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accession-icon GSE49795
Brown Adipose Tissue (BAT) in Visceral Fat Depot
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Case story. A patient with massive infiltration of the visceral adipose tissue depot by BAT in a patient with a catecholamine secreting paraganglioma. BAT tissue was identified by protein expression of UCP1 (western blotting and immunostaining)

Publication Title

Chronic adrenergic stimulation induces brown adipose tissue differentiation in visceral adipose tissue.

Alternate Accession IDs

E-GEOD-49795

Sample Metadata Fields

Specimen part

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accession-icon SRP014636
RNA-seq in wild-type and glass mutant eye-antennal discs in Drosophila melanogaster
  • organism-icon Drosophila melanogaster
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The aim of this data set is to perform a differential expression analysis between wild type eye-antennal imaginal disc and discs that are homozygous glass mutant gl[60j]. This data set is used to validate Glass target gene predictions identified by i-cisTarget on a set of conserved eye-specific genes. Overall design: RNA-seq was performed in eye-antennal imaginal discs of two D.melanogaster wild-type strains (Canton S and strain RAL-208 (Jordan et al. 2007, Ayroles et al. 2009)), representing two biological replicates; and in glass mutant (gl[60j]) discs for two technical replicates.

Publication Title

Comparative motif discovery combined with comparative transcriptomics yields accurate targetome and enhancer predictions.

Alternate Accession IDs

GSE39781

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP068213
Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic [RNA-seq]
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Analysis of p53 binding sites using multiplex enhancer reporter assays, ChIP-seq data and RNA-seq data. Transcription factors establish and maintain the specific transcriptome of a cell by binding to genomic regulatory regions, thereby regulating the transcription of their target genes. Like many transcription factors, the DNA sequence-specific binding preferences of p53 are known. However, it remains largely unclear what distinguishes functional enhancers from other bound genomic regions that have no regulatory activity. In addition, the genome is scattered with seemingly perfect recognition sequences that remain unoccupied. To disentangle the rules of genome-wide p53 binding, we employed two complementary techniques of multiplex enhancer-reporter assays, one using barcoded reporters and the other using enhancer self-transcription. We compared the activity of more than one thousand candidate p53 enhancers under loss and gain of p53 conditions and identified several hundred high-confidence p53-responsive enhancers. Strikingly, the large majority (99%) of these target enhancers can be characterized and distinguished from negative sequences by the occurrence of a single p53 binding site. By training a machine learning classifier on these data, and integrating the resulting genome-wide predictions with fifteen publicly available human p53 ChIP-seq data sets, we identified a consensus set of 1148 functional p53 binding sites in the human genome. Unexpectedly, this direct p53 cistrome is invariably used between cell types and experimental conditions, while differences between experiments can be largely attributed to indirect non-functional binding. Our data suggest that direct p53 enhancers function in a context-independent manner and do not contain obvious combinatorial complexity of binding sites for multiple transcription factors. They represent a class of unsophisticated cell-autonomous enhancers with a single binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors. This suggests that context-dependent regulation of p53 target genes is not encoded in the p53 enhancer, but at different upstream or downstream layers of the cell''s gene regulatory network. Overall design: RNA-seq on MCF7 cells with p53 stable knockdown.

Publication Title

Multiplex enhancer-reporter assays uncover unsophisticated TP53 enhancer logic.

Alternate Accession IDs

GSE76656

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP044038
Mapping gene regulatory networks in Drosophila eye development by large-scale transcriptome perturbations and motif inference. [RNA-seq]
  • organism-icon Drosophila melanogaster
  • sample-icon 72 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Genome control is operated by transcription factors (TF) controlling their target genes by binding to promoters and enhancers. Conceptually, the interactions between TFs, their binding sites, and their functional targets are represented by gene regulatory networks (GRN). Deciphering in vivo GRNs underlying organ development in an unbiased genome-wide setting involves identifying both functional TF-gene interactions and physical TF-DNA interactions. To reverse-engineer the GRN of eye development in Drosophila, we performed RNA-seq across 72 genetic perturbations and sorted cell types, and inferred a co-expression network. Next, we derived direct TF-DNA interactions using computational motif inference, ultimately connecting 241 TFs to 5632 direct target genes through 24926 enhancers. Using this network we found network motifs, cis-regulatory codes, and new regulators of eye development. We validate the predicted target regions of Grainyhead by ChIP-seq and identify this factor as a general co-factor in the eye network, being bound to thousands of nucleosome-free regions. Overall design: RNA-seq gene expression profiling across Drosophila 3rd instar larval wild type tissues (brain, eye-antennal and wing discs), specific cell types from the eye-antennal disc, sorted by FACS, and genetic perturbations (TF mutants, TF over-expression, and TF RNAi knockdown).

Publication Title

Mapping gene regulatory networks in Drosophila eye development by large-scale transcriptome perturbations and motif inference.

Alternate Accession IDs

GSE59059

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE16391
GGI: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial.

Publication Title

The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial.

Alternate Accession IDs

E-GEOD-16391

Sample Metadata Fields

Age, Specimen part, Disease stage, Treatment

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accession-icon GSE26679
comparison of powdery mildew-induced gene expression between Col-0 and the edr1 mutant
  • organism-icon Arabidopsis thaliana
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

The edr1 mutant of Arabidopsis thaliana displays enhanced resistance to the powdery mildew Golovinomyces cichoracearum, resulting in cell death and an absence of visible disease symptoms. To better characterize and understand the defense response of edr1, a time course of early signaling responses was performed after inoculation with powdery mildew and compared to the responses of wild-type Col-0. These time points represent early stages in the infection process, before any signs of susceptibility or resistance are visible.

Publication Title

Negative regulation of defence signalling pathways by the EDR1 protein kinase.

Alternate Accession IDs

E-GEOD-26679

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP074850
Systems genetics reveals a transcriptional network associated with susceptibility in the maize-gray leaf spot pathosystem
  • organism-icon Zea mays
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Background: Maize plants developed typical gray leaf spot disease (GLS) symptoms initiating at the lower leaves and progressing to upper leaves through the season. Leaf material was collected at 77 days after planting, at which stage there were a large number of GLS disease necrotic lesions on lower leaves (8% surface area on average determined by digital image analysis), but very few lesions and only at chlorotic stage on leaves above the ear (average of 0.2% lesion surface area). Method:To collect material that reflected a difference between C.zeina infected B73 leaves and control B73 leaf material, samples were collected from two lower GLS infected leaves (second and third leaf internode below ear) , and two upper leaves with minimal GLS symptoms (second and third internode above ear), respectively. The two lower leaves from each plant were pooled prior to RNA extraction, and the two upper leaves from each plant were pooled prior to RNA extraction. Upper and lower leaf samples from three maize B73 plants were subjected to RNA sequencing individually. The three maize plants were selected randomly as one plant per row from three rows of ten B73 plants each. Result: A systems genetics strategy revealed regions on the maize genome underlying co-expression of genes in susceptible and resistance responses, including a set of 100 genes common to the susceptible response of sub-tropical and temperate maize. Overall design: To collect material that reflected a difference between C.zeina infected B73 leaves and control B73 leaf material, samples were collected from two lower GLS infected leaves (second and third leaf internode below ear) , and two upper leaves with minimal GLS symptoms (second and third internode above ear), respectively. The two lower leaves from each plant were pooled prior to RNA extraction, and the two upper leaves from each plant were pooled prior to RNA extraction. Upper and lower leaf samples from three maize B73 plants were subjected to RNA sequencing individually. The three maize plants were selected randomly as one plant per row from three rows of ten B73 plants each.

Publication Title

Systems genetics reveals a transcriptional network associated with susceptibility in the maize-grey leaf spot pathosystem.

Alternate Accession IDs

GSE81344

Sample Metadata Fields

Subject

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accession-icon GSE14420
Global gene expression of Arabidopsis lines with altered ANAC102 expression under normal and low oxygen conditions
  • organism-icon Arabidopsis thaliana
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Global gene expression was compared between Arabidopsis lines with altered expression of ANAC102 (over-expressed and knocked-out) and wild-type. ANAC102 is a putative NAC domain transcription factor. Gene expression was compared between an ANAC102 over-expressing line and parental ecotype C24 under ambient atmosphere to determine which genes ANAC102 is capable of regulating. Gene expression was also compared between three week old plants of an ANAC102 knock-out line and parental ecotype Col-0 under 0.1% Oxygen and ambient atmosphere conditions to determine which genes may require ANAC102 for appropriate expression under these conditions. Gene expression was also compared between imbibed seeds of an ANAC102 knock-out line and parental ecotype Col-0 following a 0.1% Oxygen treatment.

Publication Title

The low-oxygen-induced NAC domain transcription factor ANAC102 affects viability of Arabidopsis seeds following low-oxygen treatment.

Alternate Accession IDs

E-GEOD-14420

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE16467
Global gene expression analysis of waterlogging stressed Cotton root and leaf tissue
  • organism-icon Gossypium hirsutum
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

Global gene expression was compared between roots of cotton plants (variety Sicot 71) flooded for 4 hours and roots of unflooded cotton plants. Global gene expression was also compared between leaves of cotton plants (variety Sicot 71) flooded for 24 hours and leaves of unflooded cotton plants.

Publication Title

Global gene expression responses to waterlogging in roots and leaves of cotton (Gossypium hirsutum L.).

Alternate Accession IDs

E-GEOD-16467

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE21504
Global gene expression analysis of Arabidopsis Col-0 under normal and low oxygen conditions
  • organism-icon Arabidopsis thaliana
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Global gene expression was compared between root RNA samples from three-week-old Arabidopsis Col-0 plants subjected to 0.1% oxygen (balance nitrogen) or ambient atmospheric conditions.

Publication Title

Comparisons of early transcriptome responses to low-oxygen environments in three dicotyledonous plant species.

Alternate Accession IDs

E-GEOD-21504

Sample Metadata Fields

Age, Specimen part, Treatment

View Samples
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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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