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accession-icon SRP061835
Characterization of t(15;21) translocations in myeloid disorders
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We report on two novel t(15;21) alterations [t(15;21)(q24;q22) and t(15;21)(q21;q22)], which led to concurrent disruption of RUNX1 and two translocation partner genes encoding for transcription factors (SIN3A, TCF12) Overall design: Examination of four different patients with myeloid disorders. 2 out of 4 have been analyzed by means RNAseq

Publication Title

t(15;21) translocations leading to the concurrent downregulation of RUNX1 and its transcription factor partner genes SIN3A and TCF12 in myeloid disorders.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE110104
pre-B cells from normal control, preleukemic, fully leukemic and fully leukemic, nilotinib-treated P190 BCR/ABL transgenic mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Precursor B-lineage acute lymphoblastic leukemia (pre-B ALL) can be subdivided into different categories based on genetic abnormalities.

Publication Title

Pre-B cell receptor-mediated cell cycle arrest in Philadelphia chromosome-positive acute lymphoblastic leukemia requires IKAROS function.

Sample Metadata Fields

Specimen part

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accession-icon GSE19655
Reprogramming of anaerobic metabolism by the FnrS Small RNA
  • organism-icon Escherichia coli
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

Small RNAs (sRNA) that act by base pairing with trans-encoded mRNAs modulate metabolism in response to a variety of environmental stimuli. Here, we describe an Hfq-binding sRNA (FnrS) whose expression is induced upon a shift from aerobic to anaerobic conditions and which acts to down regulate the levels of a variety of mRNAs encoding metabolic enzymes. Anaerobic induction in minimal medium depends strongly on FNR but is also affected by ArcA and CRP. Whole genome expression analysis showed that the levels of at least 32 mRNAs are down regulated upon FnrS overexpression, 15 of which are predicted to base pair with FnrS by TargetRNA. The sRNA is highly conserved across its entire length in numerous enterobacteria, and mutation analysis revealed that two separate regions of FnrS base pair with different sets of target mRNAs. The majority of the target genes previously reported to be down regulated in an FNR-dependent manner lack recognizable FNR binding sites. We thus suggest that FnrS extends the FNR regulon and increases the efficiency of anaerobic metabolism by repressing the synthesis of enzymes that are not needed under these conditions.

Publication Title

Reprogramming of anaerobic metabolism by the FnrS small RNA.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE24875
The base pairing RNA Spot 42 participates in a multi-output feedforward loop to help enact catabolite repression in Escherichia coli
  • organism-icon Escherichia coli str. k-12 substr. mg1655
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

Bacteria selectively consume some carbon sources over others through a regulatory mechanism termed catabolite repression. Here, we show that the base pairing RNA Spot 42 plays a broad role in catabolite repression in Escherichia coli by directly repressing genes involved in central and secondary metabolism, redox balancing, and the consumption of diverse non-preferred carbon sources. Many of the genes repressed by Spot 42 are transcriptionally activated by the global regulator CRP. Since CRP represses Spot 42, these regulators participate in a specific regulatory circuit called a multi-output feedforward loop. We found that this loop can reduce leaky expression of target genes in the presence of glucose and can maintain repression of target genes under changing nutrient conditions. Our results suggest that base pairing RNAs in feedforward loops can help shape the steady-state levels and dynamics of gene expression.

Publication Title

The base-pairing RNA spot 42 participates in a multioutput feedforward loop to help enact catabolite repression in Escherichia coli.

Sample Metadata Fields

Specimen part

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accession-icon GSE25318
Expanding the Pathways of Manganese Homeostasis: Role of a Small Manganese Chaperone Protein, MntS
  • organism-icon Escherichia coli str. k-12 substr. mg1655
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

Escherichia coli possesses >65 small proteins of <50 amino acids, many of which are uncharacterized. We have identified a new small protein, MntS, involved in manganese homeostasis. Manganese is a critical micronutrient, serving as an enzyme cofactor and protecting against oxidative stress. Yet manganese is toxic in excess and little is known about its function in cells. Bacteria carefully control intracellular manganese levels using the transcription regulator MntR. Before this work, mntH, which encodes a manganese importer, was the only gene known to respond to manganese via MntR repression in E. coli K12. We demonstrated that mntS is another member of the MntR manganese regulon. We also identified yebN, which encodes a putative manganese efflux pump, as the first gene positively regulated by MntR in Enterobacteria. Since MntS is expressed when manganese levels are low, causes manganese sensitivity when overexpressed, and binds manganese, we propose that MntS may be a manganese chaperone. This study reveals new factors involved in manganese regulation and metabolism and expands our knowledge of how small proteins function.

Publication Title

The Escherichia coli MntR miniregulon includes genes encoding a small protein and an efflux pump required for manganese homeostasis.

Sample Metadata Fields

Treatment

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accession-icon GSE85599
Whole transcriptome profiling reveals major cell types in the cellular immune response against acute and chronic active Epstein-Barr virus infection
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

EpsteinBarr virus (EBV) is a common human pathogen that infects over 95% of the population worldwide. In the present study, the whole transcriptome microarray data were generated from peripheral blood mononuclear cells from Chinese children with acute infectious mononucleosis (AIM) and chronic active EBV infection (CAEBV) that were also compared with a publicly available microarray dataset from a study of American college students with AIM. Our study characterized for the first time a broad spectrum of molecular signatures in AIM and CAEBV. The key findings from the transcriptome profiling were validated with qPCR and flow cytometry assays. The most important finding in our study is the discovery of predominant TCR expression and T cell expansion in AIM. This finding, in combination with the striking up-regulation of CD3, CD8 and CD94, suggests that CD8+ T cells and CD94+ NK cells may play a major role in AIM. Moreover, the unique up-regulation of CD64A/B and its significant correlation with the monocyte marker CD14 was observed in CAEBV and that implies an important role of monocytes in CAEBV. In conclusion, our study reveals major cell types (particularly T cells) in the host cellular immune response against AIM and CAEBV.

Publication Title

Whole transcriptome profiling reveals major cell types in the cellular immune response against acute and chronic active Epstein-Barr virus infection.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon GSE8659
Whole genome microarray analysis of C. elegans rrf-3 and eri-1 mutants
  • organism-icon Caenorhabditis elegans
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

RRF-3 and ERI-1 are first identified proteins required for accumulation of at least some endogenous secondary siRNAs in C.elegans. Genome wide gene expression analysis was performed on L4 stage rrf-3 and eri-1 mutant C. elegans to study effects caused by loss of these proteins. Mutant rrf-3 and eri-1 strains exhibited similar expression patterns when compared to N2 wild type, while 72 transcripts were found to be co-overexpressed and 4 transcripts co-underexpressed (> 2-fold, p< 0.05). Ontology analysis indicated many of the gene products were associated with protein phosphorylation and sperm function. These results provide additional support for the hypothesis that RRF-3 and ERI-1 act together in a siRNA pathway and may indicate biological processes that are related to endo-siRNAs.

Publication Title

Whole genome microarray analysis of C. elegans rrf-3 and eri-1 mutants.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE13477
Gene Expression Analysis of ARC (NSC 188491) Treated MCF7 cells
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

ARC (NSC 188491, SMA-491), 4-amino-6-hydrazino-7-beta-d-ribofuranosyl-7H-pyrrolo-(2,3-d)-pyrimidine-5-carboxamide, is a nucleoside analog with profound in vitro anti-cancer activity. First identified in a high-throughput screen for inhibitors of p21 mRNA expression, subsequent experiments showed that ARC also repressed expression of hdm2 and survivin, leading to its classification as a global inhibitor of transcription 1. The following Hu U133 plus 2.0 arrays represent single time point (24 hour) gene expression analysis of transcripts altered by ARC treatment. Arrays for the other compounds (sangivamycin and doxorubicin) are included as comparators.

Publication Title

ARC (NSC 188491) has identical activity to Sangivamycin (NSC 65346) including inhibition of both P-TEFb and PKC.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE7458
Transcriptional Profiles of Human Epithelial Cells in Response to Heat
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95 Version 2 Array (hgu95av2)

Description

We hypothesized that broad-scale expression profiling would provide insight into the regulatory pathways that control gene expression in response to stress, and potentially identify novel heat-responsive genes. HEp2 cells were heated at 37 to 43 C for 60 min to gauge the heat shock response, using as a proxy inducible HSP-70 quantified by western blot analysis. Based on these results, microarray experiments were conducted at 37, 40, 41, 42 and 43C (3 replicates/temperature x 5 groups = 15 U95Aver2 GeneChips). Using linear modeling, we compared the sets of microarrays at 40, 41, 42 and 43C with the 37C baseline temperature and took the union of the genes exhibiting differential gene expression signal to create two sets of heat shock response genes, each set reflecting either increased or decreased RNA abundance. Leveraging human and mouse orthologous alignments, we used the two lists of co-expressed genes to predict transcription factor binding sites in silico, including those for heat shock factor 1 (HSF1) and heat shock factor 2 (HSF2) transcription factors. We discovered HSF1 and HSF2 binding sites in 15 genes not previously associated with the heat shock response. We conclude that microarray experiments coupled with upstream promoter analysis can be used to identify novel genes that respond to heat shock. Additional experiments are required to validate these putative heat shock proteins and facilitate a deeper understanding of the mechanisms involved during the stress response.

Publication Title

Transcriptional profiles of human epithelial cells in response to heat: computational evidence for novel heat shock proteins.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9514
Changes in gene expression in response to heme deficiency and hypoxia
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

We addressed changes in gene expression profile in response to

Publication Title

Role of PUG1 in inducible porphyrin and heme transport in Saccharomyces cerevisiae.

Sample Metadata Fields

No sample metadata fields

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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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