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accession-icon GSE38989
Light- and Phytochrome-Dependent Regulation of Hypocotyl Elongation in Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

To identify and characterize genes required for tissue-specific phytochrome responses during hypocotyl development in far-red-light grown bvr lines, we performed gene transcriptional profiling using bvr lines with mesophyll-specific phytochrome inactivation (cab3: :pBVR2). We identified several candidate genes whose expression is significantly altered in lines with mesophyll tissue-specific BVR expression (Cab3::pBVR2), compared to constitutive phytochrome inactivation lines, i.e. 35S-driven BVR lines (35S::pBVR3). No-0 is used as wild-type (WT)

Publication Title

Downstream effectors of light- and phytochrome-dependent regulation of hypocotyl elongation in Arabidopsis thaliana.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MEXP-3639
Transcription profiling by array of Escherichia coli (strain MG1655) to study cellular responses to the oxidizing effects of bleach
  • organism-icon Escherichia coli
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

E. coli MG1655 was grown in MOPS minimal glucose medium at 37 degrees C with aeration to an OD600 of 0.4 - 0.5, and HOCl was added to a final concentration of 400 ?M. 0.5 ml samples were collected in liquid nitrogen immediately before, 5 min after, and 10 min after HOCl addition, and total RNA was prepared using the RNeasy? Midi kit (Qiagen). cDNA synthesis, array hybridization to Affymetrix GeneChip E. coli genome 2.0 Arrays, and imaging were performed according to Affymetrix guidelines at the Affymetrix and Microarray Core facility at the University of Michigan, Ann Arbor.

Publication Title

No associated publication

Sample Metadata Fields

Compound, Time

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accession-icon GSE15904
Genetic Heterogeneity in Mouse Mammary Tumors
  • organism-icon Mus musculus
  • sample-icon 126 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Human cancers result from a complex series of genetic alterations resulting in heterogeneous disease states. Dissecting this heterogeneity is critical for understanding underlying mechanisms and providing opportunities for therapeutics matching the complexity. Mouse models of cancer have generally been employed to reduce this complexity and focus on the role of single genes. Nevertheless, our analysis of tumors arising in the MMTV-Myc model of mammary carcinogenesis reveals substantial heterogeneity, seen in both histological and expression phenotypes. One contribution to this heterogeneity is the substantial frequency of activating Ras mutations, the frequency of which can be changed by alterations in Myc. Additionally, we show that these Myc-induced mammary tumors exhibit even greater heterogeneity, revealed by distinct histological subtypes as well as distinct patterns of gene expression, than many other mouse models of tumorigenesis. Two of the major histological subtypes are characterized by differential patterns of cellular signaling pathways, including B-Catenin and Stat3 activities. We also demonstrate the predictive nature of this approach though examining metastatic potential. Together, these data reveal that a combination of histological and genomic analyses can uncover substantial heterogeneity in mammary tumor formation and therefore highlight aspects of tumor phenotype not evident in the population as a whole.

Publication Title

Genetic heterogeneity of Myc-induced mammary tumors reflecting diverse phenotypes including metastatic potential.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE104397
Expression data from MMTV-PyMT Induced Tumors
  • organism-icon Mus musculus
  • sample-icon 80 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Loss of E2F transcription factos alters metastatic capacity of MMTV-PyMT tumors.

Publication Title

Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers.

Sample Metadata Fields

Disease

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accession-icon GSE24594
MMTV-Myc tumor development in E2F-null backgrounds
  • organism-icon Mus musculus
  • sample-icon 80 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Advances in genomic signatures have begun to dissect breast cancer heterogeneity, and application of these signatures will allow the prediction of which pathways are important in tumor development. Here we used genomic signatures to predict involvement of specific E2F transcription factors in Myc-induced tumors. We genetically tested this prediction by interbreeding Myc transgenics with mice lacking various activator E2F alleles. Tumor latency decreased in the E2F1 mutant background and significantly increased in both the E2F2 and E2F3 mutants. Investigating the mechanism behind these changes revealed a reduction in apoptosis in the E2F1 knockout strain. E2F2 and E2F3 mutant backgrounds alleviated Myc effects on the mammary gland, reducing the susceptible tumor target population. Gene expression data from tumors revealed that the E2F2 knockout background resulted in fewer tumors with EMT, corresponding with a reduction in probability of Ras activation. In human breast cancer we found that a low probability of E2F2 pathway activation was associated with increased relapse-free survival time. Together these data illustrate the predictive utility of genomic signatures in deciphering the heterogeneity within breast cancer and illustrate the unique genetic requirements for individual E2Fs in mediating tumorigenesis in both mouse models and human breast cancer.

Publication Title

Prediction and genetic demonstration of a role for activator E2Fs in Myc-induced tumors.

Sample Metadata Fields

Specimen part

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accession-icon GSE42533
Her2/Neu tumorigenesis and metastasis is regulated by E2F transcription factors
  • organism-icon Mus musculus
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

HER2 / Neu is amplified and overexpressed in a large proportion of human breast cancers, but the signaling pathways that contribute to tumor development and metastatic progression are not completely understood. Using gene expression data and pathway signatures we predicted a role for activator E2F transcription factors in Neu induced tumors. This was genetically tested by interbreeding Neu transgenics with knockouts of the three activator E2Fs. Loss of any E2F delayed Neu induced tumor onset. E2F1 loss accelerated tumor growth while E2F2 and E2F3 loss did not. Strikingly, it was observed that loss of E2F1 or E2F2 significantly reduced the metastatic capacity of the tumor and this was associated with a reduction in circulating tumor cells in the E2F2 knockout. Gene expression analysis between the tumors in the various E2F mutant backgrounds revealed that there was extensive compensation by other E2F family members in the individual knockouts, underscoring the importance of the E2Fs in HER2 / Neu induced tumors. Extension to HER2 positive human breast cancer revealed a number of HER2+ subtypes based on E2F activity with differences in relapse free survival times. Taken together these data demonstrate that the E2F transcription factors are integral to HER2+ tumor development and progression.

Publication Title

HER2/Neu tumorigenesis and metastasis is regulated by E2F activator transcription factors.

Sample Metadata Fields

Specimen part

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accession-icon GSE24517
Light- and plastid-regulated transcriptomes in Arabidopsis seedlings
  • organism-icon Arabidopsis thaliana
  • sample-icon 47 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Plastids emit signals that broadly affect cellular processes. Based on previous genetic analyses, we propose that plastid signaling regulates the downstream components of a light signaling network and that these interactions coordinate chloroplast biogenesis with both the light environment and development by regulating gene expression. We tested these ideas by analyzing light-regulated and plastid-regulated transcriptomes. We found that the plastid is a major regulator of light signaling, attenuating the expression of more than half of all light-regulated genes in our dataset and changing the nature of light regulation for a smaller fraction of these light-regulated genes.

Publication Title

Plastids are major regulators of light signaling in Arabidopsis.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE48454
Genes and pathways involved in cellular transformation by Marek's disease oncoprotein Meq
  • organism-icon Gallus gallus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE48453
Transcriptional Profiling of Meq-dependent Genes in Mareks Disease Resistant and Susceptible Inbred Chicken Lines
  • organism-icon Gallus gallus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

Mareks disease (MD) is an economically significant disease in chickens caused by the highly oncogenic Mareks disease virus (MDV). Understanding the genes and biological pathways that confer MD genetic resistance should lead towards the development of more disease resistant commercial poultry flocks or improved MD vaccines. MDV Meq, a bZIP transcription factor, is largely attributed for viral oncogenicity though only a few host target genes have been described, which has impeded our understanding of MDV-induced tumorigenesis. Given the importance of Meq in MDV-induced pathogenesis, we explored the role of Meq in genetic resistance to MDV. Using global transcriptome analysis to compare the host response between birds challenge with either wild type MDV or a recombinant lacking Meq, we identified a number of specific genes and pathways associated with either MD resistance. Integrating prior information from ChIP-seq, microarray analysis, and SNPs exhibiting allele-specific expression (ASE) in response to MDV infection from two inbred layer lines that differ greatly in MD genetic resistance, we were able to provide a evidence for 35 genes that SNPs within transcription factor binding sites can affect transcription factor binding and gene expression in an allele-specific manner.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE58710
Time Course of Gene Expression in the Substantia Nigra in Response to Intrastriatal 6-hydroxydopamine in the rat.
  • organism-icon Rattus norvegicus
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

The 6-hydroxydopamine (6OHDA) rat model of parkinsonism is among the first, and most commonly used, animal models of Parkinsons disease. It provides insight into the compensatory changes that occur in the brain after dopamine (DA) neuron degeneration. In order to better define the consequences of substantia nigra DA neuron loss on the neural and glial populations during and following nigrostriatal degeneration, tissue was collected and evaluated from the substantia nigra of 6OHDA or vehicle treated, or nave rats at 1, 2, 4, 6 & 16 weeks.

Publication Title

The longitudinal transcriptomic response of the substantia nigra to intrastriatal 6-hydroxydopamine reveals significant upregulation of regeneration-associated genes.

Sample Metadata Fields

Sex, 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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