Abstract
BackgroundMicroRNAs (miRNAs) simultaneously target many transcripts through partial complementarity binding, and have emerged as a key type of post-transcriptional regulator for gene expression. How miRNA accomplishes its pleiotropic effects largely depends on its expression and its target repertoire. Previous studies discovered thousands of miRNAs and numerous miRNA target genes mainly through computation and prediction methods which produced high rates of false positive prediction. The development of Argonaute cross-linked immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) provides a system to effectively determine miRNA target genes. Likewise, the accuracy of dissecting the transcriptional regulation of miRNA genes has been greatly improved by chromatin immunoprecipitation of the transcription factors coupled with sequencing (ChIP-Seq). Elucidation of the miRNA target repertoire will provide an in-depth understanding of the functional roles of microRNA pathways. To reliably reconstruct a miRNA-mediated regulatory network, we established a computational framework using publicly available, sequence-based transcription factor-miRNA databases, including ChIPBase and TransmiR for the TF-miRNA interactions, along with miRNA-target databases, including miRTarBase, TarBase and starBase, for the miRNA-target interactions. We applied the computational framework to elucidate the miRNA-mediated regulatory network in the Mir122a-/- mouse model, which has an altered transcriptome and progressive liver disease.ResultsWe applied our computational framework to the expression profiles of miRNA/mRNA of Mir122a-/- mutant mice and wild-type mice. The miRNA-mediated network involves 40 curated TFs contributing to the aberrant expression of 65 miRNAs and 723 curated miRNA target genes, of which 56% was found in the differentially-expressed genes of Mir122a--mice. Hence, the regulatory network disclosed previously-known and also many previously-unidentified miRNA-mediated regulations in mutant mice. Moreover, we demonstrate that loss of imprinting at the chromosome 12qF1 region is associated with miRNA overexpression in human hepatocellular carcinoma and stem cells, suggesting initiation of precancerous changes in young mice deficient in miR-122. A group of 9 miRNAs was found to share miR-122 target genes, indicating synergy between miRNAs and target genes by way of multiplicity and cooperativity.ConclusionsThe study provides significant insight into miRNA-mediated regulatory networks. Based on experimentally verified data, this network is highly reliable and effective in revealing previously-undetermined disease-associated molecular mechanisms. This computational framework can be applied to explore the significant TF-miRNA-miRNA target interactions in any complex biological systems with high degrees of confidence.
Highlights
MicroRNAs simultaneously target many transcripts through partial complementarity binding, and have emerged as a key type of post-transcriptional regulator for gene expression
Since its first discovery in Caenorhabditis elegans [1,2,3], microRNA has been seen as a key regulator of gene expression [4]. miRNAs are RNA molecules ranging in size from 21 to 23 nucleotides that down-regulate genes by guiding Argonaute (AGO) proteins to form miRNA-induced silencing complexes leading to translational repression or mRNA degradation [5]
Considering that different platforms have different coverage for all mouse miRNAs, we focus on the differentially expressed miRNAs (DEmiRs) presented by both small RNA sequencing (RNA-Seq) and OpenArray assay
Summary
MicroRNAs (miRNAs) simultaneously target many transcripts through partial complementarity binding, and have emerged as a key type of post-transcriptional regulator for gene expression. The development of Argonaute cross-linked immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) provides a system to effectively determine miRNA target genes. The accuracy of dissecting the transcriptional regulation of miRNA genes has been greatly improved by chromatin immunoprecipitation of the transcription factors coupled with sequencing (ChIP-Seq). We applied the computational framework to elucidate the miRNA-mediated regulatory network in the Mir122a-/- mouse model, which has an altered transcriptome and progressive liver disease. Yang et al [16] integrated the high throughput ChIP-Seq datasets to provide a web-based tool called ChIPBase to help detect transcription factor binding sites (TFBSs) for non-coding RNAs including miRNAs
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