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Three topological features of regulatory networks control life-essential and specialized subsystems
Gene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relation...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688434/ https://www.ncbi.nlm.nih.gov/pubmed/34930908 http://dx.doi.org/10.1038/s41598-021-03625-w |
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author | Wolf, Ivan Rodrigo Simões, Rafael Plana Valente, Guilherme Targino |
author_facet | Wolf, Ivan Rodrigo Simões, Rafael Plana Valente, Guilherme Targino |
author_sort | Wolf, Ivan Rodrigo |
collection | PubMed |
description | Gene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relationship amongst the main GRN topological features that influence the control of essential and specific subsystems. We found that the K(nn), page rank, and degree are the most relevant GRN features: the ones are conserved along the evolution and are also relevant in pluripotent cells. Interestingly, life-essential subsystems are governed mainly by TFs with intermediary K(nn) and high page rank or degree, whereas specialized subsystems are mainly regulated by TFs with low K(nn). Hence, we suggest that the high probability of TFs be toured by a random signal, and the high probability of the signal propagation to target genes ensures the life-essential subsystems’ robustness. Gene/genome duplication is the main evolutionary process to rise K(nn) as the most relevant feature. Herein, we shed light on unexplored topological GRN features to assess how they are related to subsystems and how the duplications shaped the regulatory systems along the evolution. The classification model generated can be found here: https://github.com/ivanrwolf/NoC/. |
format | Online Article Text |
id | pubmed-8688434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86884342021-12-22 Three topological features of regulatory networks control life-essential and specialized subsystems Wolf, Ivan Rodrigo Simões, Rafael Plana Valente, Guilherme Targino Sci Rep Article Gene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relationship amongst the main GRN topological features that influence the control of essential and specific subsystems. We found that the K(nn), page rank, and degree are the most relevant GRN features: the ones are conserved along the evolution and are also relevant in pluripotent cells. Interestingly, life-essential subsystems are governed mainly by TFs with intermediary K(nn) and high page rank or degree, whereas specialized subsystems are mainly regulated by TFs with low K(nn). Hence, we suggest that the high probability of TFs be toured by a random signal, and the high probability of the signal propagation to target genes ensures the life-essential subsystems’ robustness. Gene/genome duplication is the main evolutionary process to rise K(nn) as the most relevant feature. Herein, we shed light on unexplored topological GRN features to assess how they are related to subsystems and how the duplications shaped the regulatory systems along the evolution. The classification model generated can be found here: https://github.com/ivanrwolf/NoC/. Nature Publishing Group UK 2021-12-20 /pmc/articles/PMC8688434/ /pubmed/34930908 http://dx.doi.org/10.1038/s41598-021-03625-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wolf, Ivan Rodrigo Simões, Rafael Plana Valente, Guilherme Targino Three topological features of regulatory networks control life-essential and specialized subsystems |
title | Three topological features of regulatory networks control life-essential and specialized subsystems |
title_full | Three topological features of regulatory networks control life-essential and specialized subsystems |
title_fullStr | Three topological features of regulatory networks control life-essential and specialized subsystems |
title_full_unstemmed | Three topological features of regulatory networks control life-essential and specialized subsystems |
title_short | Three topological features of regulatory networks control life-essential and specialized subsystems |
title_sort | three topological features of regulatory networks control life-essential and specialized subsystems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688434/ https://www.ncbi.nlm.nih.gov/pubmed/34930908 http://dx.doi.org/10.1038/s41598-021-03625-w |
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