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accession-icon GSE5528
Identifying targets of FLC at 27oC
  • organism-icon Arabidopsis thaliana
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

FLOWERING LOCUS C (FLC) is a MADS box transcription factor that plays a well characterised role in repressing the vegetative to floral transition of Arabidopsis thaliana. FLC has also been shown to affect the Arabidopsis circadian clock, with mutant seedlings showing short circadian periods. In a previous study, we identified the temperature-dependent circadian period QTL PerCv5b near the FLC locus on the top arm of Chromosome 5. PerCv5b caused a significant period effect at 27oC but not at 12oC or 22oC. Temperature-dependent circadian period phenotypes and a known polymorphism in the Ler allele made FLC a strong candidate gene for PerCv5b. The period effect of FLC was enhanced by combination with alleles of FRIGIDA (FRI), a gene shown to up-regulate FLC's expression.

Publication Title

FLOWERING LOCUS C mediates natural variation in the high-temperature response of the Arabidopsis circadian clock.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP067378
Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis (PAGODA)
  • organism-icon Mus musculus
  • sample-icon 557 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The extent of transcriptional diversity in mouse NPCs is likely to be influenced by a variety of unexamined factors that include programmed cell death, genomic mosaicism as well as a variety of “environmental” influences such as changes in exposure to signaling lipids. We therefore used scRNA-seq to assess a cohort of cortical NPCs from an embryonic mouse. We demonstrate that PAGODA (Pathway And Geneset OverDispersion Analysis) effectively recovers the known neuroanatomical and functional organization of NPCs, identifying multiple aspects of transcriptional heterogeneity within the developing mouse cortex that are difficult to discern by the existing heterogeneity analysis approaches. Overall design: Examination of mouse NPC transcriptional heterogeneity via single cell RNA-seq

Publication Title

Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP076704
The transcription factor, Nuclear factor, erythoid 2 (Nfe2), is a regulator of the oxidative stress response during Danio rerio development
  • organism-icon Danio rerio
  • sample-icon 54 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Development is a complex and well-defined process characterized by rapid cell proliferation and apoptosis. At this stage in life, a developmentally young organism is more sensitive to toxicants and other stressors when compared to an adult. In response to pro-oxidant exposure, members of the Cap’n’Collar (CNC) basic leucine zipper (b-ZIP) transcription factor family (including the Nfe2-related factors, Nrfs) activate the expression of genes that contribute to reduced toxicity. Here, we studied the role of the Nrf protein, Nfe2, in the developmental response to pro-oxidant exposure in the zebrafish. Following acute waterborne exposures to diquat or tert-buytlhydroperoxide (tBOOH) at three developmental stages, wildtype (WT) and nfe2 knockout (KO) embryos and larvae were morphologically scored and their transcriptomes sequenced. Overall design: Wildtype animals were on the AB background and an additional germline nfe2 knockout strain were created by disruption of the nfe2 reading frame. Waterborne exposures to either diquat or tBOOH were carried out at three different developmental stages: 2 hours post fertilization (hpf), 48hpf, and 96hpf in 3 pools of 30 embryos per condition. Animals were exposed to no treatment, 20µM diquat or 1mM tBOOH for a 4-hour dosing period. Total RNA was isolated from pooled animals and 50 bp, paired end, libraries were sequenced using the Illumina HiSeq 2000 platform, with approximately 25 million reads per sample. Reads were then aligned to the Ensembl GRCz10 zebrafish reference genome using Tophat2 and raw counts data normalized using DESeq2. Gene annotation was from Ensemble for GRCz10.

Publication Title

The transcription factor, Nuclear factor, erythroid 2 (Nfe2), is a regulator of the oxidative stress response during Danio rerio development.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE32056
The effect of trypsin-2 on human tongue squamous cell carcinoma cell line gene expression
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The level of trypsin-2 has been shown to correlate with the malignancy and metastatic potential of many cancer.

Publication Title

Trypsin-2 enhances carcinoma invasion by processing tight junctions and activating ProMT1-MMP.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE51191
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1 in the regulation of the hypoxic gene program
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II, Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE51190
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1 in the regulation of the hypoxic gene program [microarray: kD_AP1]
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st), Illumina Genome Analyzer II

Description

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.

Publication Title

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Sample Metadata Fields

Treatment

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accession-icon E-MEXP-736
Transcription profiling by array of zebrafish ZF4 and PAC2 cells after treatment with fetal calf serum
  • organism-icon Danio rerio
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Zebrafish Genome Array (zebrafish)

Description

In this study, zebrafish ZF4 and PAC2 cells were seeded in 0.5% or 1% FCS, respectively, and grown to 85% confluence and subsequently cultured for 24 hours without serum. Then they were treated with either medium without serum or medium with serum (ZF4 in 10% FCS and PAC2 in 15% FCS).After 6 hours, RNA was extracted from the cells and analyzed using the Affymetrix GeneChip Zebrafish Genome Array (GeneChip 430). There are 15502 oligonucleotide sets on each Affymetrix chip, 14895 of which can be linked to a UniGene assignment (Unigene data set 06-12-2005).

Publication Title

Genetic and transcriptome characterization of model zebrafish cell lines.

Sample Metadata Fields

Cell line, Compound

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accession-icon GSE80521
The genomic context and co-recruitment of SP1 affect ERR co-activation by PGC-1 in muscle cells [array]
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The peroxisome proliferator-activated receptor co-activator 1 (PGC-1) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor (ERR) in the regulation of oxidative substrate metabolism. Despite a close functional relationship, the interaction between these two proteins has not been studied on a genomic level. We now mapped the genome-wide binding of ERR to DNA in skeletal muscle cell line with elevated PGC-1 and linked the DNA recruitment to global PGC-1 target gene regulation. We found that, surprisingly, ERR co-activation by PGC-1 is only observed in the minority of all PGC-1 recruitment sites. Nevertheless, a majority of PGC-1 target gene expression is dependent on ERR. Intriguingly, the interaction between these two proteins is controlled by the genomic context of response elements, in particular the relative GC and CpG content, monomeric and dimeric repeat binding site configuration for ERR, and adjacent recruitment of the transcription factor SP1. These findings thus not only reveal an unprecedented insight into the regulatory network underlying muscle cell plasticity, but also strongly link the genomic context of DNA response elements to control transcription factor - co-regulator interactions.

Publication Title

The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE51189
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1 in the regulation of the hypoxic gene program [microarray: PGC1a_vs_GFP]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II, Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.

Publication Title

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE80522
The genomic context and co-recruitment of SP1 affect ERR co-activation by PGC-1 in muscle cells
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.

Sample Metadata Fields

Specimen part

View Samples
...

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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