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accession-icon GSE48522
Akt signalling leads to stem cell activation and promotes tumour development in epidermis.
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
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Description

A permantly active form of the oncogene Akt was expressed in the keratinocytes of the basal proliferative layer of the epidermis. Stem cells of the hair follicle expressing the cell surface marker CD34 were isolated. RNA form the CD34(+) and CD34(-) keratinocytes was extracted and and hybridized to Mouse Genome 430 2.0 Affymetrix arrays.

Publication Title

Akt signaling leads to stem cell activation and promotes tumor development in epidermis.

Sample Metadata Fields

Specimen part

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accession-icon GSE24928
Gene expression change induced by bisphenol A in mouse urogenital sinus
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
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Description

Bisphenol A (BPA), an endocrine-disrupting chemical (EDC), is a well-known, ubiquitous estrogenic chemical. To investigate the effects of fetal exposure to low-dose BPA on the development of the prostate, we first examined the alterations of in situ sex steroid hormonal environment in the mouse urogenital sinus (UGS).

Publication Title

Endocrine disrupter bisphenol A increases in situ estrogen production in the mouse urogenital sinus.

Sample Metadata Fields

Specimen part

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accession-icon GSE8349
Microarray platform comparison study of hippocampal gene expression in DCLK1 transgenic and wild-type mice
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
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Description

The aim of the present study was to compare, on a statistical basis, the performance of different microarray platforms to detect differences in gene expression in a realistic and challenging biological setting. Gene expression profiles in the hippocampus of five wild-type and five transgenic C-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina and home-spotted oligonucleotide arrays. We observed considerable overlap between the different platforms, the overlap being better detectable with significance level-based ranking than with a p-value based cut-off. Confirming the qualitative agreement between platforms, Pathway analysis consistently demonstrated aberrances in GABA-ergic signalling in the transgenic mice, even though pathways were represented by only partially overlapping genes on the different platforms.

Publication Title

Can subtle changes in gene expression be consistently detected with different microarray platforms?

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE11291
Effect of age, calorie restriction and resveratrol on gene expression in mouse heart, brain, and skeletal muscle
  • organism-icon Mus musculus
  • sample-icon 60 Downloadable Samples
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Description

Resveratrol in high doses has been shown to extend lifespan in some studies in invertebrates and to prevent early mortality in mice fed a high-fat diet. We fed mice from middle age (14-months) to old age (30-months) either a control diet, a low dose of resveratrol (4.9 mg kg-1 day-1), or a calorie restricted (CR) diet and examined genome-wide transcriptional profiles.

Publication Title

A low dose of dietary resveratrol partially mimics caloric restriction and retards aging parameters in mice.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE20244
A comprehensive methylome map of lineage commitment from hematopoietic progenitors
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
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Description

Epigenetic modifications must underlie lineage-specific differentiation since terminally differentiated cells express tissue-specific genes, but their DNA sequence is unchanged. Hematopoiesis provides a well-defined model of progressive differentiation in which to study the role of epigenetic modifications in cell fate decisions. Multi-potent progenitors (MPPs) can differentiate into all blood cell lineages, while downstream progenitors commit to either myeloerythroid or lymphoid lineages. While DNA methylation is critical for myeloid versus lymphoid differentiation, as demonstrated by the myeloerythroid bias in Dnmt1 hypomorphs {Broske, 2009 #6}, a comprehensive DNA methylation map of hematopoietic progenitors, or of any cell lineage, does not exist. Here we have generated a mouse DNA methylation map, examining 4.6 million CpG sites throughout the genome including all CpG islands and shores, examining MPPs, all lymphoid progenitors (ALPs), common myeloid progenitors (CMPs), granulocyte/macrophage progenitors (GMPs), and thymocyte progenitors (DN1, DN2, DN3). Interestingly, differentiation towards the myeloid lineage corresponds with a net decrease in DNA methylation, while lymphoid commitment involves a net increase in DNA methylation, but both show substantial dynamic changes consistent with epigenetic plasticity during development. By comparing lineage-specific DNA methylation to gene expression array data, we find many examples of genes and pathways not previously known to be involved in lymphoid/myeloid differentiation, such as Gcnt2, Arl4c, Gadd45, and Jdp2. Several transcription factors, including Meis1 and Prdm16 were methylated and silenced during differentiation, suggesting a role in maintaining an undifferentiated state. Additionally, epigenetic modification of modifiers of the epigenome appears to be important in hematopoietic differentiation. Our results directly demonstrate that modulation of DNA methylation occurs during lineage-specific differentiation, often correlating with gene expression changes, and define a comprehensive map of the methylation and transcriptional changes that accompany myeloid versus lymphoid fate decisions.

Publication Title

Comprehensive methylome map of lineage commitment from haematopoietic progenitors.

Sample Metadata Fields

Sex, Age

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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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