Background: Gene expression patterns provide a detailed view of cellular functions. Comparison of profiles in disease vs normal conditions provides insights into the processes underlying disease progression. However, availability and integration of public gene expression datasets remains a major challenge. The aim of the present study was to explore the transcriptome of pancreatic islets and, based on this information, to prepare a comprehensive and open access inventory of insulin-producing beta cell gene expression, the Beta Cell Gene Atlas (BCGA).
Methods: We performed Massively Parallel Signature Sequencing (MPSS) analysis of human pancreatic islet samples and microarray analyses of purified rat beta cells, alpha cells and INS-1 cells, and compared the information with available array data in the literature.
Results: MPSS analysis detected around 7600 mRNA transcripts, of which around a third were of low abundance. We identified 2000 and 1400 transcripts that are enriched/depleted in beta cells compared to alpha cells and INS-1 cells, respectively. Microarray analysis identified around 200 transcription factors that are differentially expressed in either beta or alpha cells. We reanalyzed publicly available gene expression data and integrated these results with the new data from this study to build the BCGA. The BCGA contains basal (untreated conditions) gene expression level estimates in beta cells as well as in different cell types in human, rat and mouse pancreas. Hierarchical clustering of expression profile estimates classify cell types based on species while beta cells were clustered together.
Conclusion: Our gene atlas is a valuable source for detailed information on the gene expression distribution in beta cells and pancreatic islets along with insulin producing cell lines. The BCGA tool, as well as the data and code used to generate the Atlas are available at the T1Dbase website (T1DBase.org).
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http://dx.doi.org/10.1186/1755-8794-2-3 | DOI Listing |
Dig Dis Sci
January 2025
Ningxia Medical University, Xing Qing Block, Shengli Street No.1160, Yin Chuan City, 750004, Ningxia Province, People's Republic of China.
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View Article and Find Full Text PDFClin Rheumatol
January 2025
Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
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View Article and Find Full Text PDFBiochem Genet
January 2025
Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
This study aimed to identify shared gene expression related to circadian rhythm disruption in polycystic ovary syndrome (PCOS) and non-alcoholic fatty liver disease (NAFLD) to discover common diagnostic biomarkers. Visceral fat RNA samples were collected from 12 PCOS and 14 non-PCOS patients, a sample size representing the clinical situation and sufficient to capture PCOS gene expression profiles. Along with liver transcriptome profiles from NAFLD patients, these data were analyzed to identify crosstalk circadian rhythm-related genes (CRRGs) between the diseases.
View Article and Find Full Text PDFClin Exp Med
January 2025
Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
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View Article and Find Full Text PDFArch Dermatol Res
January 2025
Department of Physiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
We have recently shown that fluoxetine (FX) suppressed polyinosinic-polycytidylic acid-induced inflammatory response and endothelin release in human epidermal keratinocytes, via the indirect inhibition of the phosphoinositide 3-kinase (PI3K)-pathway. Because PI3K-signaling is a positive regulator of the proliferation, in the current, highly focused follow-up study, we assessed the effects of FX (14 µM) on the proliferation and differentiation of human epidermal keratinocytes. We found that FX exerted anti-proliferative actions in 2D cultures (HaCaT and primary human epidermal keratinocytes [NHEKs]; 48- and 72-h; CyQUANT-assay) as well as in 3D reconstructed epidermal equivalents (48-h; Ki-67 immunohistochemistry).
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