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Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks
Biological networks often show a scale-free topology with node degree following a power-law distribution. Lethal genes tend to form functional hubs, whereas non-lethal disease genes are located at the periphery. Uni-dimensional analyses, however, are flawed. We created and investigated two distinct...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814386/ https://www.ncbi.nlm.nih.gov/pubmed/23935122 http://dx.doi.org/10.1093/nar/gkt683 |
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author | Han, Hyun Wook Ohn, Jung Hun Moon, Jisook Kim, Ju Han |
author_facet | Han, Hyun Wook Ohn, Jung Hun Moon, Jisook Kim, Ju Han |
author_sort | Han, Hyun Wook |
collection | PubMed |
description | Biological networks often show a scale-free topology with node degree following a power-law distribution. Lethal genes tend to form functional hubs, whereas non-lethal disease genes are located at the periphery. Uni-dimensional analyses, however, are flawed. We created and investigated two distinct scale-free networks; a protein–protein interaction (PPI) and a perturbation sensitivity network (PSN). The hubs of both networks exhibit a low molecular evolutionary rate (P < 8 × 10(−12), P < 2 × 10(−4)) and a high codon adaptation index (P < 2 × 10(−16), P < 2 × 10(−8)), indicating that both hubs have been shaped under high evolutionary selective pressure. Moreover, the topologies of PPI and PSN are inversely proportional: hubs of PPI tend to be located at the periphery of PSN and vice versa. PPI hubs are highly enriched with lethal genes but not with disease genes, whereas PSN hubs are highly enriched with disease genes and drug targets but not with lethal genes. PPI hub genes are enriched with essential cellular processes, but PSN hub genes are enriched with environmental interaction processes, having more TATA boxes and transcription factor binding sites. It is concluded that biological systems may balance internal growth signaling and external stress signaling by unifying the two opposite scale-free networks that are seemingly opposite to each other but work in concert between death and disease. |
format | Online Article Text |
id | pubmed-3814386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-38143862013-12-27 Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks Han, Hyun Wook Ohn, Jung Hun Moon, Jisook Kim, Ju Han Nucleic Acids Res Computational Biology Biological networks often show a scale-free topology with node degree following a power-law distribution. Lethal genes tend to form functional hubs, whereas non-lethal disease genes are located at the periphery. Uni-dimensional analyses, however, are flawed. We created and investigated two distinct scale-free networks; a protein–protein interaction (PPI) and a perturbation sensitivity network (PSN). The hubs of both networks exhibit a low molecular evolutionary rate (P < 8 × 10(−12), P < 2 × 10(−4)) and a high codon adaptation index (P < 2 × 10(−16), P < 2 × 10(−8)), indicating that both hubs have been shaped under high evolutionary selective pressure. Moreover, the topologies of PPI and PSN are inversely proportional: hubs of PPI tend to be located at the periphery of PSN and vice versa. PPI hubs are highly enriched with lethal genes but not with disease genes, whereas PSN hubs are highly enriched with disease genes and drug targets but not with lethal genes. PPI hub genes are enriched with essential cellular processes, but PSN hub genes are enriched with environmental interaction processes, having more TATA boxes and transcription factor binding sites. It is concluded that biological systems may balance internal growth signaling and external stress signaling by unifying the two opposite scale-free networks that are seemingly opposite to each other but work in concert between death and disease. Oxford University Press 2013-11 2013-08-09 /pmc/articles/PMC3814386/ /pubmed/23935122 http://dx.doi.org/10.1093/nar/gkt683 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Han, Hyun Wook Ohn, Jung Hun Moon, Jisook Kim, Ju Han Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks |
title | Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks |
title_full | Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks |
title_fullStr | Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks |
title_full_unstemmed | Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks |
title_short | Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks |
title_sort | yin and yang of disease genes and death genes between reciprocally scale-free biological networks |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814386/ https://www.ncbi.nlm.nih.gov/pubmed/23935122 http://dx.doi.org/10.1093/nar/gkt683 |
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