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accession-icon SRP014009
DGCR8 HITS-CLIP reveals novel functions for the Microprocessor (CLIP-seq)
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina Genome Analyzer IIx

Description

The Drosha-DGCR8 complex (Microprocessor) is required for microRNA (miRNA) biogenesis. DGCR8 contains two double-stranded RNA binding motifs that recognize the RNA substrate, whereas Drosha functions as the endonuclease. We have used high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) to identify endogenous RNA targets of DGCR8 in mammalian cells. Unexpectedly, miRNAs were not the most abundant targets. DGCR8-bound RNAs comprised several hundred mRNAs as well as snoRNAs and long non-coding RNAs. We found that DGCR8 together with Drosha controls the abundance of several mRNAs, as well as long non-coding RNAs, such as MALAT-1. By contrast, the DGCR8-mediated cleavage of snoRNAs is independent of Drosha, suggesting the involvement of DGCR8 in cellular complexes with other endonucleases. Interestingly, binding of DGCR8 to cassette exons, acts as a novel mechanism to regulate the relative abundance of alternatively spliced isoforms. Collectively, these data provide new insights in the complex role of DGCR8 in controlling the fate of several classes of RNAs. Overall design: Comparison of RNAs associated to both endogenous (D8) and overexpressed (T7) DGCR8 in HEK293T cells

Publication Title

Drosha regulates gene expression independently of RNA cleavage function.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP074138
Human islets contain four distinct subtypes of ß cells
  • organism-icon Homo sapiens
  • sample-icon 31 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 2500

Description

The transcriptomes of four subpopulations of beta cells isolated by FACS from five healthy human donors. Populations were defined using cell surface-labeling antibodies, avoiding the need for fixation. Overall design: There are 5 biological replicates of 4 different cell types. Each donor yielded all 4 subtypes.

Publication Title

Human islets contain four distinct subtypes of β cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP075377
RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes
  • organism-icon Homo sapiens
  • sample-icon 1600 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Pancreatic islet cells are critical for maintaining normal blood glucose levels and their malfunction underlies diabetes development and progression. We used single-cell RNA sequencing to determine the transcriptomes of 1,492 human pancreatic a-, ß-, d- and PP cells from non-diabetic and type 2 diabetes organ donors. We identified cell type specific genes and pathways as well as 245 genes with disturbed expression in type 2 diabetes. Importantly, 92% of the genes have not previously been associated with islet cell function or growth. Comparison of gene profiles in mouse and human a- and ß-cells revealed species-specific expression. All data are available for online browsing and download and will hopefully serve as a resource for the islet research community. Overall design: Single-cell RNA sequencing of human non-diabetic and type 2 diabetic pancreatic islet cells

Publication Title

RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes.

Sample Metadata Fields

Sex, Age, Specimen part, Race, Subject

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accession-icon SRP076340
Single-Cell RNAseq Reveals That Pancreatic ß-Cells From Very Old Male Mice Have a Young Gene Signature
  • organism-icon Mus musculus
  • sample-icon 207 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Aging improves pancreatic ß-cell function in mice. This is a surprising finding since aging is typically associated with functional decline. We performed single-cell RNA sequencing of ß-cells from 3 and 26 month old mice to explore how changes in gene expression contribute to improved function with age. The old mice were healthy, had reduced blood glucose levels and increased ß-cell mass, which correlated to their body weight. ß-cells from young and old mice had similar transcriptome profiles. In fact, only 193 genes (0.89% of all detected genes) were significantly regulated (= 2-fold; false discovery rate < 0.01; normalized counts > 5). Of these, 183 were downregulated and mainly associated with pathways regulating gene expression, cell cycle, cell death and survival as well as cellular movement, function and maintenance. Collectively, our data show that ß-cells from very old mice have transcriptome profiles similar to those of young mice. These data support previous findings that aging is not associated with reduced ß-cell mass or functional ß-cell decline in mice. Overall design: Single-cell RNA sequencing of mouse pancreatic islet beta cells

Publication Title

Single-Cell RNAseq Reveals That Pancreatic β-Cells From Very Old Male Mice Have a Young Gene Signature.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon SRP070425
Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells
  • organism-icon Mus musculus
  • sample-icon 622 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of alpha-cells (5%), beta-cells (92%), delta-cells (1%) and PP-cells (2%). We identified cell-type specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability (23%), low sequencing quality (13%) or contamination resulting in the detection of more than one islet hormone (64%). Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system. Overall design: Single-cell RNA sequencing of mouse C57BL/6 pancreatic islet cells

Publication Title

Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP092584
PC1/3 deficiency impacts POMC processing in human embryonic stem cell-derived hypothalamic neurons
  • organism-icon Homo sapiens
  • sample-icon 89 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We developed a technique for generating hypothalamic neurons from human pluripotent stem cells. Here, as proof-of-principle, we examine the use of these cells in modeling of a monogenic form of severe obesity: PCSK1 deficiency. We generated PCSK1 (PC1/3)-deficient human embryonic stem cell (hESC) lines using both shRNA and CRISPR-Cas9, and investigated pro-opiomelanocortin (POMC) processing using hESC-differentiated hypothalamic neurons. Overall design: We tried to idenitify transcripitional profiles and specific transcription factors that involved in of different stages during hypothalamic neuron differentiation from single cell sequencing for hESC-derived Day27 hypothalamic neurons, Day 12 neuron progenitors and undifferentiated stem cells

Publication Title

PC1/3 Deficiency Impacts Pro-opiomelanocortin Processing in Human Embryonic Stem Cell-Derived Hypothalamic Neurons.

Sample Metadata Fields

Sex, Specimen part, Subject

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accession-icon GSE67351
Altering TET dioxygenase levels within physiological range affects DNA methylation dynamics of HEK293 cells
  • organism-icon Homo sapiens
  • sample-icon 17 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

Altering TET dioxygenase levels within physiological range affects DNA methylation dynamics of HEK293 cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE39186
Effect of TET1 and TET3 overexpression on the transcriptome of HEK293 cells
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We compared TET1 and TET3 overexpressing cells to uninduced cells with endogenous levels of the respective transcript to determine global gene expression changes.

Publication Title

Altering TET dioxygenase levels within physiological range affects DNA methylation dynamics of HEK293 cells.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE67348
Effect of the simultaneous knockdown of TET1, TET2 and TET3 on the transcriptome of HEK293 cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We compared TET triple knockdown cells to control cells treated with non-targeting siRNAs to determine global gene expression changes.

Publication Title

Altering TET dioxygenase levels within physiological range affects DNA methylation dynamics of HEK293 cells.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon SRP092805
Amino Acid Transporter Slc38a5 Mediates Glucagon Receptor Inhibition-Induced Pancreatic a-Cell Hyperplasia in Mice
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Glucagon supports glucose homeostasis by stimulating hepatic gluconeogenesis, in part by promoting the uptake and conversion of amino acids into gluconeogenic precursors. Genetic disruption or pharmacologic inhibition of glucagon signaling results in elevated plasma amino acids, and compensatory glucagon hypersecretion involving expansion of pancreatic a-cell mass. Regulation of pancreatic a- and ß-cell growth has drawn a lot of attention because of potential therapeutic implications. Recent findings indicate that hyperaminoacidemia triggers pancreatic a-cell proliferation via an mTOR-dependent pathway. We confirm and extend these findings by demonstrating that glucagon pathway blockade selectively increases expression of the sodium-coupled neutral amino acid transporter Slc38a5 in a subset of highly proliferative a-cells, and that Slc38a5 is critical for the pancreatic response to glucagon pathway blockade; most notably, mice deficient in Slc38a5 exhibit markedly decreased a-cell hyperplasia to glucagon pathway blockade-induced hyperaminoacidemia. These results show that Slc38a5 is a key component of the feedback circuit between glucagon receptor signaling in the liver and amino acid-dependent regulation of pancreatic a-cell mass in mice. Overall design: Examination of the transcriptomes of pancreatic islets of mice treated with GCGR-antibody and an isotype control antibody.

Publication Title

Amino Acid Transporter Slc38a5 Controls Glucagon Receptor Inhibition-Induced Pancreatic α Cell Hyperplasia in Mice.

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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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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