Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.7/415
Título: Characterization of the neural stem cell gene regulatory network identifies OLIG2 as a multifunctional regulator of self-renewal
Autor: Mateo, Juan L
van den Berg, Debbie L C
Haeussler, Maximilian
Drechsel, Daniela
Gaber, Zachary B
Castro, Diogo S
Robson, Paul
Crawford, Gregory E
Flicek, Paul
Ettwiller, Laurence
Wittbrodt, Joachim
Guillemot, François
Martynoga, Ben
Palavras-chave: Stem Cells
OLIG2
Data: Jan-2015
Editora: Cold Spring Harbor Lab Press
Resumo: The gene regulatory network (GRN) that supports neural stem cell (NS cell) self-renewal has so far been poorly characterized. Knowledge of the central transcription factors (TFs), the noncoding gene regulatory regions that they bind to, and the genes whose expression they modulate will be crucial in unlocking the full therapeutic potential of these cells. Here, we use DNase-seq in combination with analysis of histone modifications to identify multiple classes of epigenetically and functionally distinct cis-regulatory elements (CREs). Through motif analysis and ChIP-seq, we identify several of the crucial TF regulators of NS cells. At the core of the network are TFs of the basic helix-loop-helix (bHLH), nuclear factor I (NFI), SOX, and FOX families, with CREs often densely bound by several of these different TFs. We use machine learning to highlight several crucial regulatory features of the network that underpin NS cell self-renewal and multipotency. We validate our predictions by functional analysis of the bHLH TF OLIG2. This TF makes an important contribution to NS cell self-renewal by concurrently activating pro-proliferation genes and preventing the untimely activation of genes promoting neuronal differentiation and stem cell quiescence.
Peer review: yes
URI: http://hdl.handle.net/10400.7/415
DOI: 10.1101/gr.173435.114
Versão do Editor: http://genome.cshlp.org/content/25/1/41.long
Aparece nas colecções:MN - Artigos

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Genome Res.-2015-Mateo-41-56.pdfartigo principal2,46 MBAdobe PDFVer/Abrir


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