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Genome-wide gene expression analyses reveal unique cellular characteristics related to the amenability of HPC/HSCs into high-quality induced pluripotent stem cells

Overview of attention for article published in Stem Cell Research & Therapy, March 2016
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Title
Genome-wide gene expression analyses reveal unique cellular characteristics related to the amenability of HPC/HSCs into high-quality induced pluripotent stem cells
Published in
Stem Cell Research & Therapy, March 2016
DOI 10.1186/s13287-016-0298-z
Pubmed ID
Authors

Shuai Gao, Li Tao, Xinfeng Hou, Zijian Xu, Wenqiang Liu, Kun Zhao, Mingyue Guo, Hong Wang, Tao Cai, Jianhui Tian, Shaorong Gao, Gang Chang

Abstract

Transcription factor-mediated reprogramming can efficiently convert differentiated cells into induced pluripotent stem cells (iPSCs). Furthermore, many cell types have been shown to be amenable to reprogramming into iPSCs, such as neural stem cells, hematopoietic progenitor and stem cells (HPC/HSCs). However, the mechanisms related to the amenability of these cell types to be reprogrammed are still unknown. Herein, we attempt to elucidate the mechanisms of HPC/HSC reprogramming using the sequential reprogramming system that we have previously established. We found that HPC/HSCs were amenable to transcription factor-mediated reprogramming, which yielded a high frequency of fully reprogrammed HPC/HSC-iPSCs. Genome-wide gene expression analyses revealed select down-regulated tumor suppressor and mesenchymal genes as well as up-regulated oncogenes in HPC/HSCs compared with mouse embryonic fibroblasts (MEFs), indicating that these genes may play important roles during the reprogramming of HPC/HSCs. Additional studies provided insights into the contribution of select tumor suppressor genes (p21, Ink4a and Arf) and an epithelial-to-mesenchymal transition (EMT) factor (Snail1) to the reprogramming process of HPC/HSCs. Our findings demonstrate that HPC/HSCs carry unique cellular characteristics, which determine the amenability of HPC/HSCs to be reprogrammed into high-quality iPSCs.

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The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 20%
Student > Bachelor 2 20%
Student > Master 2 20%
Student > Ph. D. Student 1 10%
Researcher 1 10%
Other 1 10%
Unknown 1 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 40%
Agricultural and Biological Sciences 2 20%
Immunology and Microbiology 1 10%
Psychology 1 10%
Engineering 1 10%
Other 0 0%
Unknown 1 10%