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microRNA‐17‐92 cluster is a direct Nanog target and controls neural stem cell through Trp53inp1

Overview of attention for article published in EMBO Journal, September 2013
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Title
microRNA‐17‐92 cluster is a direct Nanog target and controls neural stem cell through Trp53inp1
Published in
EMBO Journal, September 2013
DOI 10.1038/emboj.2013.214
Pubmed ID
Authors

Neha Garg, Agnese Po, Evelina Miele, Antonio Francesco Campese, Federica Begalli, Marianna Silvano, Paola Infante, Carlo Capalbo, Enrico De Smaele, Gianluca Canettieri, Lucia Di Marcotullio, Isabella Screpanti, Elisabetta Ferretti, Alberto Gulino

Abstract

The transcription factor Nanog plays a critical role in the self-renewal of embryonic stem cells as well as in neural stem cells (NSCs). microRNAs (miRNAs) are also involved in stemness regulation. However, the miRNA network downstream of Nanog is still poorly understood. High-throughput screening of miRNA expression profiles in response to modulated levels of Nanog in postnatal NSCs identifies miR-17-92 cluster as a direct target of Nanog. Nanog controls miR-17-92 cluster by binding to the upstream regulatory region and maintaining high levels of transcription in NSCs, whereas Nanog/promoter association and cluster miRNAs expression are lost alongside differentiation. The two miR-17 family members of miR-17-92 cluster, namely miR-17 and miR-20a, target Trp53inp1, a downstream component of p53 pathway. To support a functional role, the presence of miR-17/20a or the loss of Trp53inp1 is required for the Nanog-induced enhancement of self-renewal of NSCs. We unveil an arm of the Nanog/p53 pathway, which regulates stemness in postnatal NSCs, wherein Nanog counteracts p53 signals through miR-17/20a-mediated repression of Trp53inp1.

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Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 4%
Italy 2 3%
Japan 2 3%
Unknown 71 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 31%
Student > Ph. D. Student 18 23%
Other 6 8%
Student > Doctoral Student 5 6%
Student > Master 5 6%
Other 12 15%
Unknown 8 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 37%
Biochemistry, Genetics and Molecular Biology 19 24%
Neuroscience 7 9%
Medicine and Dentistry 6 8%
Chemistry 2 3%
Other 5 6%
Unknown 10 13%