A wide repertoire of miRNA binding sites: prediction and functional implications

MOTIVATION: Over the past decade, deciphering the roles of microRNAs (miRNAs) has relied heavily upon the identification of their targets. Most of the targets that were computationally and experimentally characterized were evolutionarily conserved 'seed' targets, containing a perfect 6-8 nt match between the miRNA 5(')-region and the messenger RNA (mRNA). Gradually, it has become evident that other types of miRNA binding can confer target regulation, but their characterization has been lagging behind. RESULTS: Here, we complement the putative evolutionarily-conserved seed-containing targets by a wide repertoire of putative targets exhibiting a variety of miRNA binding patterns, predicted by our algorithm RepTar. These include non-conserved sites, 'seed' binding sites with G:U-wobbles within the seed, '3(') compensatory' sites and 'centered' sites. Apart from the centered sites, we demonstrate the functionality of these sites and characterize the target profile of a miRNA by the types of binding sites predicted in its target 3(') UTRs. We find that different miRNAs have individual target profiles, with some more inclined to seed binding and others more inclined to binding through 3(') compensatory sites. This diversity in targeting patterns is also evident within several miRNA families (defined by common seed sequences), leading to divergence in the target sets of members of the same family. The prediction of non-conventional miRNA targets is also beneficial in the search for targets of the non-conserved viral miRNAs. Analyzing the cellular targets of viral miRNAs, we show that viral miRNAs use various binding patterns to exploit cellular miRNA binding sites and suggest roles for these targets in virus-host interactions.     

Efficiency of the miRNA–mRNA Interaction Prediction Programs

miRNAs play a key role in regulation of gene expression. Nowadays it is known more than 2500 human miRNAs, while a majority of miRNA–mRNA interactions remains unidentified. The recent development of a high-throughput CLASH (crosslinking, ligation and sequencing of hybrids) technique for discerning miRNA–mRNA interactions allowed an experimental analysis of the human miRNA–mRNA interactome. Therefore, it allowed us, for the first time, make an experimental analysis of the human miRNA–mRNA interactome as a whole and an evaluation of the quality of most commonly used miRNA prediction tools (TargetScan, PicTar, PITA, RNA22 and miRanda). To estimate efficiency of the miRNA–mRNA prediction tools, we used next parameters: sensitivity, positive predicted value, predictions in different mRNA regions (3' UTR, CDS, 5' UTR), predictions for different types of interactions (5 classes), predictions of “canonical” and “nocanonical” interactions, similarity with the random generated data. The analysis revealed low efficiency of all prediction programs in comparison with the CLASH data in terms of the all examined parameters.     

Mutation altering the miR-184 seed region causes familial keratoconus with cataract

MicroRNAs (miRNAs) bind to complementary sequences within the 3' untranslated region (UTR) of mRNAs from hundreds of target genes, leading either to mRNA degradation or suppression of translation. We found that a mutation in the seed region of miR-184 (MIR184) is responsible for familial severe keratoconus combined with early-onset anterior polar cataract by deep sequencing of a linkage region known to contain the mutation. The mutant form fails to compete with miR-205 (MIR205) for overlapping target sites on the 3' UTRs of INPPL1 and ITGB4. Although these target genes and miR-205 are expressed widely, the phenotype is restricted to the cornea and lens because of the very high expression of miR-184 in these tissues. Our finding highlights the tissue specificity of a gene network regulated by a miRNA. Awareness of the important function of miRNAs could aid identification of susceptibility genes and new therapeutic targets for treatment of both rare and common diseases.     

Human microRNA-155 on chromosome 21 differentially interacts with its polymorphic target in the AGTR1 3' untranslated region: a mechanism for functional single-nucleotide polymorphisms related to phenotypes

Animal microRNAs (miRNAs) regulate gene expression through base pairing to their targets within the 3' untranslated region (UTR) of protein-coding genes. Single-nucleotide polymorphisms (SNPs) located within such target sites can affect miRNA regulation. We mapped annotated SNPs onto a collection of experimentally supported human miRNA targets. Of the 143 experimentally supported human target sites, 9 contain 12 SNPs. We further experimentally investigated one of these target sites for hsa-miR-155, within the 3' UTR of the human AGTR1 gene that contains SNP rs5186. Using reporter silencing assays, we show that hsa-miR-155 down-regulates the expression of only the 1166A, and not the 1166C, allele of rs5186. Remarkably, the 1166C allele has been associated with hypertension in many studies. Thus, the 1166C allele may be functionally associated with hypertension by abrogating regulation by hsa-miR-155, thereby elevating AGTR1 levels. Since hsa-miR-155 is on chromosome 21, we hypothesize that the observed lower blood pressure in trisomy 21 is partially caused by the overexpression of hsa-miR-155 leading to allele-specific underexpression of AGTR1. Indeed, we have shown in fibroblasts from monozygotic twins discordant for trisomy 21 that levels of AGTR1 protein are lower in trisomy 21.     

Intron size, abundance, and distribution within untranslated regions of genes

Most research concerning the evolution of introns has largely considered introns within coding sequences (CDSs), without regard for introns located within untranslated regions (UTRs) of genes. Here, we directly determined intron size, abundance, and distribution in UTRs of genes using full-length cDNA libraries and complete genome sequences for four species, Arabidopsis thaliana, Drosophila melanogaster, human, and mouse. Overall intron occupancy (introns/exon kbp) is lower in 5' UTRs than CDSs, but intron density (intron occupancy in regions containing introns) tends to be higher in 5' UTRs than in CDSs. Introns in 5' UTRs are roughly twice as large as introns in CDSs, and there is a sharp drop in intron size at the 5' UTR-CDS boundary. We propose a mechanistic explanation for the existence of selection for larger intron size in 5' UTRs, and outline several implications of this hypothesis. We found introns to be randomly distributed within 5' UTRs, so long as a minimum required exon size was assumed. Introns in 3' UTRs were much less abundant than in 5' UTRs. Though this was expected for human and mouse that have intron-dependent nonsense-mediated decay (NMD) pathways that discourage the presence of introns within the 3' UTR, it was also true for A. thaliana and D. melanogaster, which may lack intron-dependent NMD. Our findings have several implications for theories of intron evolution and genome evolution in general.     

A catalog of polymorphisms falling in microRNA-binding regions of cancer genes

Recent evidence indicates that small, nonprotein-coding RNA molecules, called microRNAs (miRNAs), control cell growth, differentiation, and apoptosis, and are also involved in tumorigenesis. miRNAs can bind to the 3' untranslated regions (3'UTRs) of messenger RNAs and interfere with their translation. We hypothesized that common polymorphisms within their genes or within their targets could have an important impact for an individual's risk to develop complex diseases. In this study, we selected the 3'UTRs of 129 genes involved in pathways commonly acknowledged as important for cancer, and we identified putative miRNA-binding sites by means of specialized algorithms (PicTar, DIANA-MicroT, miRBase, miRanda, TargetScan, and MicroInspector). Then we investigated 79 single-nucleotide polymorphisms (SNPs) within the putative binding sites for their ability to affect or impair the binding with the miRNA by assessing the DeltaDeltaG, the variation of DeltaG (Gibbs free energy), through comparing the wild-type and their corresponding variant alleles. Moreover, we reported seven identified SNPs in seven pre-miRNA hairpin regions and one SNP in the mature sequence of miR-608. Considering the validation status of the SNPs and their frequencies, we found at least 23 candidate polymorphisms of biological relevance that we propose for further investigation in case-control association studies.     

The Drosophila splicing regulator sex-lethal directly inhibits translation of male-specific-lethal 2 mRNA.

Male-specific expression of the protein male-specific-lethal 2 (MSL-2) controls dosage compensation in Drosophila. msl-2 gene expression is inhibited in females by Sex-lethal (SXL), an RNA binding protein known to regulate pre-mRNA splicing. An intron present at the 5' untranslated region (UTR) of msl-2 mRNA contains putative SXL binding sites and is retained in female flies. Here we show that SXL plays a dual role in the inhibition of msl-2 expression. Cotransfection of Drosophila Schneider cells with an SXL expression vector and a reporter containing the 5' UTR of msl-2 mRNA resulted in retention of the 5' UTR intron and efficient accumulation of the unspliced mRNA in the cytoplasm, where its translation was blocked by SXL, but not by the intron per se. Both splicing and translation inhibition by SXL were recapitulated in vitro and found to be dependent upon SXL binding to high-affinity sites within the intron, showing that SXL directly regulates these events. Our data reveal a coordinated mechanism for the regulation of msl-2 expression by the same regulatory factor: SXL enforces intron retention in the nucleus and subsequent translation inhibition in the cytoplasm.     

Computational prediction of intronic microRNA targets using host gene expression reveals novel regulatory mechanisms

Approximately half of known human miRNAs are located in the introns of protein coding genes. Some of these intronic miRNAs are only expressed when their host gene is and, as such, their steady state expression levels are highly correlated with those of the host gene's mRNA. Recently host gene expression levels have been used to predict the targets of intronic miRNAs by identifying other mRNAs that they have consistent negative correlation with. This is a potentially powerful approach because it allows a large number of expression profiling studies to be used but needs refinement because mRNAs can be targeted by multiple miRNAs and not all intronic miRNAs are co-expressed with their host genes.Here we introduce InMiR, a new computational method that uses a linear-Gaussian model to predict the targets of intronic miRNAs based on the expression profiles of their host genes across a large number of datasets. Our method recovers nearly twice as many true positives at the same fixed false positive rate as a comparable method that only considers correlations. Through an analysis of 140 Affymetrix datasets from Gene Expression Omnibus, we build a network of 19,926 interactions among 57 intronic miRNAs and 3,864 targets. InMiR can also predict which host genes have expression profiles that are good surrogates for those of their intronic miRNAs. Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3' UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns.We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs. These prediction are supported both by sequence features and expression. By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.