Son Mi-Young, Jung Cho-Rok, Kim Dae-Soo, Cho Hyun-Soo
Stem Cell Research Center, Korea Research Institute of Bioscience and Biotechnology, 125 Gwahak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.
Department of Functional Genomics, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea.
Mol Biol Rep. 2018 Jun;45(3):309-314. doi: 10.1007/s11033-018-4163-2. Epub 2018 Apr 6.
The technology of tissue differentiation from human pluripotent stem cells has attracted attention as a useful resource for regenerative medicine, disease modeling and drug development. Recent studies have suggested various key factors and specific culture methods to improve the successful tissue differentiation and efficient generation of human induced pluripotent stem cells. Among these methods, epigenetic regulation and epigenetic signatures are regarded as an important hurdle to overcome during reprogramming and differentiation. Thus, in this study, we developed an in silico epigenetic panel and performed a comparative analysis of epigenetic modifiers in the RNA-seq results of 32 human tissues. We demonstrated that an in silico epigenetic panel can identify epigenetic modifiers in order to overcome epigenetic barriers to tissue-specific differentiation.
从人类多能干细胞进行组织分化的技术，作为再生医学、疾病建模和药物开发的有用资源已受到关注。最近的研究提出了各种关键因素和特定培养方法，以提高人类诱导多能干细胞成功的组织分化和高效生成。在这些方法中，表观遗传调控和表观遗传特征被视为重编程和分化过程中需要克服的重要障碍。因此，在本研究中，我们开发了一种计算机表观遗传分析方法，并对32种人类组织的RNA测序结果中的表观遗传修饰因子进行了比较分析。我们证明，一种计算机表观遗传分析方法可以识别表观遗传修饰因子，以克服组织特异性分化的表观遗传障碍。
