miRNA-target chimeras reveal miRNA 3'-end pairing as a major determinant of Argonaute target specificity

An Assessment of the Next Generation of Animal miRNA Target Prediction Algorithms

The advent of genome-wide next-generation sequencing technologies has revolutionized the genomic and transcriptomic fields. New technologies also present an opportunity for greater discovery and understanding of post-transcriptional processes, in particular, translational inhibition of transcripts by miRBP (microRNA-RNA binding protein) complexes. Not only have novel methodologies been developed for the direct sequencing of RBP-bound RNA, but a new class of miRNA (microRNA) target prediction algorithms trained on this data has emerged. In this article, we will explore and evaluate the next generation of animal miRNA target prediction algorithms, their relationship to more traditional prediction methods, and the implications of such methodologies for the future of miRNA target prediction and miRNA research as a whole.

Dissecting miRNA gene repression on single cell level with an advanced fluorescent reporter system

Despite major advances on miRNA profiling and target predictions, functional readouts for endogenous miRNAs are limited and frequently lead to contradicting conclusions. Numerous approaches including functional high-throughput and miRISC complex evaluations suggest that the functional miRNAome differs from the predictions based on quantitative sRNA profiling. To resolve the apparent contradiction of expression versus function, we generated and applied a fluorescence reporter gene assay enabling single cell analysis. This approach integrates and adapts a mathematical model for miRNA-driven gene repression. This model predicts three distinct miRNA-groups with unique repression activities (low, mid and high) governed not just by expression levels but also by miRNA/target-binding capability. Here, we demonstrate the feasibility of the system by applying controlled concentrations of synthetic siRNAs and in parallel, altering target-binding capability on corresponding reporter-constructs. Furthermore, we compared miRNA-profiles with the modeled predictions of 29 individual candidates. We demonstrate that expression levels only partially reflect the miRNA function, fitting to the model-projected groups of different activities. Furthermore, we demonstrate that subcellular localization of miRNAs impacts functionality. Our results imply that miRNA profiling alone cannot define their repression activity. The gene regulatory function is a dynamic and complex process beyond a minimalistic conception of "highly expressed equals high repression".

Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite

BACKGROUND

MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics.

METHODS AND RESULTS

We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs.

CONCLUSIONS

With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases.

Using hiCLIP to identify RNA duplexes that interact with a specific RNA-binding protein

The structure of RNA molecules has a critical role in regulating gene expression, largely through influencing their interactions with RNA-binding proteins (RBPs). RNA hybrid and individual-nucleotide resolution UV cross-linking and immunoprecipitation (hiCLIP) is a transcriptome-wide method of monitoring these interactions by identifying RNA duplexes bound by a specific RBP. The hiCLIP protocol consists of the following steps: in vivo cross-linking of RBPs to their bound RNAs; partial RNA digestion and purification of RNA duplexes interacting with the specific RBP using immunoprecipitation; ligation of the two arms of RNA duplexes via a linker; reverse transcription; cDNA library amplification; and finally high-throughput DNA sequencing. Mapping of the sequenced arms to a reference transcriptome identifies the exact locations of duplexes. hiCLIP data can directly identify all types of RNA duplexes bound by RBPs, including those that are challenging to predict computationally, such as intermolecular and long-range intramolecular duplexes. Moreover, the use of an adaptor that links the two arms of the RNA duplex permits hiCLIP to unambiguously identify the duplexes. Here we describe in detail the procedure for a hiCLIP experiment and the subsequent streamlined data analysis with an R package, 'hiclipr' (https://github.com/luslab/hiclipr/). Preparation of the library for high-throughput DNA sequencing takes ∼7 d and the basic bioinformatic pipeline takes 1 d.

Computational analysis of CLIP-seq data

CLIP-seq experiments are currently the most important means for determining the binding sites of RNA binding proteins on a genome-wide level. The computational analysis can be divided into three steps. In the first pre-processing stage, raw reads have to be trimmed and mapped to the genome. This step has to be specifically adapted for each CLIP-seq protocol. The next step is peak calling, which is required to remove unspecific signals and to determine bona fide protein binding sites on target RNAs. Here, both protocol-specific approaches as well as generic peak callers are available. Despite some peak callers being more widely used, each peak caller has its specific assets and drawbacks, and it might be advantageous to compare the results of several methods. Although peak calling is often the final step in many CLIP-seq publications, an important follow-up task is the determination of binding models from CLIP-seq data. This is central because CLIP-seq experiments are highly dependent on the transcriptional state of the cell in which the experiment was performed. Thus, relying solely on binding sites determined by CLIP-seq from different cells or conditions can lead to a high false negative rate. This shortcoming can, however, be circumvented by applying models that predict additional putative binding sites.

RNA-based recognition and targeting: sowing the seeds of specificity

RNA is involved in the regulation of multiple cellular processes, often by forming sequence-specific base pairs with cellular RNA or DNA targets that must be identified among the large number of nucleic acids in a cell. Several RNA-based regulatory systems in eukaryotes, bacteria and archaea, including microRNAs (miRNAs), small interfering RNAs (siRNAs), CRISPR RNAs (crRNAs) and small RNAs (sRNAs) that are dependent on the RNA chaperone protein Hfq, achieve specificity using similar strategies. Central to their function is the presentation of short 'seed sequences' within a ribonucleoprotein complex to facilitate the search for and recognition of targets.

RNA-mediated communication between helminths and their hosts: The missing links

Small RNAs have been discovered in a wide variety of extracellular environments and are now thought to participate in communication between cells and even between different organisms and species. Helminths are parasitic worms that generally reside in extracellular niches in their hosts and can establish chronic infection through the release of immunomodulatory factors. Recent work has demonstrated that Extracellular RNA (exRNA) may be another class of immunomodulator secreted by helminths. Here we will detail what is known about small RNA pathways in helminth pathogens (focusing on nematodes) and mammalian hosts. We will then explore the computational challenges with identifying RNA-RNA interactions between 2 different species and the paradigm of RNA-RNA co-evolution that accompanies this. Finally we explore the lingering questions that require further investigation to understand the properties of exRNA that would enable it to function as an immunomodulator.

TargetLink, a new method for identifying the endogenous target set of a specific microRNA in intact living cells

MicroRNAs are small non-coding RNAs acting as posttranscriptional repressors of gene expression. Identifying mRNA targets of a given miRNA remains an outstanding challenge in the field. We have developed a new experimental approach, TargetLink, that applied locked nucleic acid (LNA) as the affinity probe to enrich target genes of a specific microRNA in intact cells. TargetLink also consists a rigorous and systematic data analysis pipeline to identify target genes by comparing LNA-enriched sequences between experimental and control samples. Using miR-21 as a test microRNA, we identified 12 target genes of miR-21 in a human colorectal cancer cell by this approach. The majority of the identified targets interacted with miR-21 via imperfect seed pairing. Target validation confirmed that miR-21 repressed the expression of the identified targets. The cellular abundance of the identified miR-21 target transcripts varied over a wide range, with some targets expressed at a rather low level, confirming that both abundant and rare transcripts are susceptible to regulation by microRNAs, and that TargetLink is an efficient approach for identifying the target set of a specific microRNA in intact cells. C20orf111, one of the novel targets identified by TargetLink, was found to reside in the nuclear speckle and to be reliably repressed by miR-21 through the interaction at its coding sequence.

A Broad RNA Virus Survey Reveals Both miRNA Dependence and Functional Sequestration

Small non-coding RNAs have emerged as key modulators of viral infection. However, with the exception of hepatitis C virus, which requires the liver-specific microRNA (miRNA)-122, the interactions of RNA viruses with host miRNAs remain poorly characterized. Here, we used crosslinking immunoprecipitation (CLIP) of the Argonaute (AGO) proteins to characterize strengths and specificities of miRNA interactions in the context of 15 different RNA virus infections, including several clinically relevant pathogens. Notably, replication of pestiviruses, a major threat to milk and meat industries, critically depended on the interaction of cellular miR-17 and let-7 with the viral 3' UTR. Unlike canonical miRNA interactions, miR-17 and let-7 binding enhanced pestivirus translation and RNA stability. miR-17 sequestration by pestiviruses conferred reduced AGO binding and functional de-repression of cellular miR-17 targets, thereby altering the host transcriptome. These findings generalize the concept of RNA virus dependence on cellular miRNAs and connect virus-induced miRNA sequestration to host transcriptome regulation.

Evolutionary patterns of metazoan microRNAs reveal targeting principles in the let-7 and miR-10 families

MicroRNAs (miRNAs) regulate gene output by targeting degenerate elements in mRNAs and have undergone drastic expansions in higher metazoan genomes. The evolutionary advantage of maintaining copies of highly similar miRNAs is not well understood, nor is it clear what unique functions, if any, miRNA family members possess. Here, we study evolutionary patterns of metazoan miRNAs, focusing on the targeting preferences of the let-7 and miR-10 families. These studies reveal hotspots for sequence evolution with implications for targeting and secondary structure. High-throughput screening for functional targets reveals that each miRNA represses sites with distinct features and regulates a large number of genes with cooperative function in regulatory networks. Unexpectedly, given the high degree of similarity, single-nucleotide changes grant miRNA family members with distinct targeting preferences. Together, our data suggest complex functional relationships among miRNA duplications, novel expression patterns, sequence change, and the acquisition of new targets.

Definition and identification of small RNA sponges: Focus on miRNA sequestration

Targeting RNAs appears as an important opportunity to modulate biological processes. Here, we overviewed critical parameters implied in RNAs competition to bind small RNAs. These competitions influence small RNA availability and thereby gene expression and cell fate. We focused on the ability of RNAs to sequester small RNA, mainly the microRNAs (miRNAs) and proposed experimental workflows to demonstrate the existence and activity of RNA-sponge. From this basic science, we detailed tailored oligonucleotides, developed to challenge the binding of small RNA. In vitro and in vivo, these tailored oligonucleotides efficiently restore small RNA activity by preventing their sequestration on RNA-sponges.

MicroRNAs in the Host Response to Viral Infections of Veterinary Importance

The discovery of small regulatory non-coding RNAs has been an exciting advance in the field of genomics. MicroRNAs (miRNAs) are endogenous RNA molecules, approximately 22 nucleotides in length, that regulate gene expression, mostly at the posttranscriptional level. MiRNA profiling technologies have made it possible to identify and quantify novel miRNAs and to study their regulation and potential roles in disease pathogenesis. Although miRNAs have been extensively investigated in viral infections of humans, their implications in viral diseases affecting animals of veterinary importance are much less understood. The number of annotated miRNAs in different animal species is growing continuously, and novel roles in regulating host–pathogen interactions are being discovered, for instance, miRNA-mediated augmentation of viral transcription and replication. In this review, we present an overview of synthesis and function of miRNAs and an update on the current state of research on host-encoded miRNAs in the genesis of viral infectious diseases in their natural animal host as well as in selected in vivo and in vitro laboratory models.

Pairing beyond the Seed Supports MicroRNA Targeting Specificity

To identify endogenous miRNA-target sites, we isolated AGO-bound RNAs from Caenorhabditis elegans by individual-nucleotide resolution crosslinking immunoprecipitation (iCLIP), which fortuitously also produced miRNA-target chimeric reads. Through the analysis of thousands of reproducible chimeras, pairing to the miRNA seed emerged as the predominant motif associated with functional interactions. Unexpectedly, we discovered that additional pairing to 3' sequences is prevalent in the majority of target sites and leads to specific targeting by members of miRNA families. By editing an endogenous target site, we demonstrate that 3' pairing determines targeting by specific miRNA family members and that seed pairing is not always sufficient for functional target interactions. Finally, we present a simplified method, chimera PCR (ChimP), for the detection of specific miRNA-target interactions. Overall, our analysis revealed that sequences in the 5' as well as the 3' regions of a miRNA provide the information necessary for stable and specific miRNA-target interactions in vivo.

Learning to Predict miRNA-mRNA Interactions from AGO CLIP Sequencing and CLASH Data

Recent technologies like AGO CLIP sequencing and CLASH enable direct transcriptome-wide identification of AGO binding and miRNA target sites, but the most widely used miRNA target prediction algorithms do not exploit these data. Here we use discriminative learning on AGO CLIP and CLASH interactions to train a novel miRNA target prediction model. Our method combines two SVM classifiers, one to predict miRNA-mRNA duplexes and a second to learn a binding model of AGO’s local UTR sequence preferences and positional bias in 3’UTR isoforms. The duplex SVM model enables the prediction of non-canonical target sites and more accurately resolves miRNA interactions from AGO CLIP data than previous methods. The binding model is trained using a multi-task strategy to learn context-specific and common AGO sequence preferences. The duplex and common AGO binding models together outperform existing miRNA target prediction algorithms on held-out binding data. Open source code is available at https://bitbucket.org/leslielab/chimiric.

MicroRNAs (or miRNAs) are a family of small RNA molecules that guide Argonaute (AGO) to specific target sites within mRNAs and regulate numerous biological processes in normal cells and in disease. Despite years of research, the principles of miRNA targeting are incompletely understood, and computational miRNA target prediction methods still achieve only modest performance. Most previous target prediction work has been based on indirect measurements of miRNA regulation, such as mRNA expression changes upon miRNA perturbation, without mapping actual binding sites, which limits accuracy and precludes discovery of more subtle miRNA targeting rules. The recent introduction of CLIP (UV crosslinking followed by immunoprecipitation) sequencing technologies enables direct identification of interactions between miRNAs and mRNAs. However, the data generated from these assays has not been fully exploited in target prediction. Here, we present a model to predict miRNA-mRNA interactions solely based on their sequences, using new technologies to map AGO and miRNA binding interactions with machine learning techniques. Our algorithm produces more accurate predictions than state-of-the-art methods based on indirect measurements. Moreover, interpretation of the learned model reveals novel features of miRNA-mRNA interactions, including potential cooperativity with specific RNA-binding proteins.

MicroRNA Target Recognition: Insights from Transcriptome-Wide Non-Canonical Interactions

MicroRNAs (miRNAs) are small non-coding RNAs (∼22 nucleotides) regulating gene expression at the post-transcriptional level. By directing the RNA-induced silencing complex (RISC) to bind specific target mRNAs, miRNA can repress target genes and affect various biological phenotypes. Functional miRNA target recognition is known to majorly attribute specificity to consecutive pairing with seed region (position 2-8) of miRNA. Recent advances in a transcriptome-wide method of mapping miRNA binding sites (Ago HITS-CLIP) elucidated that a large portion of miRNA-target interactions in vivo are mediated not only through the canonical "seed sites" but also via non-canonical sites (∼15-80%), setting the stage to expand and determine their properties. Here we focus on recent findings from transcriptome-wide non-canonical miRNA-target interactions, specifically regarding "nucleation bulges" and "seed-like motifs". We also discuss insights from Ago HITS-CLIP data alongside structural and biochemical studies, which highlight putative mechanisms of miRNA target recognition, and the biological significance of these non-canonical sites mediating marginal repression.

A tale of two sequences: microRNA-target chimeric reads

In animals, a functional interaction between a microRNA (miRNA) and its target RNA requires only partial base pairing. The limited number of base pair interactions required for miRNA targeting provides miRNAs with broad regulatory potential and also makes target prediction challenging. Computational approaches to target prediction have focused on identifying miRNA target sites based on known sequence features that are important for canonical targeting and may miss non-canonical targets. Current state-of-the-art experimental approaches, such as CLIP-seq (cross-linking immunoprecipitation with sequencing), PAR-CLIP (photoactivatable-ribonucleoside-enhanced CLIP), and iCLIP (individual-nucleotide resolution CLIP), require inference of which miRNA is bound at each site. Recently, the development of methods to ligate miRNAs to their target RNAs during the preparation of sequencing libraries has provided a new tool for the identification of miRNA target sites. The chimeric, or hybrid, miRNA-target reads that are produced by these methods unambiguously identify the miRNA bound at a specific target site. The information provided by these chimeric reads has revealed extensive non-canonical interactions between miRNAs and their target mRNAs, and identified many novel interactions between miRNAs and noncoding RNAs.

isomiR-SEA: an RNA-Seq analysis tool for miRNAs/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation

Background

Massive parallel sequencing of transcriptomes, revealed the presence of many miRNAs and miRNAs variants named isomiRs with a potential role in several cellular processes through their interaction with a target mRNA. Many methods and tools have been recently devised to detect and quantify miRNAs from sequencing data. However, all of them are implemented on top of general purpose alignment methods, thus providing poorly accurate results and no information concerning isomiRs and conserved miRNA-mRNA interaction sites.

Results

To overcome these limitations we present a novel algorithm named isomiR-SEA, that is able to provide users with very accurate miRNAs expression levels and both isomiRs and miRNA-mRNA interaction sites precise classifications. Tags are mapped on the known miRNAs sequences thanks to a specialized alignment algorithm developed on top of biological evidence concerning miRNAs structure. Specifically, isomiR-SEA checks for miRNA seed presence in the input tags and evaluates, during all the alignment phases, the positions of the encountered mismatches, thus allowing to distinguish among the different isomiRs and conserved miRNA-mRNA interaction sites.

Conclusions

isomiR-SEA performances have been assessed on two public RNA-Seq datasets proving that the implemented algorithm is able to account for more reliable and accurate miRNAs expression levels with respect to those provided by two compared state of the art tools. Moreover, differently from the few methods currently available to perform isomiRs detection, the proposed algorithm implements the evaluation of isomiRs and conserved miRNA-mRNA interaction sites already in the first alignment phases, thus avoiding any additional filtering stages potentially responsible for the loss of useful information.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0958-0) contains supplementary material, which is available to authorized users.

Sequence-dependent but not sequence-specific piRNA adhesion traps mRNAs to the germ plasm

The conserved Piwi family of proteins and piwi-interacting RNAs (piRNAs) play a central role in genomic stability, which is inextricably tied with germ cell formation, by forming ribonucleoproteins (piRNPs) that silence transposable elements (TEs)¹. In Drosophila melanogaster and other animals, primordial germ cell (PGC) specification in the developing embryo is driven by maternal mRNAs and proteins that assemble into specialized mRNPs localized in the germ (pole) plasm at the posterior of the oocyte^2,3. Maternal piRNPs, especially those loaded on Aubergine (Aub), a Piwi protein, are transmitted to the germ plasm to initiate transposon silencing in the offspring germline^4–7. Transport of mRNAs to the oocyte by midoogenesis is an active, microtubule-dependent process⁸; mRNAs necessary for PGC formation are enriched in the germ plasm at late oogenesis via a diffusion and entrapment mechanism, whose molecular identity remains unknown^8,9. Aub is a central component of germ granule RNPs, which house mRNAs in the germ plasm^10–12 and interactions between Aub and Tudor are essential for the formation of germ granules^13–16. Here we show that Aub-loaded piRNAs use partial base pairing characteristic of Argonaute RNPs to bind mRNAs randomly, acting as an adhesive trap that captures mRNAs in the germ plasm, in a Tudor-dependent manner. Strikingly, germ plasm mRNAs in Drosophilids are generally longer and more abundant than other mRNAs, suggesting that they provide more target sites for piRNAs to promote their preferential tethering in germ granules. Thus complexes containing Tudor, Aub piRNPs and mRNAs couple piRNA inheritance with germline specification. Our findings reveal an unexpected function for Piwi ribonucleoprotein complexes in mRNA trapping that may be generally relevant to the function of animal germ granules.