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Controlling Cell Fate Specification System by Key Genes Determined from Network Structure

Network structures describing regulation between biomolecules have been determined in many biological systems. Dynamics of molecular activities based on such networks are considered to be the origin of many biological functions. Recently, it has been proved mathematically that key nodes for controll...

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Detalles Bibliográficos
Autores principales: Kobayashi, Kenji, Maeda, Kazuki, Tokuoka, Miki, Mochizuki, Atsushi, Satou, Yutaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6147236/
https://www.ncbi.nlm.nih.gov/pubmed/30240747
http://dx.doi.org/10.1016/j.isci.2018.05.004
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author Kobayashi, Kenji
Maeda, Kazuki
Tokuoka, Miki
Mochizuki, Atsushi
Satou, Yutaka
author_facet Kobayashi, Kenji
Maeda, Kazuki
Tokuoka, Miki
Mochizuki, Atsushi
Satou, Yutaka
author_sort Kobayashi, Kenji
collection PubMed
description Network structures describing regulation between biomolecules have been determined in many biological systems. Dynamics of molecular activities based on such networks are considered to be the origin of many biological functions. Recently, it has been proved mathematically that key nodes for controlling dynamics in networks are identified from network structure alone. Here, we applied this theory to a gene regulatory network for the cell fate specification of seven tissues in the ascidian embryo and found that this network, which consisted of 92 factors, had five key molecules. By controlling the activities of these key molecules, the specific gene expression of six of seven tissues observed in the embryo was successfully reproduced. Since this method is applicable to all nonlinear dynamic systems, we propose this method as a tool for controlling gene regulatory networks and reprogramming cell fates.
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spelling pubmed-61472362018-10-02 Controlling Cell Fate Specification System by Key Genes Determined from Network Structure Kobayashi, Kenji Maeda, Kazuki Tokuoka, Miki Mochizuki, Atsushi Satou, Yutaka iScience Article Network structures describing regulation between biomolecules have been determined in many biological systems. Dynamics of molecular activities based on such networks are considered to be the origin of many biological functions. Recently, it has been proved mathematically that key nodes for controlling dynamics in networks are identified from network structure alone. Here, we applied this theory to a gene regulatory network for the cell fate specification of seven tissues in the ascidian embryo and found that this network, which consisted of 92 factors, had five key molecules. By controlling the activities of these key molecules, the specific gene expression of six of seven tissues observed in the embryo was successfully reproduced. Since this method is applicable to all nonlinear dynamic systems, we propose this method as a tool for controlling gene regulatory networks and reprogramming cell fates. Elsevier 2018-06-07 /pmc/articles/PMC6147236/ /pubmed/30240747 http://dx.doi.org/10.1016/j.isci.2018.05.004 Text en © 2018 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kobayashi, Kenji
Maeda, Kazuki
Tokuoka, Miki
Mochizuki, Atsushi
Satou, Yutaka
Controlling Cell Fate Specification System by Key Genes Determined from Network Structure
title Controlling Cell Fate Specification System by Key Genes Determined from Network Structure
title_full Controlling Cell Fate Specification System by Key Genes Determined from Network Structure
title_fullStr Controlling Cell Fate Specification System by Key Genes Determined from Network Structure
title_full_unstemmed Controlling Cell Fate Specification System by Key Genes Determined from Network Structure
title_short Controlling Cell Fate Specification System by Key Genes Determined from Network Structure
title_sort controlling cell fate specification system by key genes determined from network structure
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6147236/
https://www.ncbi.nlm.nih.gov/pubmed/30240747
http://dx.doi.org/10.1016/j.isci.2018.05.004
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