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. 2011 Mar 6:12:138.
doi: 10.1186/1471-2164-12-138.

Identification of microRNA-mRNA modules using microarray data

Vivek Jayaswal  1 , Mark Lutherborrow, David D F Ma, Yee H Yang
Affiliations

Identification of microRNA-mRNA modules using microarray data

Vivek Jayaswal et al. BMC Genomics. .

Abstract

Background: MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs.

Results: We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest.

Conclusions: Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.

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Figures

Figure 1
Figure 1
An integrative method for the identification of miRmR modules. (a) Schematic of the module-identification method with key input parameters and output. (b) Schematic of the multivariate random forest based guided clustering. For a given dissimilarity matrix, the grouping of miRNAs/mRNAs depends on the number of clusters specified by the user.
Figure 2
Figure 2
Comparison of unguided and guided clustering. The proportion of enriched clusters obtained for (a) leukemia data set and (b) timecourse data set.
Figure 3
Figure 3
Enriched miRmR modules for the timecourse data set. For mRNA clusters, the number of mRNAs is mentioned in brackets. The notation <φ: κ> implies that miRNA φ targets κ% of the mRNAs in the cluster.
See this image and copyright information in PMC

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