in a specific context.

Publication Title

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.

Sample Metadata Fields

Cell line

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accession-icon GSE20504
Human umbilical cord blood-derived endothelial colony forming cells under serum-free conditions
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Derivation and expansion of human umbilical cord blood-derived endothelial colony forming cells under serum-free conditions - a transcriptome analysis.

Publication Title

Optimization of the culturing conditions of human umbilical cord blood-derived endothelial colony-forming cells under xeno-free conditions applying a transcriptomic approach.

Sample Metadata Fields

Specimen part

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accession-icon GSE19698
BMP-mediated inhibition of FGF signaling promotes cardiomyocyte differentiation of anterior heart field progenitors
  • organism-icon Gallus gallus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

The transition from progenitor to differentiated cells is critical for successful organogenesis; subtle alterations in this process can lead to developmental disorders. The anterior heart field (AHF) encompasses a niche in which cardiac progenitors maintain their multipotent and undifferentiated nature by signals from the surrounding tissues, which thus far have been poorly defined. Using systems biology approaches and perturbations of signaling molecules in chick embryos, we revealed a tight crosstalk between the bone morphogenic protein (BMP) and fibroblast growth factor (FGF) signaling pathways within the AHF: BMP4 promotes myofibrillar gene expression and cardiomyocyte contractions, by blocking FGF signaling. Furthermore, inhibition of the FGF-ERK pathway is both sufficient and necessary for these processes, suggesting that FGF signaling blocks premature differentiation of cardiac progenitors in the AHF. Investigating the molecular mechanisms downstream to BMP signaling revealed that BMP4 induced a set of neural crest-related genes; including MSX1, which was sufficient to induce cardiomyocyte differentiation. We suggest that BMP and FGF signaling pathways act via inter- and intra-regulatory loops in multiple tissues, to coordinate the balance between proliferation and differentiation of cardiac progenitors.

Publication Title

BMP-mediated inhibition of FGF signaling promotes cardiomyocyte differentiation of anterior heart field progenitors.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE35299
Implantation Failure of Blastocysts Derived from Oocyte-directed Connexin 43 depleted Mice is Associated with Impaired Ribosomal and Translational Machinery Gene Expression
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Oocyte quality is a well- established determinant of embryonic fate. However, the molecular participants and biological markers that affect and predict adequate embryonic development are largely elusive. We have previously reported that oocyte- directed Connexin 43 (Cx43) depletion leads to embryo implantation defects, although both the morphology of the oocyte and processes presiding embryo implantation appear to undergo normally. In the context of previous data determining Cx43 indispensability to oocyte and embryonic development, we show here that the timing of Cx43 depletion from the oocyte and the ovarian follicle is crucial in determining the severity of subsequent embryonic defects. Specifically, we show that the implantation defects of blastocysts resulting from oocyte- directed Cx43- depleted follicles (depletion occurs at day 3 postnatal), is not due to maternal luteal insufficiency but rather depends solely on the defective blastocysts. Gene expression microarray analysis revealed global defects in the expression of ribosomal proteins, translation initiation factors and other genes associated with cellular biosynthetic and metabolic processes in these defective oocytes and specifically blastocysts. We therefore propose that timely expression of Cx43 in the oocyte and ovarian follicles is a major determinant of oocyte developmental competence, by determining the ability of the resulting blastocyst to facilitate biomass expansion and undergo adequate embryo implantation

Publication Title

Blastocyst implantation failure relates to impaired translational machinery gene expression.

Sample Metadata Fields

Specimen part

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accession-icon GSE76790
Cellular reactions to long-term volatile organic compound (VOC) exposures.
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A549 cells were grown at air liquid interphase (ALI) and exposed to airborne formaldehyde for three days. An exposure platform was developed for this purpose, which provided the volatile analyte in a humidified atmosphere. The platform was composed of a reference and an exposure chamber.

Publication Title

Cellular reactions to long-term volatile organic compound (VOC) exposures.

Sample Metadata Fields

Cell line

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accession-icon GSE24391
Coupled pre-mRNA and mRNA dynamics unveil the operation strategies underlying transcriptional responses
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Transcriptional responses to stimuli are regulated by tuning rates of transcript production and degradation. Here we show that stimulation-induced changes in transcript production and degradation rates can be inferred from simultaneously measured precursor mRNA (pre-mRNA) and mature mRNA profiles. Our studies on the transcriptome-wide responses to extracellular stimuli in different cellular model systems revealed hitherto unanticipated dynamics of transcript production and degradation rates. Intriguingly, genes with similar mRNA profiles often exhibit marked differences in the amplitude and onset of their production. Moreover, we identify a group of genes, which take advantage of the unexpectedly large dynamic range of production rates to expedite their induction by a transient production overshoot. These findings provide an unprecedented quantitative view on processes governing transcriptional responses, and may have broad implications for understanding their regulation at the transcriptional and post-transcriptional levels.

Publication Title

Coupled pre-mRNA and mRNA dynamics unveil operational strategies underlying transcriptional responses to stimuli.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE12038
XBP1 links ER stress to intestinal inflammation
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

XBP1 is the transcriptino factor that is activated by the ER stress. XBP1 is known to induce the ER dexpansion and increase the expression of the ER chaperone genes to prtect the cell from the ER stress. We generated a mouse strain that lacked XBP1 specifically in the mouse intestine by breeding the XBP1flox mice with Villin-cre mice. Here we examined genes that are differentially expressed between WT and XBP1 KO mouse intestine to identify genes that are downstream of XBP1.

Publication Title

XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP159173
PatchSeq analysis of Pthlh expressing cells of the mouse dorsolateral striatum
  • organism-icon Mus musculus
  • sample-icon 92 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

In order to investigate how electrophysiological properties vary within the Pthlh population in the dorsolateral striatum we performed PatchSeq analysis of neurons labeled in 5HT3a(EGFP) and Pvalb(cre)::RCE/tdTomato mouse lines, which included Th, Npy/Mia, Cck, and Cck/Vip expressing cells. Overall design: 98 FACS-sorted single cells isolated from the dorso-lateral striatum from either a 5ht3a-EGFP mouse line or a Lhx6-cre mouse crossed onto a R26R-tdTomato reporter mouse line

Publication Title

Diversity of Interneurons in the Dorsal Striatum Revealed by Single-Cell RNA Sequencing and PatchSeq.

Sample Metadata Fields

Specimen part, Cell line, 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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