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miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells

micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information on the biologica...

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Autores principales: Hua, Youjia, Duan, Shiwei, Murmann, Andrea E., Larsen, Niels, Kjems, Jørgen, Lund, Anders H., Peter, Marcus E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3202536/
https://www.ncbi.nlm.nih.gov/pubmed/22046300
http://dx.doi.org/10.1371/journal.pone.0026521
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author Hua, Youjia
Duan, Shiwei
Murmann, Andrea E.
Larsen, Niels
Kjems, Jørgen
Lund, Anders H.
Peter, Marcus E.
author_facet Hua, Youjia
Duan, Shiwei
Murmann, Andrea E.
Larsen, Niels
Kjems, Jørgen
Lund, Anders H.
Peter, Marcus E.
author_sort Hua, Youjia
collection PubMed
description micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information on the biological state of the cell and, hence, of the function of the expressed miRNAs. We have compared the large amount of available gene array data on the steady state system of the NCI60 cell lines to two different data sets containing information on the expression of 583 individual miRNAs. In addition, we have generated custom data sets containing expression information of 54 miRNA families sharing the same seed match. We have developed a novel strategy for correlating miRNAs with individual genes based on a summed Pearson Correlation Coefficient (sPCC) that mimics an in silico titration experiment. By focusing on the genes that correlate with the expression of miRNAs without necessarily being direct targets of miRNAs, we have clustered miRNAs into different functional groups. This has resulted in the identification of three novel miRNAs that are linked to the epithelial-to-mesenchymal transition (EMT) in addition to the known EMT regulators of the miR-200 miRNA family. In addition, an analysis of gene signatures associated with EMT, c-MYC activity, and ribosomal protein gene expression allowed us to assign different activities to each of the functional clusters of miRNAs. All correlation data are available via a web interface that allows investigators to identify genes whose expression correlates with the expression of single miRNAs or entire miRNA families. miRConnect.org will aid in identifying pathways regulated by miRNAs without requiring specific knowledge of miRNA targets.
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spelling pubmed-32025362011-11-01 miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells Hua, Youjia Duan, Shiwei Murmann, Andrea E. Larsen, Niels Kjems, Jørgen Lund, Anders H. Peter, Marcus E. PLoS One Research Article micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information on the biological state of the cell and, hence, of the function of the expressed miRNAs. We have compared the large amount of available gene array data on the steady state system of the NCI60 cell lines to two different data sets containing information on the expression of 583 individual miRNAs. In addition, we have generated custom data sets containing expression information of 54 miRNA families sharing the same seed match. We have developed a novel strategy for correlating miRNAs with individual genes based on a summed Pearson Correlation Coefficient (sPCC) that mimics an in silico titration experiment. By focusing on the genes that correlate with the expression of miRNAs without necessarily being direct targets of miRNAs, we have clustered miRNAs into different functional groups. This has resulted in the identification of three novel miRNAs that are linked to the epithelial-to-mesenchymal transition (EMT) in addition to the known EMT regulators of the miR-200 miRNA family. In addition, an analysis of gene signatures associated with EMT, c-MYC activity, and ribosomal protein gene expression allowed us to assign different activities to each of the functional clusters of miRNAs. All correlation data are available via a web interface that allows investigators to identify genes whose expression correlates with the expression of single miRNAs or entire miRNA families. miRConnect.org will aid in identifying pathways regulated by miRNAs without requiring specific knowledge of miRNA targets. Public Library of Science 2011-10-26 /pmc/articles/PMC3202536/ /pubmed/22046300 http://dx.doi.org/10.1371/journal.pone.0026521 Text en Hua et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Hua, Youjia
Duan, Shiwei
Murmann, Andrea E.
Larsen, Niels
Kjems, Jørgen
Lund, Anders H.
Peter, Marcus E.
miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells
title miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells
title_full miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells
title_fullStr miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells
title_full_unstemmed miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells
title_short miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells
title_sort mirconnect: identifying effector genes of mirnas and mirna families in cancer cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3202536/
https://www.ncbi.nlm.nih.gov/pubmed/22046300
http://dx.doi.org/10.1371/journal.pone.0026521
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