Principles of miRNA-mRNA interactions: beyond sequence complementarity

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression by altering the translation efficiency and/or stability of targeted mRNAs. In vertebrates, more than 50% of all protein-coding RNAs are assumed to be subject to miRNA-mediated control, but current high-throughput methods that reliably measure miRNA-mRNA interactions either require prior knowledge of target mRNAs or elaborate preparation procedures. Consequently, experimentally validated interactions are relatively rare. Furthermore, in silico prediction based on sequence complementarity of miRNAs and their corresponding target sites suffers from extremely high false positive rates. Apparently, sequence complementarity alone is often insufficient to reflect the complex post-transcriptional regulation of mRNAs by miRNAs, which is especially true for animals. Therefore, combined analysis of small non-coding and protein-coding RNAs is indispensable to better understand and predict the complex dynamics of miRNA-regulated gene expression. Single-nucleotide polymorphisms (SNPs) and alternative polyadenylation (APA) can affect miRNA binding of a given transcript from different individuals and tissues, and especially APA is currently emerging as a major factor that contributes to variations in miRNA-mRNA interplay in animals. In this review, we focus on the influence of APA and SNPs on miRNA-mediated gene regulation and discuss the computational approaches that take these mechanisms into account.

Fig. 1

Canonical miRNA biogenesis and generation of intron-derived miRNAs (mirtrons) in animals. a Canonical miRNAs are transcribed independently by Pol-II into pri-miRNAs. Subsequent microprocessing of pri-miRNAs is mediated by the DGCR8/DROSHA complex and produces pre-miRNAs that are exported into the cytoplasm. b Mirtrons are transcribed together with a host gene and produced by refolding of debranched intron lariats during mRNA splicing. After export into the cytoplasm, miRNA/miRNA* duplexes are generated by cleavage of the loop via Dicer. The duplexes are loaded into RISC, where only the mature miRNA strand of the duplex is retained, whereas the passenger strand is degraded. In general, partially complementary base pairing of a miRNA seed region with a target mRNA induces translational repression, while perfect base pairing results in siRNA-induced endonucleolytic cleavage

Fig. 2

Mapping pattern of miRNAs. Removal of the pre-miRNA loop by Dicer leads to two separated clusters of reads mapped to the reference genome. The figure is based on http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-112876

Fig. 3

Alternative polyadenylation (APA) results in formation of distinct mRNA isoforms that are derived from one and the same pre-mRNA. Terminal exons that contain 3′ UTRs with multiple PA sites can give rise to mRNA isoforms that differ in UTR length only (shown on top). The length of these tandem UTRs depends on recognition of promotor-proximal PA sites that are linked to shortened 3′ UTR formation or distal PA sites that result in transcription of (nearly) full-length UTRs. Additionally, APA occurs in a splicing-dependent context that comprises the incorporation of alternative terminal exons into the mature mRNA (shown at the bottom). In contrast to formation of splicing-independent tandem UTRs, 3′ exon switching affects both the sequence as well as the length of a given 3′ UTR. Shortened or mutually exclusive 3′ UTRs contain different miRNA recognition and protein binding sites that affect the stability, localization, and translation efficiency of an mRNA. Evasion of miRNA-mediated post-transcriptional regulation due to the lack of miRNA binding sites either caused by shortening of tandem UTRs or through incorporation of alternative 3′ terminal exons is typically coupled to increased translation and protein synthesis. Figure adapted from [52]

Fig. 4

Visualization of the 3′ UTR from the human IGF2BP1 transcript by APADB. Nine PA sites (I) detected by clustering of end-coordinates of polyA-tail positive NGS reads (III) are present in human HLF liver cancer cell lines. Except for one site (IGF2BP1.3) each PA site is associated with a closely upstream (~20 BPs) PA signal (II). Only the longest 3′ UTR isoform harbors all predicted TargetScan binding sites (IV), while the isoform with the shortest 3′ UTR (IGF2BP1.9) does not carry a single predicted miRNA binding site

Fig. 5

Integration of experimental expression data into target prediction. In order to predict miRNA–mRNA interactions, a matrix for each miRNA-mRNA pair is generated (top). Potential miRNA–mRNA interactions exhibit a significant negative correlation (circles). Furthermore, interactions gain support by sequence complementarity (S), as visualized at the left bottom, and by the observed expression of miRNAs and mRNAs in each biological replicate (dots in the scatterplot at the bottom)