Whole miRNome-wide Differential Co-expression of MicroRNAs  

作　　者：Cord F.Stehler Andreas Keller Petra Leidinger Christina Backes Anoop Chandran Jerg Wischhusen Benjamin Meder Eckart Meese 

机构地区：[1]Siemens Healthcare,Strategy [2]Department of Human Genetics,Saarland University [3]Interdisciplinary Center for Clinical Research, University of Wuerzburg [4]Department of Internal Medicine III,Heidelberg University

出　　处：《Genomics, Proteomics & Bioinformatics》2012年第5期285-294,共10页基因组蛋白质组与生物信息学报（英文版）

基　　金：Financial support was granted by HOMFOR,Deutsche Forschungsgemeinschaft (DFG,LE 2783/1-1),and Hed-wig-Stalter Foundation

摘　　要：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 hierarchi- cal 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 net- work 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.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 hierarchi- cal 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 net- work 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.

关 键 词：CO-EXPRESSION MICROARRAY MicroRNA Network analysis 

分 类 号：R341[医药卫生—基础医学]