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Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control

Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulat...

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Autores principales: Kagami, Haruna, Akutsu, Tatsuya, Maegawa, Shingo, Hosokawa, Hiroshi, Nacher, Jose C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602215/
https://www.ncbi.nlm.nih.gov/pubmed/26459019
http://dx.doi.org/10.1038/srep14577
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author Kagami, Haruna
Akutsu, Tatsuya
Maegawa, Shingo
Hosokawa, Hiroshi
Nacher, Jose C.
author_facet Kagami, Haruna
Akutsu, Tatsuya
Maegawa, Shingo
Hosokawa, Hiroshi
Nacher, Jose C.
author_sort Kagami, Haruna
collection PubMed
description Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10(−109)). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies.
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spelling pubmed-46022152015-10-23 Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control Kagami, Haruna Akutsu, Tatsuya Maegawa, Shingo Hosokawa, Hiroshi Nacher, Jose C. Sci Rep Article Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10(−109)). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies. Nature Publishing Group 2015-10-13 /pmc/articles/PMC4602215/ /pubmed/26459019 http://dx.doi.org/10.1038/srep14577 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Kagami, Haruna
Akutsu, Tatsuya
Maegawa, Shingo
Hosokawa, Hiroshi
Nacher, Jose C.
Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control
title Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control
title_full Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control
title_fullStr Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control
title_full_unstemmed Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control
title_short Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control
title_sort determining associations between human diseases and non-coding rnas with critical roles in network control
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602215/
https://www.ncbi.nlm.nih.gov/pubmed/26459019
http://dx.doi.org/10.1038/srep14577
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