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accession-icon GSE62099
CD161 defines a transcriptional and functional phenotype shared across distinct human T cell lineages
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

CD161 defines a transcriptional and functional phenotype across distinct human T cell lineages.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE62096
CD161 defines a transcriptional and functional phenotype shared across distinct human T cell lineages (CD 8)
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

T lymphocytes are conventionally divided into subsets based upon expression of co-receptors, cytokines and surface molecules. By mRNA microarray analysis, T lymphocytes that express the C-type lectin CD161 were identified to share a transcriptional profile, which led to the identification of an innate function across these previously defined subsets, including CD8, CD4 and TCRgd T cells.

Publication Title

CD161 defines a transcriptional and functional phenotype across distinct human T cell lineages.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE62095
CD161 defines a transcriptional and functional phenotype shared across distinct human T cell lineages (CD4)
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

T lymphocytes are conventionally divided into subsets based upon expression of co-receptors, cytokines and surface molecules. By mRNA microarray analysis, T lymphocytes that express the C-type lectin CD161 were identified to share a transcriptional profile, which led to the identification of an innate function across these previously defined subsets, including CD8, CD4 and TCRgd T cells.

Publication Title

CD161 defines a transcriptional and functional phenotype across distinct human T cell lineages.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE110531
Developmental and Functional Heterogeneity of White Adipocytes within a Single Fat Depot
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We and others have previously observed that adipocytes and preadipocytes taken from different adipose tissue depots are characterized by differential expression of developmental and patterning genes (Dankel et al., 2010; Ferrer-Lorente et al., 2014; Gesta et al., 2006; Lee et al., 2017a; Lee et al., 2013; Macotela et al., 2012; Tchkonia et al., 2007; Yamamoto et al., 2010). To investigate how adipocyte heterogeneity and differences in the expression of developmental genes might impact the biology of adipocytes and preadipocytes, we created preadipocyte cell lines from the stromovascular fraction (SVF) isolated from the scapular white, inguinal, perigonadal, perirenal, and mesenteric fat pads of 6-week old male Immortomouse (Jat et al., 1991).During routine culture of the subcutaneous and visceral/perigonadal clonal cell lines, we observed extreme variation in media acidification rates that was unrelated to the fat pad of origin, the differentiation capacity of the cells, or the rate of their proliferation, suggesting metabolic heterogeneity. To further investigate this possibility, 24 clonal cell lines (12 each from subcutaneous and perigonadal fat) were selected based on variable media acidification rates, and their mRNA expression pattern determined by microarray analysis. The expression data was clustered using three different algorythms, and the consensus was used to categorize each type of adipose tissue.

Publication Title

Developmental and functional heterogeneity of white adipocytes within a single fat depot.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE70489
Tbx15 Controls Skeletal Muscle Fiber Type Determination and Muscle Metabolism
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Skeletal muscle is composed of both slow-twich oxidative myofibers and fast-twitch glycolytic myofibers that differentially impact muscle metabolism, function, and eventually whole-body physiology. In the present study, we find that the mesodermal transcription factor T-box 15 (Tbx15) is highly and specifically expressed in glycolytic myofibers. Ablation of Tbx15 in vivo leads to a decrease in muscle size due to a decrease in the number of glycolytic fibers, associated with a small increase in the number of oxidative fibers. This shift in fiber composition results in muscles with slower myofiber contraction and relaxation, and also results in decreased whole-body oxygen consumption, decreased spontaneous activity, increased adiposity, and glucose intolerance. In order to identify genes regulated by Tbx15, we utilized C2C12 myoblasts with either a stable retroviral over-expression or stable lentiviral knockdown of Tbx15.

Publication Title

Tbx15 controls skeletal muscle fibre-type determination and muscle metabolism.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE97272
A history of obesity leaves an inflammatory fingerprint in liver and adipose tissue
  • organism-icon Mus musculus
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A history of obesity leaves an inflammatory fingerprint in liver and adipose tissue.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE97269
A history of obesity leaves an inflammatory fingerprint in liver and adipose tissue [Liver]
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Dieting is a popular yet often ineffective way to lower body weight, as the majority of people regain most of their pre-dieting weights in a relatively short time. The underlying molecular mechanisms driving weight regain and the increased risk for metabolic disease are still incompletely understood. Here we investigate the molecular alterations inherited from a history of obesity. In our model, male HFD fed obese C57BL/6J mice, were switched to a low caloric chow diet, resulting in a decline of body weight to that of lean mice. Within seven weeks after diet switch, most obesity associated phenotypes, such as body mass, glucose intolerance and blood metabolite levels were reversed. However, hepatic inflammation, hepatic steatosis as well as hypertrophy and inflammation of perigonadal, but not subcutaneous, adipocytes persisted in formerly obese mice. Transcriptional profiling of liver and perigonadal fat revealed an upregulation of pathways associated with immune function and cellularity. Thus, we show that weight reduction leaves signs of inflammation in liver and perigonadal fat, indicating that persisting proinflammatory signals in liver and adipose tissue could contribute to an increased risk of formerly obese subjects to develop the metabolic syndrome upon recurring weight gain.

Publication Title

A history of obesity leaves an inflammatory fingerprint in liver and adipose tissue.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE68324
Expression data from MCF7 cells: control or tuberin-depleted
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of the expression profiles of MCF7 cells transduced with a control shRNA and an TSC2-targeted shRNA (leading to tuberin depletion).

Publication Title

Lymphangioleiomyomatosis Biomarkers Linked to Lung Metastatic Potential and Cell Stemness.

Sample Metadata Fields

Cell line

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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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