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accession-icon GSE43270
Genome wide-DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2), Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

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accession-icon GSE43191
Genome wide-DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients (gene expression)
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2), Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

The aim of this study is to identify, for the first time, the genome-wide DNA methylation profiles of human articular chondrocytes from OA and healtly cartilage samples.

Publication Title

Genome-wide DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE21383
Expression data from porcine ovary tissue of sows from two prolificacy levels
  • organism-icon Sus scrofa
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

Previous results from a genome scan in a F2 Iberian by Meishan intercross showed several chromosome regions associated with litter size traits. In order to identify candidate genes underlying these QTL we have performed an ovary gene expression analysis during pregnancy. F2 sows were ranked by their estimated breeding values for prolificacy, the six sows with higher EBV (HIGH prolificacy) and the six with lower EBV (LOW prolificacy) were selected. Samples were hybridized to Affymetrix porcine expression microarrays. The statistical analysis with a mixed-model approach identified 221 differentially expressed probes, representing 189 genes. These genes were functionally annotated in order to identify the genetic pathways overrepresented. Among the most represented functional groups the first one was immune system response activation against external stimulus. The second group was made up of genes which regulate the maternal homeostasis by complement and coagulation cascades. The last group was involved on lipid and fatty acid enzymes of metabolic processes, which participate in steroidogenesis pathway. In order to identify powerful candidate genes for prolificacy, the second approach of this study was merging microarray data with position information of QTL affecting litter size, previously detected in the same experimental cross. According to this, we have identified 27 differentially expressed genes co-localized with QTL for litter size traits, which fulfill the biological, positional and functional criteria.

Publication Title

Differential gene expression in ovaries of pregnant pigs with high and low prolificacy levels and identification of candidate genes for litter size.

Sample Metadata Fields

Specimen part

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accession-icon GSE67796
Expression data from liver, PFC and amygdala of mice treated with PPAR agonists
  • organism-icon Mus musculus
  • sample-icon 112 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists have demonstrated therapeutic properties for several brain disorders, including alcohol dependence. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated and little is known about their effects in the brain. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar and fenofibrate decreased ethanol consumption in male C57BL/6J mice while bezafibrate did not. Hypothesizing that fenofibrate and tesaglitazar are causing brain gene expression changes that precipitate the reduction in ethanol drinking, we gave daily oral injections of fenofibrate, tesaglitazar and bezafibrate to mice for eight consecutive days and collected liver, prefrontal cortex and amygdala 24 hours after last injection. RNA was isolated and purified using MagMAX-96 Total RNA Isolation Kit. Biotinylated, amplified cRNA was generated using Illumina TotalPrep RNA Amplification Kit and hybridized to Illumina MouseWG-6 v2.0 Expression microarrays.

Publication Title

PPAR agonists regulate brain gene expression: relationship to their effects on ethanol consumption.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE89445
Expression data from D.melanogaster guts with a constitutively active Imd in the presence or absence of a microbiome
  • organism-icon Drosophila melanogaster
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

Innate immune responses contributed to the containment of intestinal microbes.

Publication Title

Constitutive Immune Activity Promotes Tumorigenesis in Drosophila Intestinal Progenitor Cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE51730
Profiling the transcriptome: synaptoneurosomes capture the molecular effects of alcohol consumption
  • organism-icon Mus musculus
  • sample-icon 40 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Action of alcohol on synaptic mRNA in the amygdala of mice

Publication Title

The synaptoneurosome transcriptome: a model for profiling the emolecular effects of alcohol.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE12978
Microarray Analysis of the transcriptome of the Subfornical Organ in the rat
  • organism-icon Rattus norvegicus
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

In these studies we have for the first time described the transcriptome of the rat SFO, and have in addition identified genes the expression of which is significantly modified by either water or food deprivation.

Publication Title

Microarray analysis of the transcriptome of the subfornical organ in the rat: regulation by fluid and food deprivation.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE10898
Transcriptome architecture across tissues in the pig
  • organism-icon Sus scrofa
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

Artificial selection has resulted in animal breeds with extreme phenotypes. As an organism is made up of many different tissues and organs, each with its own genetic programme, it is pertinent to ask what are the relative contributions of breed or sex when assessed across tissues.

Publication Title

Transcriptome architecture across tissues in the pig.

Sample Metadata Fields

Age

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accession-icon GSE41342
Data from a time course study of gene expression in a mouse model of osteoarthritis
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The purpose of this study was to characterize the histologic development of OA in a mouse model where OA is induced by destabilization of the medial meniscus (DMM model) and to identify genes regulated during different stages of the disease, using RNA isolated from the joint organ and analyzed using microarrays.427 genes from the microarrays passed consistency and significance filters. There was an initial up-regulation at 2 and 4 weeks of genes involved in morphogenesis, differentiation, and development, including growth factor and matrix genes, as well as transcription factors including Atf2, Creb3l1, and Erg. Most genes were off or down-regulated at 8 weeks with the most highly down-regulated genes involved in cell division and the cytoskeleton. Gene expression increased at 16 weeks, in particular extracellular matrix genes including Prelp, Col3a1 and fibromodulin.The results support a phasic development of OA with early matrix remodelling and transcriptional activity followed by a more quiescent period that is not maintained.

Publication Title

Disease progression and phasic changes in gene expression in a mouse model of osteoarthritis.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE12837
Gene expression in human myeloid cells.
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Human myelopoiesis is an exciting biological model for cellular differentiation since it represents a plastic process where pluripotent stem cells gradually limit their differentiation potential, generating different precursor cells which finally evolve into distinct terminally differentiated cells. This study aimed at investigating the genomic expression during myeloid differentiation through a computational approach that integrates gene expression profiles with functional information and genome organization. The genomic distribution of myelopoiesis genes was investigated integrating transcriptional and functional characteristics of genes. The analysis of genomic expression during human myelopoiesis using an integrative computational approach allowed discovering important relationships between genomic position, biological function and expression patterns and highlighting chromatin domains, including genes with coordinated expression and lineage-specific functions.

Publication Title

Motif discovery in promoters of genes co-localized and co-expressed during myeloid cells differentiation.

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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Developed by the Childhood Cancer Data Lab

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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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