Joint analysis of miRNA and mRNA expression data

Abstract

miRNAs are small RNA molecules ('22 nt) that interact with their target mRNAs inhibiting translation or/and cleavaging the target mRNA. This interaction is guided by sequence complentarity and results in the reduction of mRNA and/or protein levels. miRNAs are involved in key biological processes and different diseases. Therefore, deciphering miRNA targets is crucial for diagnostics and therapeutics. However, miRNA regulatory mechanisms are complex and there is still no high-throughput and low-cost miRNA target screening technique. In recent years, several computational methods based on sequence complementarity of the miRNA and the mRNAs have been developed. However, the predicted interactions using these computational methods are inconsistent and the expected false positive rates are still large. Recently, it has been proposed to use the expression values of miRNAs and mRNAs (and/or proteins) to refine the results of sequence-based putative targets for a particular experiment. These methods have shown to be effective identifying the most prominent interactions from the databases of putative targets. Here, we review these methods that combine both expression and sequence-based putative targets to predict miRNA targets.

Databases for lncRNAs: a comparative evaluation of emerging tools

“…These techniques are usually based on the identification of functional similarity patterns extracted from sequences (DNA or RNA motifs), of gene coexpression, and of evolutionary conservation relationships (Kel et al 2003;Muniategui et al 2013). The computational prediction of interactions can also involve machine learning models built on training data sets that contain relatively large collections of known lncRNA-RNA interactions, together with instances defined as noninteracting pairs.…”

MiR-206 Target Prediction in Breast Cancer Subtypes by Bioinformatics Tools

“…Although a number of computational methods based on sequence complementarity of the miRNA and the mRNAs have been proposed, the predicted interactions using these computational techniques are unreliable according to high false positive rates. Incorporation of the expression values of miRNAs and mRNAs (and/or proteins) has been suggested as a method to improve the results of sequence-based predictions (12). Our proposed approach provides a tool for combination of miRNA target prediction with mRNA expression data.…”

“…Homogeneity in experimental conditions should be maintained in our proposed approach. Considering the more significant role of other factors such as transcription factors in regulation of gene expression compared with miRNAs role, heterogeneity of information sources is regarded as a limitation in such approaches (12).…”

“…However, the valid prediction of miRNA targets is still problematic. Merging experimental and computational tools for decoding miRNA functions and targets has been suggested as an attractive approach in this regard (12). Consequently, in the present study, we have suggested a bioinformatics approach for the identification of miRNA-206 target genes implicated in breast cancer based on miRNA target prediction tools and microarray data analysis.…”

Small RNA biology: From fundamental studies to applications

“…Improvement of current computational algorithms will likely facilitate our understanding of more comprehensive miRNA targetome [62][63][64]. New advances in RNA-Seq technologies may enable the experimental examination of changes in target gene expression when miRNA level is deliberately altered [63,65]. Development of methods for real-time monitoring small RNA activities in vivo may provide new insights into their functions in normal physiology and disease [66][67][68].…”