Project description:To identify METTL3 binding sites on RNAs, we performed HITS-CLIP of endogenous SRSF1 Overall design: H1299 cells were subjected to the HITS-CLIP procedure (Licatalosi D, et al. 2008, Nature 456:464-U22)
Project description:To identify SRSF1 binding sites on RNAs, we performed HITS-CLIP of endogenous SRSF1 in MDA-LM2 cells Overall design: MDA-LM2 cells were subjected to the HITS-CLIP procedure (Licatalosi D, et al. 2008, Nature 456:464-U22)
Project description:MicroRNAs (miRNAs) have critical roles in the regulation of gene expression; however, as miRNA activity requires base pairing with only 6-8 nucleotides of messenger RNA, predicting target mRNAs is a major challenge. Recently, high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) has identified functional protein-RNA interaction sites. Here we use HITS-CLIP to covalently crosslink native argonaute (Ago, also called Eif2c) protein-RNA complexes in mouse brain. This produced two simultaneous data sets-Ago-miRNA and Ago-mRNA binding sites-that were combined with bioinformatic analysis to identify interaction sites between miRNA and target mRNA. We validated genome-wide interaction maps for miR-124, and generated additional maps for the 20 most abundant miRNAs present in P13 mouse brain. Ago HITS-CLIP provides a general platform for exploring the specificity and range of miRNA action in vivo, and identifies precise sequences for targeting clinically relevant miRNA-mRNA interactions.
Project description:Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.
Project description:High-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) allows for high resolution, genome-wide mapping of RNA-binding proteins. This methodology is frequently used to validate predicted targets of microRNA binding, as well as direct targets of other RNA-binding proteins. Hence, the accuracy and sensitivity of binding site identification is critical.We found that substantial mispriming during reverse transcription results in the overrepresentation of sequences complementary to the primer used for reverse transcription. Up to 45 % of peaks in publicly available HITS-CLIP libraries are attributable to this mispriming artifact, and the majority of libraries have detectable levels of mispriming. We also found that standard techniques for validating microRNA-target interactions fail to differentiate between artifactual peaks and physiologically relevant peaks.Here, we present a modification to the HITS-CLIP protocol that effectively eliminates this artifact and improves the sensitivity and complexity of resulting libraries.
Project description:High-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP, also called CLIP-Seq) has been used to map global RNA-protein interactions. However, a critical caveat of HITS-CLIP results is that they contain non-linear background noise-different extent of non-specific interactions caused by individual transcript abundance-that has been inconsiderately normalized, resulting in sacrifice of sensitivity. To properly deconvolute RNA-protein interactions, we have implemented CLIPick, a flexible peak calling pipeline for analyzing HITS-CLIP data, which statistically determines the signal-to-noise ratio for each transcript based on the expression-dependent background simulation. Comprising of streamlined Python modules with an easy-to-use standalone graphical user interface, CLIPick robustly identifies significant peaks and quantitatively defines footprint regions within which RNA-protein interactions were occurred. CLIPick outperforms other peak callers in accuracy and sensitivity, selecting the largest number of peaks particularly in lowly expressed transcripts where such marginal signals are hard to discriminate. Specifically, the application of CLIPick to Argonaute (Ago) HITS-CLIP data were sensitive enough to uncover extended features of microRNA target sites, and these sites were experimentally validated. CLIPick enables to resolve critical interactions in a wide spectrum of transcript levels and extends the scope of HITS-CLIP analysis. CLIPick is available at: http://clip.korea.ac.kr/clipick/.
Project description:Mammalian RNA complexity is regulated through interactions of RNA-binding proteins (RBPs) with their target transcripts. High-throughput sequencing together with UV-crosslinking and immunoprecipitation (HITS-CLIP) is able to globally map RBP-binding footprint regions at a resolution of ~30-60 nucleotides. Here we describe a systematic way to analyze HITS-CLIP data to identify exact crosslink sites, and thereby determine protein-RNA interactions at single-nucleotide resolution. We found that reverse transcriptase used in CLIP frequently skips the crosslinked amino-acid-RNA adduct, resulting in a nucleotide deletion. Genome-wide analysis of these crosslinking-induced mutation sites (CIMS) in HITS-CLIP data for Nova and Argonaute (Ago) proteins in mouse brain tissue revealed deletions in ~8-20% of mRNA tags, which mapped to Nova and Ago binding sites on mRNA or miRNA. CIMS analysis provides a general and more precise means of mapping protein-RNA interactions than currently available methods and insight into the biochemical properties of such interactions in living tissues.