Uncovering disease mechanisms through network biology in the era of next generation sequencing.

Characterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and to reveal both new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced contradi...

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Detalles Bibliográficos
Autores: Piñero González, Janet, 1977-, Berenstein, Ariel José, González-Pérez, Abel, Chernomoretz, Ariel, Furlong, Laura I., 1971-
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/26957
Acceso en línea:http://hdl.handle.net/10230/26957
http://dx.doi.org/10.1038/srep24570
Access Level:acceso abierto
Palabra clave:Biologia
Genomes -- Anàlisi
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spelling Uncovering disease mechanisms through network biology in the era of next generation sequencing.Piñero González, Janet, 1977-Berenstein, Ariel JoséGonzález-Pérez, AbelChernomoretz, ArielFurlong, Laura I., 1971-BiologiaGenomes -- AnàlisiCharacterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and to reveal both new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced contradictory results. Here we have explored the causes of these discrepancies and assessed the relationship between the network roles of disease genes and their tolerance to deleterious germline variants in human populations leveraging on: the abundance of interactome resources, a comprehensive catalog of disease genes and exome variation data. We found that the most salient network features of disease genes are driven by cancer genes and that genes related to different types of diseases play network roles whose centrality is inversely correlated to their tolerance to likely deleterious germline mutations. This proved to be a multiscale signature, including global, mesoscopic and local network centrality features. Cancer driver genes, the most sensitive to deleterious variants, occupy the most central positions, followed by dominant disease genes and then by recessive disease genes, which are tolerant to variants and isolated within their network modules.We received support from UBACyT (20020130100582BA) and MinCyT (PICT2014-2701), ISCIII-FEDER (PI13/00082, CP10/00524), IMI-JU under grants agreements n° 115002 (eTOX), n° 115191 (Open PHACTS)], n° 115372 (EMIF) and n° 115735 (iPiE), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution, and the EU H2020 Programme 2014-2020 under grant agreements no. 634143 (MedBioinformatics) and no. 676559 (Elixir-Excelerate). The Research Programme on Biomedical Informatics (GRIB) is a node of the Spanish National Institute of Bioinformatics (INB). A.G.-P. is supported by a Ramon y Cajal scholarship funded by the Spanish Ministry of Economy. The authors would like to thank the Exome Aggregation Consortium and the groups that provided exome variant data for comparison. A full list of contributing groups can be found at http://exac.broadinstitute.org/about.Nature Publishing group201620162016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/26957http://dx.doi.org/10.1038/srep24570reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésScientific Reports. 2016 Apr 15;6:24570info:eu-repo/grantAgreement/EC/FP7/115002info:eu-repo/grantAgreement/EC/FP7/115191info:eu-repo/grantAgreement/EC/FP7/115372info:eu-repo/grantAgreement/EC/FP7/115735info:eu-repo/grantAgreement/EC/H2020/634143info:eu-repo/grantAgreement/EC/H2020/676559This 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/http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/269572026-05-29T05:05:01Z
dc.title.none.fl_str_mv Uncovering disease mechanisms through network biology in the era of next generation sequencing.
title Uncovering disease mechanisms through network biology in the era of next generation sequencing.
spellingShingle Uncovering disease mechanisms through network biology in the era of next generation sequencing.
Piñero González, Janet, 1977-
Biologia
Genomes -- Anàlisi
title_short Uncovering disease mechanisms through network biology in the era of next generation sequencing.
title_full Uncovering disease mechanisms through network biology in the era of next generation sequencing.
title_fullStr Uncovering disease mechanisms through network biology in the era of next generation sequencing.
title_full_unstemmed Uncovering disease mechanisms through network biology in the era of next generation sequencing.
title_sort Uncovering disease mechanisms through network biology in the era of next generation sequencing.
dc.creator.none.fl_str_mv Piñero González, Janet, 1977-
Berenstein, Ariel José
González-Pérez, Abel
Chernomoretz, Ariel
Furlong, Laura I., 1971-
author Piñero González, Janet, 1977-
author_facet Piñero González, Janet, 1977-
Berenstein, Ariel José
González-Pérez, Abel
Chernomoretz, Ariel
Furlong, Laura I., 1971-
author_role author
author2 Berenstein, Ariel José
González-Pérez, Abel
Chernomoretz, Ariel
Furlong, Laura I., 1971-
author2_role author
author
author
author
dc.subject.none.fl_str_mv Biologia
Genomes -- Anàlisi
topic Biologia
Genomes -- Anàlisi
description Characterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and to reveal both new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced contradictory results. Here we have explored the causes of these discrepancies and assessed the relationship between the network roles of disease genes and their tolerance to deleterious germline variants in human populations leveraging on: the abundance of interactome resources, a comprehensive catalog of disease genes and exome variation data. We found that the most salient network features of disease genes are driven by cancer genes and that genes related to different types of diseases play network roles whose centrality is inversely correlated to their tolerance to likely deleterious germline mutations. This proved to be a multiscale signature, including global, mesoscopic and local network centrality features. Cancer driver genes, the most sensitive to deleterious variants, occupy the most central positions, followed by dominant disease genes and then by recessive disease genes, which are tolerant to variants and isolated within their network modules.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016
2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/26957
http://dx.doi.org/10.1038/srep24570
url http://hdl.handle.net/10230/26957
http://dx.doi.org/10.1038/srep24570
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Scientific Reports. 2016 Apr 15;6:24570
info:eu-repo/grantAgreement/EC/FP7/115002
info:eu-repo/grantAgreement/EC/FP7/115191
info:eu-repo/grantAgreement/EC/FP7/115372
info:eu-repo/grantAgreement/EC/FP7/115735
info:eu-repo/grantAgreement/EC/H2020/634143
info:eu-repo/grantAgreement/EC/H2020/676559
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Publishing group
publisher.none.fl_str_mv Nature Publishing group
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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