Microarray Data Explorer
Info 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.
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GROUP CONDITION SAMPLES
Female mice islets
GSM1429373 GSM1429374 GSM1429375
GSM1429370 GSM1429371 GSM1429372
GSM1429364 GSM1429365 GSM1429366
GSM1429367 GSM1429368 GSM1429369
Description

Submission Date: Jul 07, 2014

Summary: ABSTRACT:Pregnancy requires a higher functional beta cell mass and this is associated with profound changes in the gene expression profile of pancreatic islets. Taking Tph1 as a sensitive marker for pregnancy-related islet mRNA expression in female mice, we previously identified prolactin receptors and placental lactogen as key signalling molecules. Since beta cells from male mice also express prolactin receptors, the question arose whether male and female islets have the same phenotypic resilience at the mRNA level during pregnancy. We addressed this question in vitro, by using islet tissue culture with placental lactogen and in vivo, by transplanting male or female islets into female acceptor mice. Additionally, the islet mRNA expression of pregnant prolactin receptor deficient mice was compared with that of their pregnant wild-type littermates. When cultured with placental lactogen, or transplanted in female recipients that became pregnant (day 12.5), male islets induced the 'islet pregnancy gene signature', which we defined as the 12 highest induced genes in non-transplanted female islets at day 12.5 of pregnancy. In addition, serotonin immunoreactivity was also induced in these male transplanted islets at day 12.5 of pregnancy. In order to investigate the importance of prolactin receptors in these mRNA changes we used a prolactin receptor deficient mouse model. For the 12 genes of the signature, which are highly induced in control pregnant mice, no significant induction of mRNA transcripts was found at day 9.5 of pregnancy. Together, our results support the key role of placental lactogen as a circulating factor that can trigger the pregnancy mRNA profile in male and female beta cells.

GEO Accession ID: GSE59141

PMID: 25816302

Description

Submission Date: Jul 07, 2014

Summary: ABSTRACT:Pregnancy requires a higher functional beta cell mass and this is associated with profound changes in the gene expression profile of pancreatic islets. Taking Tph1 as a sensitive marker for pregnancy-related islet mRNA expression in female mice, we previously identified prolactin receptors and placental lactogen as key signalling molecules. Since beta cells from male mice also express prolactin receptors, the question arose whether male and female islets have the same phenotypic resilience at the mRNA level during pregnancy. We addressed this question in vitro, by using islet tissue culture with placental lactogen and in vivo, by transplanting male or female islets into female acceptor mice. Additionally, the islet mRNA expression of pregnant prolactin receptor deficient mice was compared with that of their pregnant wild-type littermates. When cultured with placental lactogen, or transplanted in female recipients that became pregnant (day 12.5), male islets induced the 'islet pregnancy gene signature', which we defined as the 12 highest induced genes in non-transplanted female islets at day 12.5 of pregnancy. In addition, serotonin immunoreactivity was also induced in these male transplanted islets at day 12.5 of pregnancy. In order to investigate the importance of prolactin receptors in these mRNA changes we used a prolactin receptor deficient mouse model. For the 12 genes of the signature, which are highly induced in control pregnant mice, no significant induction of mRNA transcripts was found at day 9.5 of pregnancy. Together, our results support the key role of placental lactogen as a circulating factor that can trigger the pregnancy mRNA profile in male and female beta cells.

GEO Accession ID: GSE59141

PMID: 25816302

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Precomputed Differential Gene Expression

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Differential Gene Expression Analysis
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