Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression...

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Autores: Saha, Ashis, Kim, Yungil, Gewirtz, Ariel D.H., Jo, Brian, Gao, Chuan, McDowell, Ian C., GTEx Consortium, Reverter Comes, Ferran, Engelhardt, Barbara E., Battle, Alexis
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
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:10230/69052
Acceso en línea:http://hdl.handle.net/10230/69052
http://dx.doi.org/10.1101/gr.216721.116
Access Level:acceso abierto
Palabra clave:Traducció genètica
Codi genètic
Transcripció genètica
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spelling Co-expression networks reveal the tissue-specific regulation of transcription and splicingSaha, AshisKim, YungilGewirtz, Ariel D.H.Jo, BrianGao, ChuanMcDowell, Ian C.GTEx ConsortiumReverter Comes, FerranEngelhardt, Barbara E.Battle, AlexisTraducció genèticaCodi genèticTranscripció genèticaGene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.Cold Spring Harbor Laboratory Press (CSHL Press)202520252017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/69052http://dx.doi.org/10.1101/gr.216721.116reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésGenome Research. 2017 Nov;27(11):1843-58This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at https://creativecommons.org/licenses/by/4.0/.http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/openAccessoai:recercat.cat:10230/690522026-05-29T05:05:01Z
dc.title.none.fl_str_mv Co-expression networks reveal the tissue-specific regulation of transcription and splicing
title Co-expression networks reveal the tissue-specific regulation of transcription and splicing
spellingShingle Co-expression networks reveal the tissue-specific regulation of transcription and splicing
Saha, Ashis
Traducció genètica
Codi genètic
Transcripció genètica
title_short Co-expression networks reveal the tissue-specific regulation of transcription and splicing
title_full Co-expression networks reveal the tissue-specific regulation of transcription and splicing
title_fullStr Co-expression networks reveal the tissue-specific regulation of transcription and splicing
title_full_unstemmed Co-expression networks reveal the tissue-specific regulation of transcription and splicing
title_sort Co-expression networks reveal the tissue-specific regulation of transcription and splicing
dc.creator.none.fl_str_mv Saha, Ashis
Kim, Yungil
Gewirtz, Ariel D.H.
Jo, Brian
Gao, Chuan
McDowell, Ian C.
GTEx Consortium
Reverter Comes, Ferran
Engelhardt, Barbara E.
Battle, Alexis
author Saha, Ashis
author_facet Saha, Ashis
Kim, Yungil
Gewirtz, Ariel D.H.
Jo, Brian
Gao, Chuan
McDowell, Ian C.
GTEx Consortium
Reverter Comes, Ferran
Engelhardt, Barbara E.
Battle, Alexis
author_role author
author2 Kim, Yungil
Gewirtz, Ariel D.H.
Jo, Brian
Gao, Chuan
McDowell, Ian C.
GTEx Consortium
Reverter Comes, Ferran
Engelhardt, Barbara E.
Battle, Alexis
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Traducció genètica
Codi genètic
Transcripció genètica
topic Traducció genètica
Codi genètic
Transcripció genètica
description Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.
publishDate 2017
dc.date.none.fl_str_mv 2017
2025
2025
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/10230/69052
http://dx.doi.org/10.1101/gr.216721.116
url http://hdl.handle.net/10230/69052
http://dx.doi.org/10.1101/gr.216721.116
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Genome Research. 2017 Nov;27(11):1843-58
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 Cold Spring Harbor Laboratory Press (CSHL Press)
publisher.none.fl_str_mv Cold Spring Harbor Laboratory Press (CSHL Press)
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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