首页 | 本学科首页   官方微博 | 高级检索  
     


Integrative genomic and functional analyses reveal neuronal subtype differentiation bias in human embryonic stem cell lines
Authors:Wu Hao  Xu Jun  Pang Zhiping P  Ge Weihong  Kim Kevin J  Blanchi Bruno  Chen Caifu  Südhof Thomas C  Sun Yi E
Affiliation:Mental Retardation Research Center, David Geffen School of Medicine at University of California, Los Angeles, Neuroscience Research Building Room 351, 635 Charles E. Young Drive South, Los Angeles, CA 90095, USA.
Abstract:The self-renewal and differentiation potential of human embryonic stem cells (hESCs) suggests that hESCs could be used for regenerative medicine, especially for restoring neuronal functions in brain diseases. However, the functional properties of neurons derived from hESC are largely unknown. Moreover, because hESCs were derived under diverse conditions, the possibility arises that neurons derived from different hESC lines exhibit distinct properties, but this possibility remains unexplored. To address these issues, we developed a protocol that allows stepwise generation from hESCs of cultures composed of approximately 70-80% human neurons that exhibit spontaneous synaptic network activity. Comparison of neurons derived from the well characterized HSF1 and HSF6 hESC lines revealed that HSF1- but not HSF6-derived neurons exhibit forebrain properties. Accordingly, HSF1-derived neurons initially form primarily GABAergic synaptic networks, whereas HSF6-derived neurons initially form glutamatergic networks. microRNA profiling revealed significant expression differences between the two hESC lines, suggesting that microRNAs may influence their distinct differentiation properties. These observations indicate that although both HSF1 and HSF6 hESCs differentiate into functional neurons, the two hESC lines exhibit distinct differentiation potentials, suggesting that they are preprogrammed. Information on hESC line-specific differentiation biases is crucial for neural stem cell therapy and establishment of novel disease models using hESCs.
Keywords:
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号