RNA-protein Interaction Networks Research Articles

IdenPC-CAP: Identify protein complexes from weighted RNA-protein heterogeneous interaction networks using co-assemble partner relation.

Protein complexes play important roles in most cellular processes. The available genome-wide protein-protein interaction (PPI) data make it possible for computational methods identifying protein complexes from PPI networks. However, PPI datasets usually contain a large ratio of false positive noise. Moreover, different types of biomolecules in a living cell cooperate to form a union interaction network. Because previous computational methods focus only on PPIs ignoring other types of biomolecule interactions, their predicted protein complexes often contain many false positive proteins. In this study, we develop a novel computational method idenPC-CAP to identify protein complexes from the RNA-protein heterogeneous interaction network consisting of RNA-RNA interactions, RNA-protein interactions and PPIs. By considering interactions among proteins and RNAs, the new method reduces the ratio of false positive proteins in predicted protein complexes. The experimental results demonstrate that idenPC-CAP outperforms the other state-of-the-art methods in this field.

RNA structure-wide discovery of functional interactions with multiplexed RNA motif library

Biochemical assays and computational analyses have discovered RNA structures throughout various transcripts. However, the roles of these structures are mostly unknown. Here we develop folded RNA element profiling with structure library (FOREST), a multiplexed affinity assay system to identify functional interactions from transcriptome-wide RNA structure datasets. We generate an RNA structure library by extracting validated or predicted RNA motifs from gene-annotated RNA regions. The RNA structure library with an affinity enrichment assay allows for the comprehensive identification of target-binding RNA sequences and structures in a high-throughput manner. As a proof-of-concept, FOREST discovers multiple RNA-protein interaction networks with quantitative scores, including translational regulatory elements that function in living cells. Moreover, FOREST reveals different binding landscapes of RNA G-quadruplex (rG4) structures-binding proteins and discovers rG4 structures in the terminal loops of precursor microRNAs. Overall, FOREST serves as a versatile platform to investigate RNA structure-function relationships on a large scale.

Analysis of RNA-protein networks with RNP-MaP defines functional hubs on RNA.

RNA-protein interaction networks govern many biological processes, but are difficult to examine comprehensively. We devised ribonucleoprotein networks analyzed by mutational profiling (RNP-MaP), a live-cell chemical probing strategy that maps cooperative interactions among multiple proteins bound to single RNA molecules at nucleotide resolution. RNP-MaP uses a heterobifunctional crosslinker to freeze interacting proteins in place on RNA, and then maps multiple bound proteins in single RNA strands by read-through reverse transcription and DNA sequencing. RNP-MaP revealed that RNase P and RMRP, two sequence-divergent but structurally related non-coding RNAs, share RNP networks and that network hubs define functional sites in these RNAs. RNP-MaP also identified protein interaction networks conserved between mouse and human XIST long non-coding RNAs and defined protein communities whose binding sites colocalize and form networks in functional regions of XIST. RNP-MaP enables discovery and efficient validation of functional protein interaction networks on long RNAs in living cells.

The role of 3'UTR-protein complexes in the regulation of protein multifunctionality and subcellular localization.

Multifunctional proteins often perform their different functions when localized in different subcellular compartments. However, the mechanisms leading to their localization are largely unknown. Recently, 3′UTRs were found to regulate the cellular localization of newly synthesized proteins through the formation of 3′UTR-protein complexes. Here, we investigate the formation of 3′UTR-protein complexes involving multifunctional proteins by exploiting large-scale protein-protein and protein-RNA interaction networks. Focusing on 238 human ‘extreme multifunctional’ (EMF) proteins, we predicted 1411 3′UTR-protein complexes involving 54% of those proteins and evaluated their role in regulating protein cellular localization and multifunctionality. We find that EMF proteins lacking localization addressing signals, yet present at both the nucleus and cell surface, often form 3′UTR-protein complexes, and that the formation of these complexes could provide EMF proteins with the diversity of interaction partners necessary to their multifunctionality. Our findings are reinforced by archetypal moonlighting proteins predicted to form 3′UTR-protein complexes. Finally, the formation of 3′UTR-protein complexes that involves up to 17% of the proteins in the human protein-protein interaction network, may be a common and yet underestimated protein trafficking mechanism, particularly suited to regulate the localization of multifunctional proteins.

Networking and Dynamic Switches in Biological Condensates

Cellular liquid-liquid phase separation (LLPS) plays a key role in the dynamics and function of RNA-protein condensates like stress granules. In this issue ofCell, Yang et al., Guillén-Boixet et al., and Sanders et al. use a combination of experiment and modeling to provide an exciting mechanistic insight into the relationship between stress granules and LLPS, for example, in the context of protein disorder, switchable interactions, graph theory, and multiple interacting dense phases.

G3BP1 Is a Tunable Switch that Triggers Phase Separation to Assemble Stress Granules

The mechanisms underlying ribonucleoprotein (RNP) granule assembly, including the basis for establishing and maintaining RNP granules with distinct composition, are unknown. One prominent type of RNP granule is the stress granule (SG), a dynamic and reversible cytoplasmic assembly formed in eukaryotic cells in response to stress. Here, we show that SGs assemble through liquid-liquid phase separation (LLPS) arising from interactions distributed unevenly across a core protein-RNA interaction network. The central node of this network is G3BP1, which functions as a molecular switch that triggers RNA-dependent LLPS in response to a rise in intracellular free RNA concentrations. Moreover, we show that interplay between three distinct intrinsically disordered regions (IDRs) in G3BP1 regulates its intrinsic propensity for LLPS, and this is fine-tuned by phosphorylation within the IDRs. Further regulation of SG assembly arises through positive or negative cooperativity by extrinsic G3BP1-binding factors that strengthen or weaken, respectively, the core SG network.

Competing Protein-RNA Interaction Networks Control Multiphase Intracellular Organization

Liquid-liquid phase separation (LLPS) mediates formation of membraneless condensates such as those associated with RNA processing, but the rules that dictate their assembly, substructure, and coexistence with other liquid-like compartments remain elusive. Here, we address the biophysical mechanism of this multiphase organization using quantitative reconstitution of cytoplasmic stress granules (SGs) with attached P-bodies in human cells. Protein-interaction networks can be viewed as interconnected complexes (nodes) of RNA-binding domains (RBDs), whose integrated RNA-binding capacity determines whether LLPS occurs upon RNA influx. Surprisingly, both RBD-RNA specificity and disordered segments of key proteins are non-essential, but modulate multiphase condensation. Instead, stoichiometry-dependent competition between protein networks for connecting nodes determines SG and P-body composition and miscibility, while competitive binding of unconnected proteins disengages networks and prevents LLPS. Inspired by patchy colloid theory, we propose a general framework by which competing networks give rise to compositionally specific and tunable condensates, while relative linkage between nodes underlies multiphase organization.

Human protein-RNA interaction network is highly stable across mammals

BackgroundRNA-binding proteins (RBPs) are crucial in modulating RNA metabolism in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Although previous studies on the conservation of RBP targets have been carried out in lower eukaryotes such as yeast, relatively little is known about the extent of conservation of the binding sites of RBPs across mammalian species.ResultsIn this study, we employ CLIP-seq datasets for 60 human RBPs and demonstrate that most binding sites for a third of these RBPs are conserved in at least 50% of the studied vertebrate species. Across the studied RBPs, binding sites were found to exhibit a median conservation of 58%, ~ 20% higher than random genomic locations, suggesting a significantly higher preservation of RBP-RNA interaction networks across vertebrates. RBP binding sites were highly conserved across primates with weak conservation profiles in birds and fishes. We also note that phylogenetic relationship between members of an RBP family does not explain the extent of conservation of their binding sites across species. Multivariate analysis to uncover features contributing to differences in the extents of conservation of binding sites across RBPs revealed RBP expression level and number of post-transcriptional targets to be the most prominent factors. Examination of the location of binding sites at the gene level confirmed that binding sites occurring on the 3′ region of a gene are highly conserved across species with 90% of the RBPs exhibiting a significantly higher conservation of binding sites in 3′ regions of a gene than those occurring in the 5′. Gene set enrichment analysis on the extent of conservation of binding sites to identify significantly associated human phenotypes revealed an enrichment for multiple developmental abnormalities.ConclusionsOur results suggest that binding sites of human RBPs are highly conserved across primates with weak conservation profiles in lower vertebrates and evolutionary relationship between members of an RBP family does not explain the extent of conservation of their binding sites. Expression level and number of targets of an RBP are important factors contributing to the differences in the extent of conservation of binding sites. RBP binding sites on 3′ ends of a gene are the most conserved across species. Phenotypic analysis on the extent of conservation of binding sites revealed the importance of lineage-specific developmental events in post-transcriptional regulatory network evolution.

SliceIt: A genome-wide resource and visualization tool to design CRISPR/Cas9 screens for editing protein-RNA interaction sites in the human genome.

Several protein-RNA cross linking protocols have been established in recent years to delineate the molecular interaction of an RNA Binding Protein (RBP) and its target RNAs. However, functional dissection of the role of the RBP binding sites in modulating the post-transcriptional fate of the target RNA remains challenging. CRISPR/Cas9 genome editing system is being commonly employed to perturb both coding and noncoding regions in the genome. With the advancements in genome-scale CRISPR/Cas9 screens, it is now possible to not only perturb specific binding sites but also probe the global impact of protein-RNA interaction sites across cell types. Here, we present SliceIt (http://sliceit.soic.iupui.edu/), a database of in silico sgRNA (single guide RNA) library to facilitate conducting such high throughput screens. SliceIt comprises of ~4.8 million unique sgRNAs with an estimated range of 2-8 sgRNAs designed per RBP binding site, for eCLIP experiments of >100 RBPs in HepG2 and K562 cell lines from the ENCODE project. SliceIt provides a user friendly environment, developed using advanced search engine framework, Elasticsearch. It is available in both table and genome browser views facilitating the easy navigation of RBP binding sites, designed sgRNAs, exon expression levels across 53 human tissues along with prevalence of SNPs and GWAS hits on binding sites. Exon expression profiles enable examination of locus specific changes proximal to the binding sites. Users can also upload custom tracks of various file formats directly onto genome browser, to navigate additional genomic features in the genome and compare with other types of omics profiles. All the binding site-centric information is dynamically accessible via "search by gene", "search by coordinates" and "search by RBP" options and readily available to download. Validation of the sgRNA library in SliceIt was performed by selecting RBP binding sites in Lipt1 gene and designing sgRNAs. Effect of CRISPR/Cas9 perturbations on the selected binding sites in HepG2 cell line, was confirmed based on altered proximal exon expression levels using qPCR, further supporting the utility of the resource to design experiments for perturbing protein-RNA interaction networks. Thus, SliceIt provides a one-stop repertoire of guide RNA library to perturb RBP binding sites, along with several layers of functional information to design both low and high throughput CRISPR/Cas9 screens, for studying the phenotypes and diseases associated with RBP binding sites.

Long Non-Coding RNA Expression Levels Modulate Cell-Type-Specific Splicing Patterns by Altering Their Interaction Landscape with RNA-Binding Proteins.

Recent developments in our understanding of the interactions between long non-coding RNAs (lncRNAs) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein–RNA interaction networks. Analysis of alternative splicing events across 39 lncRNA knockdown and wildtype RNA-sequencing datasets from three human cell lines—HeLa (cervical cancer), K562 (myeloid leukemia), and U87 (glioblastoma)—resulted in the high-confidence (false discovery rate (fdr) < 0.01) identification of 11,630 skipped exon events and 5895 retained intron events, implicating 759 genes to be impacted at the post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockdown were specific to the cell type. In tandem, the functions annotated to the genes affected by alternative splicing across each lncRNA knockdown also displayed cell-type specificity. To understand the mechanism behind this cell-type-specific alternative splicing pattern, we analyzed RNA-binding protein (RBP)–RNA interaction profiles across the spliced regions in order to observe cell-type-specific alternative splice event RBP binding preference. Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron–exon junctions in a cell-type-specific manner. The cellular functions affected by alternative splicing were also affected in a cell-type-specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs and their downstream functions. We propose that such lncRNA sponges can extensively rewire post-transcriptional gene regulatory networks by altering the protein–RNA interaction landscape in a cell-type-specific manner.

Nonsense-mediated mRNA decay: The challenge of telling right from wrong in a complex transcriptome.

The nonsense-mediated mRNA decay pathway selects and degrades its targets using a dense network of RNA-protein and protein-protein interactions. Together, these interactions allow the pathway to collect copious information about the translating mRNA, including translation termination status, splice junction positions, mRNP composition, and 3'UTR length and structure. The core NMD machinery, centered on the RNA helicase UPF1, integrates this information to determine the efficiency of decay. A picture of NMD is emerging in which many factors contribute to the dynamics of decay complex assembly and disassembly, thereby influencing the probability of decay. The ability of the NMD pathway to recognize mRNP features of diverse potential substrates allows it to simultaneously perform quality control and regulatory functions. In vertebrates, increased transcriptome complexity requires balance between these two functions since high NMD efficiency is desirable for maintenance of quality control fidelity but may impair expression of normal mRNAs. NMD has adapted to this challenge by employing mechanisms to enhance identification of certain potential substrates, while using sequence-specific RNA-binding proteins to shield others from detection. These elaborations on the conserved NMD mechanism permit more sensitive post-transcriptional gene regulation but can have severe deleterious consequences, including the failure to degrade pathogenic aberrant mRNAs in many B cell lymphomas. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms.

GoldCLIP: Gel-omitted Ligation-dependent CLIP

Protein–RNA interaction networks are essential to understand gene regulation control. Identifying binding sites of RNA-binding proteins (RBPs) by the UV-crosslinking and immunoprecipitation (CLIP) represents one of the most powerful methods to map protein–RNA interactions in vivo. However, the traditional CLIP protocol is technically challenging, which requires radioactive labeling and suffers from material loss during PAGE-membrane transfer procedures. Here we introduce a super-efficient CLIP method (GoldCLIP) that omits all gel purification steps. This nonisotopic method allows us to perform highly reproducible CLIP experiments with polypyrimidine tract-binding protein (PTB), a classical RBP in human cell lines. In principle, our method guarantees sequencing library constructions, providing the protein of interest can be successfully crosslinked to RNAs in living cells. GoldCLIP is readily applicable to diverse proteins to uncover their endogenous RNA targets.

RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence.

RNA-protein interactions (RPIs) have critical roles in numerous fundamental biological processes, such as post-transcriptional gene regulation, viral assembly, cellular defence and protein synthesis. As the number of available RNA-protein binding experimental data has increased rapidly due to high-throughput sequencing methods, it is now possible to measure and understand RNA-protein interactions by computational methods. In this study, we integrate a sequence-based derived kernel with regularized least squares to perform prediction. The derived kernel exploits the contextual information around an amino acid or a nucleic acid as well as the repetitive conserved motif information. We propose a novel machine learning method, called RPiRLS to predict the interaction between any RNA and protein of known sequences. For the RPiRLS classifier, each protein sequence comprises up to 20 diverse amino acids but for the RPiRLS-7G classifier, each protein sequence is represented by using 7-letter reduced alphabets based on their physiochemical properties. We evaluated both methods on a number of benchmark data sets and compared their performances with two newly developed and state-of-the-art methods, RPI-Pred and IPMiner. On the non-redundant benchmark test sets extracted from the PRIDB, the RPiRLS method outperformed RPI-Pred and IPMiner in terms of accuracy, specificity and sensitivity. Further, RPiRLS achieved an accuracy of 92% on the prediction of lncRNA-protein interactions. The proposed method can also be extended to construct RNA-protein interaction networks. The RPiRLS web server is freely available at http://bmc.med.stu.edu.cn/RPiRLS.

The yeast noncoding RNA interaction network.

This article describes the creation of the first expert manually curated noncoding RNA interaction networks for S. cerevisiae. The RNA–RNA and RNA–protein interaction networks have been carefully extracted from the experimental literature and made available through the IntAct database (www.ebi.ac.uk/intact). We provide an initial network analysis and compare their properties to the much larger protein–protein interaction network. We find that the proteins that bind to ncRNAs in the network contain only a small proportion of classical RNA binding domains. We also see an enrichment of WD40 domains suggesting their direct involvement in ncRNA interactions. We discuss the challenges in collecting noncoding RNA interaction data and the opportunities for worldwide collaboration to fill the unmet need for this data.

Computational Prediction of RNA-Protein Interactions.

Experimental methods for identifying protein(s) bound by a specific promoter-associated RNA (paRNA) of interest can be expensive, difficult, and time-consuming. This chapter describes a general computational framework for identifying potential binding partners in RNA-protein complexes or RNA-protein interaction networks. Protocols for using three web-based tools to predict RNA-protein interaction partners are outlined. Also, tables listing additional webservers and software tools for predicting RNA-protein interactions, as well as databases that contain valuable information about known RNA-protein complexes and recognition sites for RNA-binding proteins, are provided. Although only one of the tools described, lncPro, was designed expressly to identify proteins that bind long noncoding RNAs (including paRNAs), all three approaches can be applied to predict potential binding partners for both coding and noncoding RNAs (ncRNAs).

Grad-seq guides the discovery of ProQ as a major small RNA-binding protein

The functional annotation of transcriptomes and identification of noncoding RNA (ncRNA) classes has been greatly facilitated by the advent of next-generation RNA sequencing which, by reading the nucleotide order of transcripts, theoretically allows the rapid profiling of all transcripts in a cell. However, primary sequence per se is a poor predictor of function, as ncRNAs dramatically vary in length and structure and often lack identifiable motifs. Therefore, to visualize an informative RNA landscape of organisms with potentially new RNA biology that are emerging from microbiome and environmental studies requires the use of more functionally relevant criteria. One such criterion is the association of RNAs with functionally important cognate RNA-binding proteins. Here we analyze the full ensemble of cellular RNAs using gradient profiling by sequencing (Grad-seq) in the bacterial pathogen Salmonella enterica, partitioning its coding and noncoding transcripts based on their network of RNA-protein interactions. In addition to capturing established RNA classes based on their biochemical profiles, the Grad-seq approach enabled the discovery of an overlooked large collective of structured small RNAs that form stable complexes with the conserved protein ProQ. We show that ProQ is an abundant RNA-binding protein with a wide range of ligands and a global influence on Salmonella gene expression. Given its generic ability to chart a functional RNA landscape irrespective of transcript length and sequence diversity, Grad-seq promises to define functional RNA classes and major RNA-binding proteins in both model species and genetically intractable organisms.

Both cis and trans Activities of Foot-and-Mouth Disease Virus 3D Polymerase Are Essential for Viral RNA Replication.

ABSTRACTThe Picornaviridae is a large family of positive-sense RNA viruses that contains numerous human and animal pathogens, including foot-and-mouth disease virus (FMDV). The picornavirus replication complex comprises a coordinated network of protein-protein and protein-RNA interactions involving multiple viral and host-cellular factors. Many of the proteins within the complex possess multiple roles in viral RNA replication, some of which can be provided in trans (i.e., via expression from a separate RNA molecule), while others are required in cis (i.e., expressed from the template RNA molecule). In vitro studies have suggested that multiple copies of the RNA-dependent RNA polymerase (RdRp) 3D are involved in the viral replication complex. However, it is not clear whether all these molecules are catalytically active or what other function(s) they provide. In this study, we aimed to distinguish between catalytically active 3D molecules and those that build a replication complex. We report a novel nonenzymatic cis-acting function of 3D that is essential for viral-genome replication. Using an FMDV replicon in complementation experiments, our data demonstrate that this cis-acting role of 3D is distinct from the catalytic activity, which is predominantly trans acting. Immunofluorescence studies suggest that both cis- and trans-acting 3D molecules localize to the same cellular compartment. However, our genetic and structural data suggest that 3D interacts in cis with RNA stem-loops that are essential for viral RNA replication. This study identifies a previously undescribed aspect of picornavirus replication complex structure-function and an important methodology for probing such interactions further.IMPORTANCE Foot-and-mouth disease virus (FMDV) is an important animal pathogen responsible for foot-and-mouth disease. The disease is endemic in many parts of the world with outbreaks within livestock resulting in major economic losses. Propagation of the viral genome occurs within replication complexes, and understanding this process can facilitate the development of novel therapeutic strategies. Many of the nonstructural proteins involved in replication possess multiple functions in the viral life cycle, some of which can be supplied to the replication complex from a separate genome (i.e., in trans) while others must originate from the template (i.e., in cis). Here, we present an analysis of cis and trans activities of the RNA-dependent RNA polymerase 3D. We demonstrate a novel cis-acting role of 3D in replication. Our data suggest that this role is distinct from its enzymatic functions and requires interaction with the viral genome. Our data further the understanding of genome replication of this important pathogen.

IrCLIP platform for efficient characterization of protein-RNA interactions.

The complexity of transcriptome-wide protein-RNA interaction networks is incompletely understood. While emerging studies are greatly expanding the known universe of RNA-binding proteins, methods for the discovery and characterization of protein-RNA interactions remain resource intensive and technically challenging. Here we introduce a UV-C crosslinking and immunoprecipitation platform, irCLIP, which provides an ultraefficient, fast, and nonisotopic method for the detection of protein-RNA interactions using far less material than standard protocols.

Abstract PR06: The enhancer landscape involves a core noncoding RNA protein interaction network for C-MYC expression

Abstract Many long non-coding RNAs (lncRNAs) that regulate the capacity of cells to undergo oncogenic transformation still remain unknown. However, their involvement in chromatin organization has been an emerging principle in cancer epigenomics. This recent concept has been documented through recent studies of the gene -poor chromosomal region 8q24 surrounding the C-MYC locus to understand the mechanisms enforcing or suppressing tumor cell growth from C-MYC transcription levels. In light of such examples informing us of the DNA elements and the epigenomic composition that become integrated into molecular programs that regulate C-MYC, some lncRNAs in non-genic regions are considered landmarks that enforce chromatin state changes to accommodate C-MYC expression. Here, we use an integrative genomic and proteomic approach to gain insight of how an endogenously tagged lncRNA PCAT-1 utilizes the chromatin and biochemical context to shape C-MYC locus topology to promote tumor cell growth, survival and fitness. Our results now find that WDR74 forms an integrative hub involving recognition of the m7G cap of lncRNA transcripts along with, RNMT, RAM, BRD4, β catenin, EZH2 that assist in a program that enforce C-MYC transcription and stabilize transcripts through utilizing a comprehensive mixture of cis-acting DNA elements, lncRNAs and trans functioning transcriptional and RNA capping complexes for prostate tumor cell growth. Our results now place the lncRNA PCAT-1 and the novel interacting WD40 repeat protein WDR74 at the axis along with β catenin, BRD4 and EZH2, and additional RBPs as a non -canonical chromatin complex to shape the chromosomal topology that benefit prostate cancer cell growth. Citation Format: Fan Zhang, Won-min Song, SiDe Li, Vashisht Ajay, Francesca Aguilo, Anindya Bagchi, James A. Wohlschlegel, Bin Zhang, Martin Walsh. The enhancer landscape involves a core noncoding RNA protein interaction network for C-MYC expression. [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer: Mechanisms to Medicines ; 2015 Dec 4-7; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2016;76(6 Suppl):Abstract nr PR06.

Ribo-Proteomics Approach to Profile RNA-Protein and Protein-Protein Interaction Networks.

Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses.