Uncovering disease mechanisms through network biology in the era of Next Generation Sequencing

Autores
Piñero Gonzalez, Janet; Berenstein, Ariel José; González Pérez, Abel; Chernomoretz, Ariel; Furlong, Laura Ines
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Piñero Gonzalez, Janet. Universitat Pompeu Fabra; España
Fil: Berenstein, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: González Pérez, Abel. Universitat Pompeu Fabra; España
Fil: Chernomoretz, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Furlong, Laura Ines. Universitat Pompeu Fabra; España
Materia
Next Generation Sequencing
Diseases Genetics
Genome Informatics
Network Topology
Classification And Taxonomy
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/47877
Acceder
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spelling Uncovering disease mechanisms through network biology in the era of Next Generation SequencingPiñero Gonzalez, JanetBerenstein, Ariel JoséGonzález Pérez, AbelChernomoretz, ArielFurlong, Laura InesNext Generation SequencingDiseases GeneticsGenome InformaticsNetwork TopologyClassification And Taxonomyhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Characterizing 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.Fil: Piñero Gonzalez, Janet. Universitat Pompeu Fabra; EspañaFil: Berenstein, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: González Pérez, Abel. Universitat Pompeu Fabra; EspañaFil: Chernomoretz, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Furlong, Laura Ines. Universitat Pompeu Fabra; EspañaNature Publishing Group2016-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/47877Piñero Gonzalez, Janet; Berenstein, Ariel José; González Pérez, Abel; Chernomoretz, Ariel; Furlong, Laura Ines; Uncovering disease mechanisms through network biology in the era of Next Generation Sequencing; Nature Publishing Group; Scientific Reports; 6; 4-2016; 1-122045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.nature.com/articles/srep24570info:eu-repo/semantics/altIdentifier/doi/10.1038/srep24570info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:10:33Zoai:ri.conicet.gov.ar:11336/47877instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:10:33.364CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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 Gonzalez, Janet
Next Generation Sequencing
Diseases Genetics
Genome Informatics
Network Topology
Classification And Taxonomy
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 Gonzalez, Janet
Berenstein, Ariel José
González Pérez, Abel
Chernomoretz, Ariel
Furlong, Laura Ines
author Piñero Gonzalez, Janet
author_facet Piñero Gonzalez, Janet
Berenstein, Ariel José
González Pérez, Abel
Chernomoretz, Ariel
Furlong, Laura Ines
author_role author
author2 Berenstein, Ariel José
González Pérez, Abel
Chernomoretz, Ariel
Furlong, Laura Ines
author2_role author
author
author
author
dc.subject.none.fl_str_mv Next Generation Sequencing
Diseases Genetics
Genome Informatics
Network Topology
Classification And Taxonomy
topic Next Generation Sequencing
Diseases Genetics
Genome Informatics
Network Topology
Classification And Taxonomy
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Piñero Gonzalez, Janet. Universitat Pompeu Fabra; España
Fil: Berenstein, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: González Pérez, Abel. Universitat Pompeu Fabra; España
Fil: Chernomoretz, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Furlong, Laura Ines. Universitat Pompeu Fabra; España
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 2016-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/47877
Piñero Gonzalez, Janet; Berenstein, Ariel José; González Pérez, Abel; Chernomoretz, Ariel; Furlong, Laura Ines; Uncovering disease mechanisms through network biology in the era of Next Generation Sequencing; Nature Publishing Group; Scientific Reports; 6; 4-2016; 1-12
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/47877
identifier_str_mv Piñero Gonzalez, Janet; Berenstein, Ariel José; González Pérez, Abel; Chernomoretz, Ariel; Furlong, Laura Ines; Uncovering disease mechanisms through network biology in the era of Next Generation Sequencing; Nature Publishing Group; Scientific Reports; 6; 4-2016; 1-12
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.nature.com/articles/srep24570
info:eu-repo/semantics/altIdentifier/doi/10.1038/srep24570
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
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:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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