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accession-icon SRP007668
MicroRNA expression during cell cycle arrest
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

The miR-16 family, which targets genes important for the G1-S transition, is a known modulator of the cell cycle, and members of this family are often deleted or down-regulated in many types of cancers. Here we report the reciprocal relationship - that of the cell cycle controlling the miR-16 family. Levels of this family increase rapidly as cells are arrested in G0. Conversely, as cells are released from G0 arrest, levels of the miR-16 family rapidly decrease. Such rapid changes are made possible by the unusual instabilities of several family members. The repression mediated by the miR-16 family is sensitive to these cell cycle changes, which suggests that the rapid up-regulation of the miR-16 family reinforces cell cycle arrest in G0. Upon cell cycle re-entry, the rapid decay of several members allows levels of the family to decrease, alleviating repression of target genes and allowing proper resumption of the cell cycle. Overall design: Small RNAs were profiled by high-throughput sequencing either during synchronous release after serum starvation or during cell-cycle arrest by contact inhibition.

Publication Title

MicroRNA destabilization enables dynamic regulation of the miR-16 family in response to cell-cycle changes.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP123295
Determining mRNA half-lives on a transcriptome-wide scale
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Translation and mRNA decay are intimately connected processes, and translational inhibition often precedes and stimulates transcript degradation. Here, we have focused on methods that allow determination of mRNA stability on a transcriptome-wide scale. We describe experimental and computational methods for the two most commonly used approaches (transcriptional inhibition and metabolic labeling), and we discuss associated caveats. Overall design: Metabolic labeling time courses (1, 2, 4, 8, 12, 24 hr) using 4SU were performed in HEK293.

Publication Title

Determining mRNA half-lives on a transcriptome-wide scale.

Sample Metadata Fields

Treatment, Subject

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accession-icon SRP033131
Global analyses of the effect of different cellular contexts on microRNA targeting (RNA-Seq)
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

RNA-seqs followed by miRNA transfections (miR-124 and miR-155) into four different cell lines( HeLa, HEK293, Huh7, and IMR90). Overall design: There are two biological replicates of RNA-seqs per each miRNA transfection per each sample and there are corresponding mock transfections.

Publication Title

Global analyses of the effect of different cellular contexts on microRNA targeting.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE52940
Expression data from mouse B Cells with mir-155 KO and WT
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We used microarrays to investigate the global changes of gene expression in B cells of mir-155 Knockout mice.

Publication Title

Global analyses of the effect of different cellular contexts on microRNA targeting.

Sample Metadata Fields

Specimen part

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accession-icon GSE61093
Loss of the tumor suppressor gene AIP mediates the browning of human brown fat tumors
  • organism-icon Homo sapiens
  • sample-icon 85 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Human brown fat tumors (hibernomas) display concomitant loss of the tumor suppressor genes MEN1 and AIP. In the present study, we hypothesized that the brown fat phenotype is attributed to these mutations. Accordingly, we demonstrate that silencing of AIP in human brown preadipocytic and white fat cell lines results in the induction of the brown fat marker UCP1. In human adipocytic tumors, loss of MEN1 was found both in white (one out of 51 lipomas) and brown fat tumors. In contrast, concurrent loss of AIP was always accompanied by a brown fat morphology. We conclude that this white-to-brown phenotype switch in brown fat tumors is mediated by the loss of AIP.

Publication Title

Loss of the tumour suppressor gene AIP mediates the browning of human brown fat tumours.

Sample Metadata Fields

Specimen part

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accession-icon GSE15811
ZMYM2/FGFR1, BCR/FGFR1 or BCR/ABL1 in human cord blood CD34+ cells reveals similar but distinct gene expression profiles
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The 8p11 myeloproliferative syndrome (EMS), also referred to as the stem cell leukemia/lymphoma syndrome, is a chronic myeloproliferative disorder that rapidly progresses into an acute leukemia. Molecularly, EMS is characterized by fusion of various partner genes to the FGFR1 gene, resulting in constitutive activation of the tyrosine kinase activity within FGFR1. The two most common fusion genes in human EMS are ZMYM2/FGFR1 (previously known as ZNF198/FGFR1) and BCR/FGFR1. To study the transcriptional programs becoming deregulated by the FGFR1 fusion genes, global gene expression analysis on human CD34+ cord blood cells expressing either of the fusion oncogenes ZMYM2/FGFR1 and BCR/FGFR1 was performed. As a reference gene we also included the more studied BCR/ABL1 fusion oncogene associated with chronic myeloid leukemia. We found that the 3 different fusion oncogenes had in common the upregulation of several genes involved in the JAK/STAT signalling pathway and also other sets of genes. However, the gene expression profiles were not identical, suggesting that both the tyrosine kinase containing gene and the partner gene would affect the transcription of downstream target genes.

Publication Title

Modeling the human 8p11-myeloproliferative syndrome in immunodeficient mice.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP034166
Silencing of odorant receptor gene expression by G protein ß? signaling ensures the expression of one odorant receptor per olfactory sensory neuron
  • organism-icon Danio rerio
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Olfactory sensory neurons express just one out of a possible ~1000 odorant receptor genes, reflecting an exquisite mode of gene regulation. In one model, once an odorant receptor is chosen for expression, other receptor genes are suppressed by a negative feedback mechanism, ensuring a stable functional identity of the sensory neuron for the lifetime of the cell. The signal transduction mechanism subserving odorant receptor gene silencing remains obscure, however. Here we demonstrate in the zebrafish that odorant receptor gene silencing is dependent on receptor activity. Moreover, we show that signaling through G protein ß? subunits is both necessary and sufficient to suppress the expression of odorant receptor genes, and likely acts through histone methylation to maintain the silenced odorant receptor genes in transcriptionally inactive heterochromatin. These results provide new insights linking receptor activity with the epigenetic mechanisms responsible for ensuring the expression of one odorant receptor per olfactory sensory neuron. Overall design: Total 6 samples were analyzed-3 controls & 3 samples

Publication Title

Normalization of RNA-seq data using factor analysis of control genes or samples.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE4209
Changes in Expression of Genes Involved in Apoptosis in Activated Human T-Cells in Response to Modeled Microgravity
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The purpose of this study was to search for microgravity-sensitive genes, specifically for apoptotic genes influenced by the microgravity environment and other genes related to immune response.

Publication Title

Gene expression alterations in activated human T-cells induced by modeled microgravity.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP149311
Studying the genetic heterogeneity in mouse dopamine neurons
  • organism-icon Mus musculus
  • sample-icon 384 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Midbrain dopamine neurons project to numerous targets throughout the brain to modulate various behaviors and brain states. Within this small population of neurons exists significant heterogeneity based on physiology, circuitry, and disease susceptibility. Recent studies have shown that dopamine neurons can be subdivided based on gene expression; however, the extent to which genetic markers represent functionally relevant dopaminergic subpopulations has not been fully explored. Here we performed single-cell RNA-sequencing of mouse dopamine neurons and validated studies showing that Neurod6 and Grp are selective markers for dopaminergic subpopulations. Using a combination of multiplex fluorescent in situ hybridization, retrograde labeling, and electrophysiology in mice of both sexes, we defined the anatomy, projection targets, physiological properties, and disease vulnerability of dopamine neurons based on Grp and/or Neurod6 expression. We found that the combinatorial expression of Grp and Neurod6 defines dopaminergic subpopulations with unique features. Grp/Neurod6 dopamine neurons reside in the ventromedial VTA, send projections to the medial shell of the nucleus accumbens, and have noncanonical physiological properties. Grp/Neurod6- DA neurons are found in the VTA as well as in the ventromedial portion of the SNc, where they project selectively to the dorsomedial striatum. Grp-/Neurod6 DA neurons represent a smaller VTA subpopulation, which is preferentially spared in a 6-OHDA model of Parkinson's disease. Together, our work provides detailed characterization of Neurod6 and Grp expression in the midbrain and generates new insights into how these markers define functionally relevant dopaminergic subpopulations with distinct projection patterns, physiology, and disease vulnerability. Overall design: We collected a total of 384 neurons from 8 different p26-p34 DAT-Cre::Ai9 mice (6 male 2 female) to isolate DA neurons. RNA was captured from each samples neurons on separate fluidigm chips then all samples were pooled before sequencing.

Publication Title

Combinatorial Expression of <i>Grp</i> and <i>Neurod6</i> Defines Dopamine Neuron Populations with Distinct Projection Patterns and Disease Vulnerability.

Sample Metadata Fields

Sex, Specimen part, Cell line, Subject

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accession-icon GSE4658
static vs simulated microgravity
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The below table includes a smaller list of data that was analyzed by dChip and filtered by pvalue such that a file with about 4600 genes was obtained, which allowed for ease of use from 40,000 genes.

Publication Title

Identification of mechanosensitive genes in osteoblasts by comparative microarray studies using the rotating wall vessel and the random positioning machine.

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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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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