Argonaute loading improves the 5' precision of both MicroRNAs and their miRNA* strands in flies

MicroRNAs (miRNAs) are short regulatory RNAs that direct repression of their mRNA targets. The miRNA "seed"-nucleotides 2-7-establishes target specificity by mediating target binding. Accurate processing of the miRNA 5' end is thought to be under strong selective pressure because a shift by just one nucleotide in the 5' end of a miRNA alters its seed sequence, redefining its repertoire of targets (Figure 1). Animal miRNAs are produced by the sequential cleavage of partially double-stranded precursors by the RNase III endonucleases Drosha and Dicer, thereby generating a transitory double-stranded intermediate comprising the miRNA paired to its partially complementary miRNA strand. Here, we report that in flies, the 5' ends of miRNAs and miRNA strands are typically more precisely defined than their 3' ends. Surprisingly, the precision of the 5' ends of both miRNA and miRNA sequences increases after Argonaute2 (Ago2) loading. Our data imply that either many miRNA sequences are under evolutionary pressure to maintain their seed sequences-that is, they have targets-or that secondary constraints, such as the sequence requirements for loading small RNAs into functional Argonaute complexes, narrow the range of miRNA and miRNA 5' ends that accumulate in flies.     

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method

Background

MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks.

Results

We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145.

Conclusions

Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-255) contains supplementary material, which is available to authorized users.     

Genomics of microRNA

Discovered just over a decade ago, microRNA (miRNA) is now recognized as one of the major regulatory gene families in eukaryotic cells. Hundreds of miRNAs have been found in animals, plants and viruses, and there are certainly more to come. Through specific base-pairing with mRNAs, these tiny approximately 22-nt RNAs induce mRNA degradation or translational repression, or both. Because a miRNA can target numerous mRNAs, often in combination with other miRNAs, miRNAs operate highly complex regulatory networks. In this article, we summarize the current status of miRNA gene mining and miRNA expression profiling. We also review up-to-date knowledge of miRNA gene structure and the biogenesis mechanism. Our focus is on animal miRNAs.