Crosslinking, Ligation, And Sequencing Of Hybrids Research Articles

Defining Bacterial RNA-RNA Interactomes Using CLASH.

Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterial pathogen accounting for high mortality rates among infected patients. Transcriptomic regulation by small RNAs (sRNAs) has been shown to regulate networks promoting antibiotic resistance and virulence in S. aureus. Yet, the biological role of most sRNAs during MRSA host infection remains unknown. To fill this gap, in collaboration with the lab of Jai Tree, we performed comprehensive RNA-RNA interactome analyses in MRSA using CLASH under conditions that mimic the host environment. Here we present a detailed version of this optimized CLASH (cross-linking, ligation, and sequencing of hybrids) protocol we recently developed, which has been tailored to explore the RNA interactome in S. aureus as well as other Gram-positive bacteria. Alongside, we introduce a compilation of helpful Python functions for analyzing folding energies of putative RNA-RNA interactions and streamlining sRNA and mRNA seed discovery in CLASH data. In the accompanying computational demonstration, we aim to establish a standardized strategy to evaluate the likelihood that observed chimeras arise from true RNA-RNA interactions.

MicroRNA Target Identification: Revisiting Accessibility and Seed Anchoring.

By pairing to messenger RNAs (mRNAs for short), microRNAs (miRNAs) regulate gene expression in animals and plants. Accurately identifying which mRNAs interact with a given miRNA and the precise location of the interaction sites is crucial to reaching a more complete view of the regulatory network of an organism. Only a few experimental approaches, however, allow the identification of both within a single experiment. Computational predictions of miRNA-mRNA interactions thus remain generally the first step used, despite their drawback of a high rate of false-positive predictions. The major computational approaches available rely on a diversity of features, among which anchoring the miRNA seed and measuring mRNA accessibility are the key ones, with the first being universally used, while the use of the second remains controversial. Revisiting the importance of each is the aim of this paper, which uses Cross-Linking, Ligation, And Sequencing of Hybrids (CLASH) datasets to achieve this goal. Contrary to what might be expected, the results are more ambiguous regarding the use of the seed match as a feature, while accessibility appears to be a feature worth considering, indicating that, at least under some conditions, it may favour anchoring by miRNAs.

RNase III CLASH in MRSA uncovers sRNA regulatory networks coupling metabolism to toxin expression

Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterial pathogen responsible for significant human morbidity and mortality. Post-transcriptional regulation by small RNAs (sRNAs) has emerged as an important mechanism for controlling virulence. However, the functionality of the majority of sRNAs during infection is unknown. To address this, we performed UV cross-linking, ligation, and sequencing of hybrids (CLASH) in MRSA to identify sRNA-RNA interactions under conditions that mimic the host environment. Using a double-stranded endoribonuclease III as bait, we uncovered hundreds of novel sRNA-RNA pairs. Strikingly, our results suggest that the production of small membrane-permeabilizing toxins is under extensive sRNA-mediated regulation and that their expression is intimately connected to metabolism. Additionally, we also uncover an sRNA sponging interaction between RsaE and RsaI. Taken together, we present a comprehensive analysis of sRNA-target interactions in MRSA and provide details on how these contribute to the control of virulence in response to changes in metabolism.

CLASH Analyst: A Web Server to Identify In Vivo RNA-RNA Interactions from CLASH Data.

Non-coding RNAs, such as miRNAs and piRNAs, play critical roles in gene regulation through base-pairing interactions with their target molecules. The recent development of the crosslinking, ligation, and sequencing of hybrids (CLASH) method has allowed scientists to map transcriptome-wide RNA–RNA interactions by identifying chimeric reads consisting of fragments from regulatory RNAs and their targets. However, analyzing CLASH data requires scientists to use advanced bioinformatics, and currently available tools are limited for users with little bioinformatic experience. In addition, many published CLASH studies do not show the full scope of RNA–RNA interactions that were captured, highlighting the importance of reanalyzing published data. Here, we present CLASH Analyst, a web server that can analyze raw CLASH data within a fully customizable and easy-to-use interface. CLASH Analyst accepts raw CLASH data as input and identifies the RNA chimeras containing the regulatory and target RNAs according to the user’s interest. Detailed annotation of the captured RNA–RNA interactions is then presented for the user to visualize within the server or download for further analysis. We demonstrate that CLASH Analyst can identify miRNA- and piRNA-targeting sites reported from published CLASH data and should be applicable to analyze other RNA–RNA interactions. CLASH Analyst is freely available for academic use.

Exonuclease 1 genetic variant is associated with clinical outcomes of pemetrexed chemotherapy in lung adenocarcinoma.

Pemetrexed is an anti-folate agent which is one of the most frequently used chemotherapy agents for non-squamous non-small cell lung cancer (NSCLC) patients. However, clinical response to pemetrexed chemotherapy and survival outcome of patients varies significantly. We evaluated whether the genetic variants in miRNA target sites may affect the treatment outcome of pemetrexed chemotherapy in lung adenocarcinoma patients. One hundred SNPs in miRNA binding regions in cancer-related genes were obtained from the crosslinking, ligation, and sequencing of hybrids (CLASH) and CancerGenes database, and the associations with the response to pemetrexed chemotherapy and survival outcomes were investigated in 314 lung adenocarcinoma patients. Two polymorphisms, EXO1 rs1047840G>A and CAMKK2 rs1653586G>T, were significantly associated with worse chemotherapy response (adjusted odds ratio [aOR] = 0.41, 95% CI = 0.24-0.68, P = 0.001, under dominant model; and aOR = 0.33, 95% CI = 0.16-0.67, P = 0.002, under dominant model, respectively) and worse OS (adjusted hazard ratio [aHR] = 1.34, 95% CI = 1.01-1.77, P = 0.04, under dominant model; and aHR = 1.50, 95% CI = 1.06-2.13, P = 0.02, under dominant model, respectively) in multivariate analyses. Significantly increased luciferase activity was noted in EXO1 rs1047840 A allele compared to G allele. In conclusion, two SNPs in miRNA binding sites, especially EXO1 rs1047840G>A, were associated with the chemotherapy response and survival outcome in lung adenocarcinoma patients treated with pemetrexed.

Nuclear Pore Glycoprotein 62 Genetic Variant rs9523 is Associated with Clinical Outcomes of Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Lung Adenocarcinoma Patients.

IntroductionEpidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have represented the prototype of targeted therapy in NSCLC. Patients with EGFR-mutant lung adenocarcinoma extract an extraordinary clinical benefit from EGFR-TKIs. However, the extent and duration of these responses are heterogeneous, suggesting the existence of genetic modifiers affecting an individual’s response to TKIs. We investigated whether genetic variants in miRNA binding sites are associated with the clinical outcome of EGFR-TKIs in lung adenocarcinoma patients.MethodsOne hundred SNPs at miRNA binding sites in cancer-related genes were selected for the analysis using the crosslinking, ligation and sequencing of hybrids (CLASH) and CancerGenes database. qRT-PCR and luciferase assays were conducted to evaluate the functional relevance of the SNPs.ResultsNUP62 rs9523A>G were significantly associated with worse response to EGFR-TKIs, overall survival (OS), and progression-free survival (PFS). The other three SNPs (DVL2 rs2074216G>A, ARF1 rs11541557G>T, and UHRF1 rs2261988C>A) were significantly associated with worse OS and PFS. The rs9523A>G was significantly associated with decreased NUP62 expression in tumor tissues. In addition, a significantly decreased luciferase activity was noted in NUP62 rs9523 G allele compared to A allele.ConclusionGenetic variants in miRNA binding sites, especially NUP62 rs9523A>G, may be useful in predicting the clinical outcomes of EGFR-mutant lung adenocarcinoma patients treated with EGFR-TKIs.

TRFTars: predicting the targets of tRNA-derived fragments

BackgroundtRNA-derived fragments (tRFs) are 14–40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. Many studies have shown that tRFs are associated with Argonaute (AGO) complexes and inhibit gene expression in the same manner as miRNAs. However, there are currently no tools for accurately predicting tRF target genes.MethodsWe used tRF-mRNA pairs identified by crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP to assess features that may participate in tRF targeting, including the sequence context of each site and tRF-mRNA interactions. We applied genetic algorithm (GA) to select key features and support vector machine (SVM) to construct tRF prediction models.ResultsWe first identified features that globally influenced tRF targeting. Among these features, the most significant were the minimum free folding energy (MFE), position 8 match, number of bases paired in the tRF-mRNA duplex, and length of the tRF, which were consistent with previous findings. Our constructed model yielded an area under the receiver operating characteristic (ROC) curve (AUC) = 0.980 (0.977–0.983) in the training process and an AUC = 0.847 (0.83–0.861) in the test process. The model was applied to all the sites with perfect Watson–Crick complementarity to the seed in the 3′ untranslated region (3′-UTR) of the human genome. Seven of nine target/nontarget genes of tRFs confirmed by reporter assay were predicted. We also validated the predictions via quantitative real-time PCR (qRT-PCR). Thirteen potential target genes from the top of the predictions were significantly down-regulated at the mRNA levels by overexpression of the tRFs (tRF-3001a, tRF-3003a or tRF-3009a).ConclusionsPredictions can be obtained online, tRFTars, freely available at http://trftars.cmuzhenninglab.org:3838/tar/, which is the first tool to predict targets of tRFs in humans with a user-friendly interface.

Hfq CLASH uncovers sRNA-target interaction networks linked to nutrient availability adaptation.

By shaping gene expression profiles, small RNAs (sRNAs) enable bacteria to efficiently adapt to changes in their environment. To better understand how Escherichia coli acclimatizes to nutrient availability, we performed UV cross-linking, ligation and sequencing of hybrids (CLASH) to uncover Hfq-associated RNA-RNA interactions at specific growth stages. We demonstrate that Hfq CLASH robustly captures bona fide RNA-RNA interactions. We identified hundreds of novel sRNA base-pairing interactions, including many sRNA-sRNA interactions and involving 3'UTR-derived sRNAs. We rediscovered known and identified novel sRNA seed sequences. The sRNA-mRNA interactions identified by CLASH have strong base-pairing potential and are highly enriched for complementary sequence motifs, even those supported by only a few reads. Yet, steady state levels of most mRNA targets were not significantly affected upon over-expression of the sRNA regulator. Our results reinforce the idea that the reproducibility of the interaction, not base-pairing potential, is a stronger predictor for a regulatory outcome.

Accurate and Efficient Mapping of the Cross-Linked microRNA-mRNA Duplex Reads

SummaryMicroRNA (miRNA) trans-regulates the stability of many mRNAs and controls their expression levels. Reconstruction of the miRNA-mRNA interactome is key to the understanding of the miRNA regulatory network and related biological processes. However, existing miRNA target prediction methods are limited to canonical miRNA-mRNA interactions and have high false prediction rates. Other experimental methods are low throughput and cannot be used to probe genome-wide interactions. To address this challenge, the Cross-linking Ligation and Sequencing of Hybrids (CLASH) technology was developed for high-throughput probing of transcriptome-wide microRNA-mRNA interactions in vivo. The mapping of duplex reads, chimeras of two ultra-short RNA strands, poses computational challenges to current mapping and alignment methods. To address this issue, we developed CLAN (CrossLinked reads ANalysis toolkit). CLAN generated a comparable mapping of singular reads to other tools, and significantly outperformed in mapping simulated and real CLASH duplex reads, offering a potential application to other next-generation sequencing-based duplex-read-generating technologies.

Improving miRNA Target Prediction Using CLASH Data.

In this chapter, we present a computational method, TarPmiR, for miRNA target prediction. TarPmiR is based on emerging features of miRNA-target interactions learned from CLASH (crosslinking, ligation and sequencing of hybrids) data. First, we introduce miRNA target prediction, delineate existing methods for miRNA target prediction, and discuss their usage and limitations. Next, we describe available CLASH data, the learning of new miRNA binding features from CLASH data, and the usage of CLASH features in miRNA target prediction. Finally, we detail the computational pipeline of TarPmiR, discuss its performance compared with existing computational methods for miRNA target prediction, and present its installation and usage for miRNA target prediction. This chapter will facilitate the common understanding of CLASH data, new characteristics of miRNA-target interactions, and the use of the CLASH based miRNA target prediction tool TarPmiR.

Modified Cross-Linking, Ligation, and Sequencing of Hybrids (qCLASH) Identifies Kaposi's Sarcoma-Associated Herpesvirus MicroRNA Targets in Endothelial Cells.

Kaposi's sarcoma (KS) tumors are derived from endothelial cells and express Kaposi's sarcoma-associated herpesvirus (KSHV) microRNAs (miRNAs). Although miRNA targets have been identified in B cell lymphoma-derived cells and epithelial cells, little has been done to characterize the KSHV miRNA targetome in endothelial cells. A recent innovation in the identification of miRNA targetomes, cross-linking, ligation, and sequencing of hybrids (CLASH), unambiguously identifies miRNAs and their targets by ligating the two species while both species are still bound within the RNA-induced silencing complex (RISC). We developed a streamlined quick CLASH (qCLASH) protocol that requires a lower cell input than the original method and therefore has the potential to be used on patient biopsy samples. Additionally, we developed a fast-growing, KSHV-negative endothelial cell line derived from telomerase-immortalized vein endothelial long-term culture (TIVE-LTC) cells. qCLASH was performed on uninfected cells and cells infected with either wild-type KSHV or a mutant virus lacking miR-K12-11/11*. More than 1,400 cellular targets of KSHV miRNAs were identified. Many of the targets identified by qCLASH lacked a canonical seed sequence match. Additionally, most target regions in mRNAs originated from the coding DNA sequence (CDS) rather than the 3' untranslated region (UTR). This set of genes includes some that were previously identified in B cells and some new genes that warrant further study. Pathway analysis of endothelial cell targets showed enrichment in cell cycle control, apoptosis, and glycolysis pathways, among others. Characterization of these new targets and the functional consequences of their repression will be important in furthering our understanding of the role of KSHV miRNAs in oncogenesis.IMPORTANCE KS lesions consist of endothelial cells latently infected with KSHV. Cells that make up these lesions express KSHV miRNAs. Identification of the targets of KSHV miRNAs will help us understand their role in viral oncogenesis. The cross-linking and sequencing of hybrids (CLASH) protocol is a method for unambiguously identifying miRNA targetomes. We developed a streamlined version of CLASH, called quick CLASH (qCLASH). qCLASH requires a lower initial input of cells than for its parent protocol. Additionally, a new fast-growing KSHV-negative endothelial cell line, named TIVE-EX-LTC cells, was established. qCLASH was performed on TIVE-EX-LTC cells latently infected with wild-type (WT) KSHV or a mutant virus lacking miR-K12-11/11*. A number of novel targets of KSHV miRNAs were identified, including targets of miR-K12-11, the ortholog of the cellular oncogenic miRNA (oncomiR) miR-155. Many of the miRNA targets were involved in processes related to oncogenesis, such as glycolysis, apoptosis, and cell cycle control.

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.

Association between polymorphisms in microRNA target sites and survival in early-stage non-small cell lung cancer.

A high‐throughput mapping method of RNA–RNA interactions by crosslinking, ligation, and sequencing of hybrids (CLASH) can not only provide information about canonical but also non‐canonical interactions. We evaluated the associations between variants in microRNA target sites using CLASH data and survival outcomes of 782 early‐stage non‐small cell lung cancer (NSCLC) patients who underwent curative surgical resection. Among the 100 variants studied, two variants showed significant association with survival outcomes. The POLR2A rs2071504 C > T variant was associated with poor overall and disease‐free survival under a dominant model (hazard ratio [HR] 1.42, 95% confidence interval [CI] 1.08–1.88; P = 0.01 and HR 1.34, 95% CI 1.08–1.67; P = 0.01, respectively). Patients carrying the NR2F6 rs2288539 TT genotype showed significantly better overall survival than those with the NR2F6 rs2288539 CC or CT genotypes (HR 0.13, 95% CI 0.02–0.90; P = 0.04). These findings suggest that POLR2A rs2071504 C > T and NR2F6 rs2288539 C > T can influence prognosis in early‐stage NSCLC patients.

Abstract 1903: A genetic variation in microRNA target site of ETS2 is associated with clinical outcomes of paclitaxel-cisplatin chemotherapy in non-small cell lung cancer

Abstract Background: Recently, crosslinking, ligation, and sequencing of hybrids (CLASH) provided direct observation of transcriptome-wide miRNA-target pairs. The present study was performed to investigate the association of single nucleotide polymorphisms (SNPs) located in the miRNA target sites, which were experimentally verified by CLASH, with the clinical outcome of first line paclitaxel-cisplatin chemotherapy in advanced non-small cell lung cancer (NSCLC). Methods: Eighty SNPs in miRNA target sites of cancer related genes selected from 18,500 miRNA:target interactions in CLASH data were investigated in 379 advanced NSCLC patients using a sequenom mass spectrometry-based genotype assay. Quantitative reverse transcription-polymerase chain reaction and luciferase assay were conducted to examine functional relevance of potentially functional SNPs in miRNA target sites. Results: Of the 80 SNPs analyzed, 16 SNPs were significantly associated with the clinical outcome after chemotherapy. Among these, ANAPC1 rs3814026C>T, ETS2 rs461155A>G, SORBS1 rs7081076C>A and POLR2A rs2071504C>T were found to be significantly associated with both chemotherapy response and survival. Notably, the relative expression level of ETS2 was significantly associated with rs461155A>G genotypes in both tumor and paired normal lung tissues (Ptrend = 4 × 10-7,and3×10-4,respectively). Consistently, a decreased expression of the reporter gene for the G allele of rs461155 compared with the A allele was observed by luciferase assay. Conclusion: These findings suggest that the four SNPs, especially ETS2 rs461155A>G, could be used as biomarkers predicting the response and survival of NSCLC patients treated with first-line paclitaxel-cisplatin chemotherapy. Citation Format: SON JI WOONG, Shin Yup Lee, Chang Ho Kim, Jae Yong Park. A genetic variation in microRNA target site of ETS2 is associated with clinical outcomes of paclitaxel-cisplatin chemotherapy in non-small cell lung cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1903.

TarPmiR: a new approach for microRNA target site prediction.

Motivation: The identification of microRNA (miRNA) target sites is fundamentally important for studying gene regulation. There are dozens of computational methods available for miRNA target site prediction. Despite their existence, we still cannot reliably identify miRNA target sites, partially due to our limited understanding of the characteristics of miRNA target sites. The recently published CLASH (crosslinking ligation and sequencing of hybrids) data provide an unprecedented opportunity to study the characteristics of miRNA target sites and improve miRNA target site prediction methods.Results: Applying four different machine learning approaches to the CLASH data, we identified seven new features of miRNA target sites. Combining these new features with those commonly used by existing miRNA target prediction algorithms, we developed an approach called TarPmiR for miRNA target site prediction. Testing on two human and one mouse non-CLASH datasets, we showed that TarPmiR predicted more than 74.2% of true miRNA target sites in each dataset. Compared with three existing approaches, we demonstrated that TarPmiR is superior to these existing approaches in terms of better recall and better precision.Availability and Implementation: The TarPmiR software is freely available at http://hulab.ucf.edu/research/projects/miRNA/TarPmiR/.Contacts: haihu@cs.ucf.edu or xiaoman@mail.ucf.eduSupplementary information: Supplementary data are available at Bioinformatics online.

A genetic variation in microRNA target site of ETS2 is associated with clinical outcomes of paclitaxel-cisplatin chemotherapy in non-small cell lung cancer.

The present study was performed to investigate the association of single nucleotide polymorphisms (SNPs) located in the miRNA target sites with the clinical outcomes of first line paclitaxel-cisplatin chemotherapy in advanced NSCLC. Eighty SNPs in miRNA binding sites of cancer related genes selected from 18,500 miRNA:target bindings in crosslinking, ligation, and sequencing of hybrids (CLASH) data were investigated in 379 advanced NSCLC patients using a sequenom mass spectrometry-based genotype assay. qRT-PCR and luciferase assay were conducted to examine functional relevance of potentially functional SNPs in miRNA binding sites. Of the 80 SNPs analyzed, 16 SNPs were significantly associated with the clinical outcomes after chemotherapy. Among these, ANAPC1 rs3814026C>T, ETS2 rs461155A>G, SORBS1 rs7081076C>A and POLR2A rs2071504C>T could predict both chemotherapy response and survival. Notably, ETS2 rs461155A>G was significantly associated with decreased ETS2 mRNA expression in both tumor and paired normal lung tissues (Ptrend = 4 × 10−7, and 3 × 10−4, respectively). Consistently, a decreased expression of the reporter gene for the G allele of rs461155 compared with the A allele was observed by luciferase assay. These findings suggest that the four SNPs, especially ETS2 rs461155A>G, could be used as biomarkers predicting the clinical outcomes of NSCLC patients treated with first-line paclitaxel-cisplatin chemotherapy.

Identification of miRNA-Target RNA Interactions Using CLASH.

We present a detailed protocol for the experimental identification of miRNA-target RNA interaction sites using cross-linking, ligation, and sequencing of hybrids (CLASH). The basis of the technique is the purification of UV-stabilized Argonaute (AGO)-RNA complexes assembled in living cells, with subsequent ligation of AGO-associated RNA-RNA duplexes to form chimeric RNAs. Following cDNA synthesis, DNA library preparation and high-throughput sequencing, interacting RNA molecules are unambiguously identified as chimeric reads in bioinformatic analysis of sequencing data. CLASH potentially recovers any RNA duplex that is bound by RNA-binding protein, so modified approaches would be suitable for the identification of many other inter- and intramolecular RNA-RNA interactions. Since CLASH analysis is independent of bioinformatic predictions it allows the identification and analysis of RNA targeting rules in an unbiased way.

A pre-ribosomal RNA interaction network involving snoRNAs and the Rok1 helicase.

Ribosome biogenesis in yeast requires 75 small nucleolar RNAs (snoRNAs) and a myriad of cofactors for processing, modification, and folding of the ribosomal RNAs (rRNAs). For the 19 RNA helicases implicated in ribosome synthesis, their sites of action and molecular functions have largely remained unknown. Here, we have used UV cross-linking and analysis of cDNA (CRAC) to reveal the pre-rRNA binding sites of the RNA helicase Rok1, which is involved in early small subunit biogenesis. Several contact sites were identified in the 18S rRNA sequence, which interestingly all cluster in the "foot" region of the small ribosomal subunit. These include a major binding site in the eukaryotic expansion segment ES6, where Rok1 is required for release of the snR30 snoRNA. Rok1 directly contacts snR30 and other snoRNAs required for pre-rRNA processing. Using cross-linking, ligation and sequencing of hybrids (CLASH) we identified several novel pre-rRNA base-pairing sites for the snoRNAs snR30, snR10, U3, and U14, which cluster in the expansion segments of the 18S rRNA. Our data suggest that these snoRNAs bridge interactions between the expansion segments, thereby forming an extensive interaction network that likely promotes pre-rRNA maturation and folding in early pre-ribosomal complexes and establishes long-range rRNA interactions during ribosome synthesis.

Mapping the miRNA interactome by cross-linking ligation and sequencing of hybrids (CLASH).

RNA-RNA interactions have critical roles in many cellular processes, but studying them is difficult and laborious. Here we describe an experimental procedure, termed cross-linking ligation and sequencing of hybrids (CLASH), which allows high-throughput identification of sites of RNA-RNA interaction. During CLASH, a tagged bait protein is UV-cross-linked in cell cultures to stabilize RNA interactions, and it is purified under denaturing conditions. RNAs associated with the bait protein are partially truncated, and the ends of RNA duplexes are ligated together. After linker addition, cDNA library preparation and high-throughput sequencing, the ligated duplexes give rise to chimeric cDNAs, which unambiguously identify RNA-RNA interaction sites independent of bioinformatic predictions. This protocol is optimized for studying miRNA targets bound by Argonaute (AGO) proteins, but it should be easily adapted for other RNA-binding proteins and classes of RNA. The protocol requires ∼5 d to complete, excluding the time required for high-throughput sequencing and bioinformatic analyses.

Composition of seed sequence is a major determinant of microRNA targeting patterns

MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in gene expression regulation. One major roadblock in functional miRNA studies is the reliable prediction of genes targeted by miRNAs, as rules defining miRNA target recognition have not been well-established to date. Availability of high-throughput experimental data from a recent CLASH (cross linking, ligation and sequencing of hybrids) study has presented an unprecedented opportunity to characterize miRNA target recognition patterns, which may provide guidance for improved miRNA target prediction. The CLASH data were analysed to identify distinctive sequence features that characterize canonical and non-canonical miRNA target types. Most miRNA targets were of non-canonical type, i.e. without involving perfect pairing to canonical miRNA seed region. Different miRNAs have distinct targeting patterns, and this miRNA-to-miRNA variability was associated with seed sequence composition. Specifically, seed-based canonical target recognition was dependent on the GC content of the miRNA seed. For miRNAs with low GC content of the seed region, non-canonical targeting was the dominant mechanism for target recognition. In contrast to canonical targeting, non-canonical targeting did not lead to significant target downregulation at either the RNA or protein level. xwang@radonc.wustl.edu.