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Identification of microRNA-regulated gene networks by expression analysis of target genes

MicroRNAs (miRNAs) and transcription factors control eukaryotic cell proliferation, differentiation, and metabolism through their specific gene regulatory networks. However, differently from transcription factors, our understanding of the processes regulated by miRNAs is currently limited. Here, we...

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Autores principales: Gennarino, Vincenzo Alessandro, D'Angelo, Giovanni, Dharmalingam, Gopuraja, Fernandez, Serena, Russolillo, Giorgio, Sanges, Remo, Mutarelli, Margherita, Belcastro, Vincenzo, Ballabio, Andrea, Verde, Pasquale, Sardiello, Marco, Banfi, Sandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3371699/
https://www.ncbi.nlm.nih.gov/pubmed/22345618
http://dx.doi.org/10.1101/gr.130435.111
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author Gennarino, Vincenzo Alessandro
D'Angelo, Giovanni
Dharmalingam, Gopuraja
Fernandez, Serena
Russolillo, Giorgio
Sanges, Remo
Mutarelli, Margherita
Belcastro, Vincenzo
Ballabio, Andrea
Verde, Pasquale
Sardiello, Marco
Banfi, Sandro
author_facet Gennarino, Vincenzo Alessandro
D'Angelo, Giovanni
Dharmalingam, Gopuraja
Fernandez, Serena
Russolillo, Giorgio
Sanges, Remo
Mutarelli, Margherita
Belcastro, Vincenzo
Ballabio, Andrea
Verde, Pasquale
Sardiello, Marco
Banfi, Sandro
author_sort Gennarino, Vincenzo Alessandro
collection PubMed
description MicroRNAs (miRNAs) and transcription factors control eukaryotic cell proliferation, differentiation, and metabolism through their specific gene regulatory networks. However, differently from transcription factors, our understanding of the processes regulated by miRNAs is currently limited. Here, we introduce gene network analysis as a new means for gaining insight into miRNA biology. A systematic analysis of all human miRNAs based on Co-expression Meta-analysis of miRNA Targets (CoMeTa) assigns high-resolution biological functions to miRNAs and provides a comprehensive, genome-scale analysis of human miRNA regulatory networks. Moreover, gene cotargeting analyses show that miRNAs synergistically regulate cohorts of genes that participate in similar processes. We experimentally validate the CoMeTa procedure through focusing on three poorly characterized miRNAs, miR-519d/190/340, which CoMeTa predicts to be associated with the TGFβ pathway. Using lung adenocarcinoma A549 cells as a model system, we show that miR-519d and miR-190 inhibit, while miR-340 enhances TGFβ signaling and its effects on cell proliferation, morphology, and scattering. Based on these findings, we formalize and propose co-expression analysis as a general paradigm for second-generation procedures to recognize bona fide targets and infer biological roles and network communities of miRNAs.
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spelling pubmed-33716992012-12-01 Identification of microRNA-regulated gene networks by expression analysis of target genes Gennarino, Vincenzo Alessandro D'Angelo, Giovanni Dharmalingam, Gopuraja Fernandez, Serena Russolillo, Giorgio Sanges, Remo Mutarelli, Margherita Belcastro, Vincenzo Ballabio, Andrea Verde, Pasquale Sardiello, Marco Banfi, Sandro Genome Res Method MicroRNAs (miRNAs) and transcription factors control eukaryotic cell proliferation, differentiation, and metabolism through their specific gene regulatory networks. However, differently from transcription factors, our understanding of the processes regulated by miRNAs is currently limited. Here, we introduce gene network analysis as a new means for gaining insight into miRNA biology. A systematic analysis of all human miRNAs based on Co-expression Meta-analysis of miRNA Targets (CoMeTa) assigns high-resolution biological functions to miRNAs and provides a comprehensive, genome-scale analysis of human miRNA regulatory networks. Moreover, gene cotargeting analyses show that miRNAs synergistically regulate cohorts of genes that participate in similar processes. We experimentally validate the CoMeTa procedure through focusing on three poorly characterized miRNAs, miR-519d/190/340, which CoMeTa predicts to be associated with the TGFβ pathway. Using lung adenocarcinoma A549 cells as a model system, we show that miR-519d and miR-190 inhibit, while miR-340 enhances TGFβ signaling and its effects on cell proliferation, morphology, and scattering. Based on these findings, we formalize and propose co-expression analysis as a general paradigm for second-generation procedures to recognize bona fide targets and infer biological roles and network communities of miRNAs. Cold Spring Harbor Laboratory Press 2012-06 /pmc/articles/PMC3371699/ /pubmed/22345618 http://dx.doi.org/10.1101/gr.130435.111 Text en © 2012, Published by Cold Spring Harbor Laboratory Press This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/.
spellingShingle Method
Gennarino, Vincenzo Alessandro
D'Angelo, Giovanni
Dharmalingam, Gopuraja
Fernandez, Serena
Russolillo, Giorgio
Sanges, Remo
Mutarelli, Margherita
Belcastro, Vincenzo
Ballabio, Andrea
Verde, Pasquale
Sardiello, Marco
Banfi, Sandro
Identification of microRNA-regulated gene networks by expression analysis of target genes
title Identification of microRNA-regulated gene networks by expression analysis of target genes
title_full Identification of microRNA-regulated gene networks by expression analysis of target genes
title_fullStr Identification of microRNA-regulated gene networks by expression analysis of target genes
title_full_unstemmed Identification of microRNA-regulated gene networks by expression analysis of target genes
title_short Identification of microRNA-regulated gene networks by expression analysis of target genes
title_sort identification of microrna-regulated gene networks by expression analysis of target genes
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3371699/
https://www.ncbi.nlm.nih.gov/pubmed/22345618
http://dx.doi.org/10.1101/gr.130435.111
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