Abstract
BackgroundMicroRNAs (miRNAs) are small non-coding RNAs affecting the expression of target genes via translational repression or mRNA degradation mechanisms. With the increasing availability of mRNA and miRNA expression data, it might be possible to assess functional targets using the fact that a miRNA might down-regulate its target mRNAs. In this work we computed the correlation of expression profiles between miRNAs and target mRNAs using the NCI-60 expression data. The aim is to investigate whether the correlations between miRNA and mRNA expression profiles, either positive or negative, can be used to assist the identification of functional miRNA-mRNA relationships.ResultsPredicted miRNA-mRNA interactions were taken from TargetScan 4.1 and miRBase release 5. Pearson correlation coefficients between the miRNA and the mRNA expression profiles were computed using NCI-60 data. The correlation coefficients were then subject to the Benjamini and Hochberg correction. Our results show that the percentage of TargetScan-predicted miRNA-mRNA interactions having negative correlation in expression profiles is higher than that of miRBase-predicted pairs. Using the experimentally validated miRNA targets listed in TarBase, genes involved in mRNA degradation show more negative correlations between miRNA and mRNA expression profiles, comparing with genes involved in translational repression. Furthermore, correlation analysis for miRNAs and mRNAs transcribed from the same genes shows that correlations of expression profiles between intronic miRNAs and host genes tend to be positive. Finally we found that a target gene might be down-regulated by more than one miRNAs sharing the same seed region.ConclusionOur results suggest that expression profiles can be used in the computational identification of functional miRNA-target associations. One can expect a higher chance of finding negatively correlated expression profiles for TargetScan-predicted interactions than for miRBase-predicted ones. With limited experimentally validated miRNA-target interactions, expression profiles can only serve as a supplementary role in finding interactions between miRNAs and mRNAs.
Highlights
MicroRNAs are small non-coding RNAs affecting the expression of target genes via translational repression or mRNA degradation mechanisms
With the correlation analyses using the NCI-60 data, our results show that negative correlations in expression profiles are more likely to be found for TargetScanpredicted miRNA-mRNA interactions than for miRBasepredicted ones
Computing correlations between miRNA and mRNA expression profiles gives us an opportunity to study the effects of gene expression between miRNAs and their target genes
Summary
MicroRNAs (miRNAs) are small non-coding RNAs affecting the expression of target genes via translational repression or mRNA degradation mechanisms. MiRNAs are small non-coding RNA molecules regulating gene expression through various mechanisms [1,2,3]. Many biological processes, such as development, cell differentiation, and even diseases, have been associated with the activity of miRNAs [4,5]. Given that miRNAs function through binding to the 3' untranslated regions (UTRs) of mRNAs, computational algorithms, such as miRanda, TargetScanS and PicTar, have been developed to search potential miRNA target sites throughout a genome using perfect or imperfect base paring at potential interaction sites [6,7,8]. Microarray analyses provide evidence that the expression of miRNAs decreases the abundance of many transcripts carrying potential miRNA target sites [12]
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