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Epigenetic marks of Insulin‐related transcription factor network by DNA methylation
Author(s) -
Ito Shuhei,
Sato Shinya,
Yoshioka Tetsuya,
Ohgane Jun,
Tanaka Satoshi,
Yagi Shintaro,
Shiota Kunio
Publication year - 2010
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.24.1_supplement.713.4
Subject(s) - dna methylation , epigenetics , differentially methylated regions , biology , epigenetics of physical exercise , methylation , transcription factor , promoter , epigenomics , transcription (linguistics) , microbiology and biotechnology , genetics , gene , gene expression , linguistics , philosophy
Numerous data of transcription factors for Insulin gene expression has been accumulated and used to characterize the Insulin‐producing cells induced from pluripotent stem cells. DNA methylation is a pivotal mark of epigenetic regulation of genes. There are numerous tissue‐dependent differentially methylated regions (T‐DMRs). DNA methylation profiles, which are consisting of methylated and unmethylated T‐DMRs, are unique to the cell types. Here, we analyzed DNA methylation profile of insulinoma MIN6 cell line by genome‐wide DNA methylation analysis method for T‐DMR analysis (D‐REAM). D‐REAM analysis revealed that MIN6 cells have unique DNA methylation profile distinctive from that of insulin non‐expressing cells including embryonic stem cells. Several transcription factors which are involved in Insulin 2 gene expression had T‐DMRs uniquely hypomethylated in MIN6 cells. Interestingly, main part of the Insulin transcription factor network, which involves transcription factors regulating other transcription factors, are under the epigenetic regulation by DNA methylation. Thus, Insulin‐expressing cells had a distinctive DNA methylation profile from others. DNA methylation profile is powerful to characterize the cells for regenerative medicine and the T‐DMR information will provide critical information for evaluating the Insulin‐producing cells. This work was supported by NEDO and NIBIO.