Raw gene Expression data is sourced from GEO, and the appropriate db package for mapping probes to gene symbols was sourced from the Bioconductor AnnotationData packages.
You can read more about microarray data here.
Select conditions below to toggle them from the plot:
| GROUP | CONDITION | SAMPLES |
|---|---|---|
| C57BL6 mice; Sgpp2-/- genotype |
GSM1887624 GSM1887625 GSM1887626
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GSM1887630 GSM1887631 GSM1887632
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| C57BL6 mice; Wild Type genotype |
GSM1887621 GSM1887622 GSM1887623
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GSM1887627 GSM1887628 GSM1887629
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Submission Date: Sep 17, 2015
Summary: Sphingosine-1-phosphate (S1P) is a sphingolipid metabolite that regulates basic cell functions through metabolic and signaling pathways. Intracellular metabolism of S1P is controlled, in part, by two homologous S1P phosphatases, 1 and 2, which are encoded by Sgpp1 and Sgpp2, respectively. S1P phosphatase activity is needed for efficient recycling of sphingosine into the sphingolipid synthesis pathway. S1P phosphatase 1 is important for skin homeostasis, but little is known about the functional role of S1P phosphatase 2. To identify the functions of S1P phosphatase 2 in vivo, we studied mice with the Sgpp2 gene deleted. In contrast to Sgpp1-/- mice, Sgpp2-/- mice had normal skin and were viable into adulthood. Unexpectedly, WT mice expressed Sgpp2 mRNA at high levels in pancreatic islets when compared with other tissues. Sgpp2-/- mice had normal blood insulin levels and pancreatic islet size; however, Sgpp2-/- mice treated with a high-fat diet (HFD) had significantly lower blood insulin levels and smaller pancreatic islets compared with WT mice. The smaller islets in the HFD-treated Sgpp2-/- mice had a significantly lower adaptive β-cell proliferation rate in response to the diet compared with HFD-treated WT mice. Importantly, β-cells from Sgpp2-/- mice fed a normal diet showed significantly increased expression of proteins characteristic of the endoplasmic reticulum (ER) stress response compared with β-cells from WT mice. Our results suggest that Sgpp2 deletion causes β-cell ER stress, which is a known cause of β-cell dysfunction, and reveal a novel juncture in the sphingolipid recycling pathway that could impact the development of diabetes.
GEO Accession ID: GSE73131
PMID: 27059959
Submission Date: Sep 17, 2015
Summary: Sphingosine-1-phosphate (S1P) is a sphingolipid metabolite that regulates basic cell functions through metabolic and signaling pathways. Intracellular metabolism of S1P is controlled, in part, by two homologous S1P phosphatases, 1 and 2, which are encoded by Sgpp1 and Sgpp2, respectively. S1P phosphatase activity is needed for efficient recycling of sphingosine into the sphingolipid synthesis pathway. S1P phosphatase 1 is important for skin homeostasis, but little is known about the functional role of S1P phosphatase 2. To identify the functions of S1P phosphatase 2 in vivo, we studied mice with the Sgpp2 gene deleted. In contrast to Sgpp1-/- mice, Sgpp2-/- mice had normal skin and were viable into adulthood. Unexpectedly, WT mice expressed Sgpp2 mRNA at high levels in pancreatic islets when compared with other tissues. Sgpp2-/- mice had normal blood insulin levels and pancreatic islet size; however, Sgpp2-/- mice treated with a high-fat diet (HFD) had significantly lower blood insulin levels and smaller pancreatic islets compared with WT mice. The smaller islets in the HFD-treated Sgpp2-/- mice had a significantly lower adaptive β-cell proliferation rate in response to the diet compared with HFD-treated WT mice. Importantly, β-cells from Sgpp2-/- mice fed a normal diet showed significantly increased expression of proteins characteristic of the endoplasmic reticulum (ER) stress response compared with β-cells from WT mice. Our results suggest that Sgpp2 deletion causes β-cell ER stress, which is a known cause of β-cell dysfunction, and reveal a novel juncture in the sphingolipid recycling pathway that could impact the development of diabetes.
GEO Accession ID: GSE73131
PMID: 27059959
Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.
Differential expression signatures are automatically computed using the limma R package.
More options for differential expression are available to compute below.
Signatures:
Control Condition
Perturbation Condition
Only conditions with at least 1 replicate are available to select
Differential expression signatures can be computed using DESeq2 or characteristic direction.