Toward a combinatorial nature of microRNA regulation in human cells

MicroRNAs (miRNAs) negatively regulate the levels of messenger RNA (mRNA) post-transcriptionally. Recent advances in CLIP (cross-linking immunoprecipitation) technology allowed capturing miRNAs with their cognate mRNAs. Consequently, thousands of validated mRNA-miRNA pairs have been revealed. Herein, we present a comprehensive outline for the combinatorial regulation by miRNAs. We implemented combinatorial and statistical constraints in the miRror2.0 algorithm. miRror estimates the likelihood of combinatorial miRNA activity in explaining the observed data. We tested the success of miRror in recovering the correct miRNA from 30 transcriptomic profiles of cells overexpressing a miRNA, and to identify hundreds of genes from miRNA sets, which are observed in CLIP experiments. We show that the success of miRror in recovering the miRNA regulation from overexpression experiments and CLIP data is superior in respect to a dozen leading miRNA-target prediction algorithms. We further described the balance between alternative modes of joint regulation that are executed by pairs of miRNAs. Finally, manipulated cells were tested for the possible involvement of miRNA in shaping their transcriptomes. We identified instances in which the observed transcriptome can be explained by a combinatorial regulation of miRNA pairs. We conclude that the joint operation of miRNAs is an attractive strategy to maintain cell homeostasis and overcoming the low specificity inherent in individual miRNA-mRNA interaction.