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Whole miRNome-wide Differential Co-expression of MicroRNAs

Co-regulation of genes has been extensively analyzed, however, rather limited knowledge is available on co-regulations within the miRNome. We investigated differential co-expression of microRNAs (miRNAs) based on miRNome profiles of whole blood from 540 individuals. These include patients suffering...

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Autores principales: Stäehler, Cord F., Keller, Andreas, Leidinger, Petra, Backes, Christina, Chandran, Anoop, Wischhusen, Jöerg, Meder, Benjamin, Meese, Eckart
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054199/
https://www.ncbi.nlm.nih.gov/pubmed/23200138
http://dx.doi.org/10.1016/j.gpb.2012.08.003
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author Stäehler, Cord F.
Keller, Andreas
Leidinger, Petra
Backes, Christina
Chandran, Anoop
Wischhusen, Jöerg
Meder, Benjamin
Meese, Eckart
author_facet Stäehler, Cord F.
Keller, Andreas
Leidinger, Petra
Backes, Christina
Chandran, Anoop
Wischhusen, Jöerg
Meder, Benjamin
Meese, Eckart
author_sort Stäehler, Cord F.
collection PubMed
description Co-regulation of genes has been extensively analyzed, however, rather limited knowledge is available on co-regulations within the miRNome. We investigated differential co-expression of microRNAs (miRNAs) based on miRNome profiles of whole blood from 540 individuals. These include patients suffering from different cancer and non-cancer diseases, and unaffected controls. Using hierarchical clustering, we found 9 significant clusters of co-expressed miRNAs containing 2–36 individual miRNAs. Through analyzing multiple sequencing alignments in the clusters, we found that co-expression of miRNAs is associated with both sequence similarity and genomic co-localization. We calculated correlations for all 371,953 pairs of miRNAs for all 540 individuals and identified 184 pairs of miRNAs with high correlation values. Out of these 184 pairs of miRNAs, 16 pairs (8.7%) were differentially co-expressed in unaffected controls, cancer patients and patients with non-cancer diseases. By computing correlated and anti-correlated miRNA pairs, we constructed a network with 184 putative co-regulations as edges and 100 miRNAs as nodes. Thereby, we detected specific clusters of miRNAs with high and low correlation values. Our approach represents the most comprehensive co-regulation analysis based on whole miRNome-wide expression profiling. Our findings further decrypt the interactions of miRNAs in normal and human pathological processes.
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spelling pubmed-50541992016-10-14 Whole miRNome-wide Differential Co-expression of MicroRNAs Stäehler, Cord F. Keller, Andreas Leidinger, Petra Backes, Christina Chandran, Anoop Wischhusen, Jöerg Meder, Benjamin Meese, Eckart Genomics Proteomics Bioinformatics Original Research Co-regulation of genes has been extensively analyzed, however, rather limited knowledge is available on co-regulations within the miRNome. We investigated differential co-expression of microRNAs (miRNAs) based on miRNome profiles of whole blood from 540 individuals. These include patients suffering from different cancer and non-cancer diseases, and unaffected controls. Using hierarchical clustering, we found 9 significant clusters of co-expressed miRNAs containing 2–36 individual miRNAs. Through analyzing multiple sequencing alignments in the clusters, we found that co-expression of miRNAs is associated with both sequence similarity and genomic co-localization. We calculated correlations for all 371,953 pairs of miRNAs for all 540 individuals and identified 184 pairs of miRNAs with high correlation values. Out of these 184 pairs of miRNAs, 16 pairs (8.7%) were differentially co-expressed in unaffected controls, cancer patients and patients with non-cancer diseases. By computing correlated and anti-correlated miRNA pairs, we constructed a network with 184 putative co-regulations as edges and 100 miRNAs as nodes. Thereby, we detected specific clusters of miRNAs with high and low correlation values. Our approach represents the most comprehensive co-regulation analysis based on whole miRNome-wide expression profiling. Our findings further decrypt the interactions of miRNAs in normal and human pathological processes. Elsevier 2012-10 2012-08-23 /pmc/articles/PMC5054199/ /pubmed/23200138 http://dx.doi.org/10.1016/j.gpb.2012.08.003 Text en © 2012 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Published by Elsevier Ltd and Science Press. All rights reserved. http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/).
spellingShingle Original Research
Stäehler, Cord F.
Keller, Andreas
Leidinger, Petra
Backes, Christina
Chandran, Anoop
Wischhusen, Jöerg
Meder, Benjamin
Meese, Eckart
Whole miRNome-wide Differential Co-expression of MicroRNAs
title Whole miRNome-wide Differential Co-expression of MicroRNAs
title_full Whole miRNome-wide Differential Co-expression of MicroRNAs
title_fullStr Whole miRNome-wide Differential Co-expression of MicroRNAs
title_full_unstemmed Whole miRNome-wide Differential Co-expression of MicroRNAs
title_short Whole miRNome-wide Differential Co-expression of MicroRNAs
title_sort whole mirnome-wide differential co-expression of micrornas
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054199/
https://www.ncbi.nlm.nih.gov/pubmed/23200138
http://dx.doi.org/10.1016/j.gpb.2012.08.003
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