scispace - formally typeset
Open accessJournal ArticleDOI: 10.1038/S43586-021-00018-1

CLIP and complementary methods

04 Mar 2021-Vol. 1, Iss: 1, pp 1-23
Abstract: RNA molecules start assembling into ribonucleoprotein (RNP) complexes during transcription. Dynamic RNP assembly, largely directed by cis-acting elements on the RNA, coordinates all processes in which the RNA is involved. To identify the sites bound by a specific RNA-binding protein on endogenous RNAs, cross-linking and immunoprecipitation (CLIP) and complementary, proximity-based methods have been developed. In this Primer, we discuss the main variants of these protein-centric methods and the strategies for their optimization and quality assessment, as well as RNA-centric methods that identify the protein partners of a specific RNA. We summarize the main challenges of computational CLIP data analysis, how to handle various sources of background and how to identify functionally relevant binding regions. We outline the various applications of CLIP and available databases for data sharing. We discuss the prospect of integrating data obtained by CLIP with complementary methods to gain a comprehensive view of RNP assembly and remodelling, unravel the spatial and temporal dynamics of RNPs in specific cell types and subcellular compartments and understand how defects in RNPs can lead to disease. Finally, we present open questions in the field and give directions for further development and applications. Ule and colleagues discuss cross-linking and immunoprecipitation (CLIP) methods for characterizing the RNA binding partners of RNA-binding proteins and explore the data analysis workflows, best practices and applications for these techniques. The Primer also considers methods for characterizing the protein binding partners of specific RNAs and discusses how data from these complementary methods can be integrated into CLIP workflows.

... read more


19 results found

Open accessJournal ArticleDOI: 10.1038/S41598-021-97915-Y
16 Sep 2021-Scientific Reports
Abstract: X-ray computed micro-tomography typically involves a trade-off between sample size and resolution, complicating the study at a micrometer scale of representative volumes of materials with broad feature size distributions (e.g. natural stones). X-ray dark-field tomography exploits scattering to probe sub-resolution features, promising to overcome this trade-off. In this work, we present a quantification method for sub-resolution feature sizes using dark-field tomograms obtained by tuning the autocorrelation length of a Talbot grating interferometer. Alumina particles with different nominal pore sizes (50 nm and 150 nm) were mixed and imaged at the TOMCAT beamline of the SLS synchrotron (PSI) at eighteen correlation lengths, covering the pore size range. The different particles cannot be distinguished by traditional absorption µCT due to their very similar density and the pores being unresolved at typical image resolutions. Nevertheless, by exploiting the scattering behavior of the samples, the proposed analysis method allowed to quantify the nominal pore sizes of individual particles. The robustness of this quantification was proven by reproducing the experiment with solid samples of alumina, and alumina particles that were kept separated. Our findings demonstrate the possibility to calibrate dark-field image analysis to quantify sub-resolution feature sizes, allowing multi-scale analyses of heterogeneous materials without subsampling.

... read more

3 Citations

Open accessPosted Content
Abstract: Protein-RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions. Due to the limitation of the previous database, especially the lack of protein structure data, most of the existing computational methods rely heavily on the sequence data, with only a small portion of the methods utilizing the structural information. Recently, AlphaFold has revolutionized the entire protein and biology field. Foreseeably, the protein-RNA interaction prediction will also be promoted significantly in the upcoming years. In this work, we give a thorough review of this field, surveying both the binding site and binding preference prediction problems and covering the commonly used datasets, features, and models. We also point out the potential challenges and opportunities in this field. This survey summarizes the development of the RBP-RNA interaction field in the past and foresees its future development in the post-AlphaFold era.

... read more

3 Citations

Open accessJournal ArticleDOI: 10.3390/IJMS22105312
Akio Masuda1, Toshihiko Kawachi1, Kinji Ohno1Institutions (1)
Abstract: During mRNA transcription, diverse RNA-binding proteins (RBPs) are recruited to RNA polymerase II (RNAP II) transcription machinery. These RBPs bind to distinct sites of nascent RNA to co-transcriptionally operate mRNA processing. Recent studies have revealed a close relationship between transcription and co-transcriptional RNA processing, where one affects the other's activity, indicating an essential role of protein-RNA interactions for the fine-tuning of mRNA production. Owing to their limited amount in cells, the detection of protein-RNA interactions specifically assembled on the transcribing RNAP II machinery still remains challenging. Currently, cross-linking and immunoprecipitation (CLIP) has become a standard method to detect in vivo protein-RNA interactions, although it requires a large amount of input materials. Several improved methods, such as infrared-CLIP (irCLIP), enhanced CLIP (eCLIP), and target RNA immunoprecipitation (tRIP), have shown remarkable enhancements in the detection efficiency. Furthermore, the utilization of an RNA editing mechanism or proximity labeling strategy has achieved the detection of faint protein-RNA interactions in cells without depending on crosslinking. This review aims to explore various methods being developed to detect endogenous protein-RNA interaction sites and discusses how they may be applied to the analysis of co-transcriptional RNA processing.

... read more

Topics: RNA-binding protein (65%), RNA editing (65%), RNA polymerase II (64%) ... show more

3 Citations

Open accessJournal ArticleDOI: 10.1002/WRNA.1681
Abstract: The N6-methyladenosine (m6A) RNA methyltransferase METTL16 is an emerging player in the RNA modification landscape of the human cell. Originally thought to be a ribosomal RNA methyltransferase, it has now been shown to bind and methylate the MAT2A messenger RNA (mRNA) and U6 small nuclear RNA (snRNA). It has also been shown to bind the MALAT1 long noncoding RNA and several other RNAs. METTL16's methyltransferase domain contains the Rossmann-like fold of class I methyltransferases and uses S-adenosylmethionine (SAM) as the methyl donor. It has an RNA methylation consensus sequence of UACAGARAA (modified A underlined), and structural requirements for its known RNA interactors. In addition to the methyltransferase domain, METTL16 protein has two other RNA binding domains, one of which resides in a vertebrate conserved region, and a putative nuclear localization signal. The role of METTL16 in the cell is still being explored, however evidence suggests it is essential for most cells. This is currently hypothesized to be due to its role in regulating the splicing of MAT2A mRNA in response to cellular SAM levels. However, one of the more pressing questions remaining is what role METTL16's methylation of U6 snRNA plays in splicing and potentially cellular survival. METTL16 also has several other putative coding and noncoding RNA interactors but the definitive methylation status of those RNAs and the role METTL16 plays in their life cycle is yet to be determined. Overall, METTL16 is an intriguing RNA binding protein and methyltransferase whose important functions in the cell are just beginning to be understood. This article is categorized under: RNA Processing > RNA Editing and Modification RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

... read more

Topics: RNA (73%), Non-coding RNA (72%), RNA editing (72%) ... show more

3 Citations

Open accessPosted ContentDOI: 10.5281/ZENODO.4963330
16 Jun 2021-bioRxiv
Abstract: Author(s): Reynaud, Kendra Keilani | Advisor(s): Ingolia, Nicholas T | Abstract: At all stages of a messenger RNA’s lifecycle, it is covered in RNA-binding proteins. These proteins regulate an RNA transcript’s splicing and processing in the nucleus, its export from the nucleus into the cytoplasm, its localization and translation in the cytoplasm, and its eventual turnover and decay. Despite knowing the identities of roughly 700 RNA-binding proteins in budding yeast, the role in RNA regulation that many of these proteins perform remains unclear. Here we present two studies that are aimed at the functional characterization of proteins that regulate post-transcriptional gene expression. In the first study, we devised a high-throughput tethering assay for the characterization of proteins on a proteome-wide scale. This novel assay provides domain-level resolution for the functional regions of proteins and identifies their regulatory activity in a quantitative manner. In the second study, we characterized the yeast RNA-binding protein Mrn1p and found that it is a dynamic regulator of post-transcriptional regulation that functions through mRNA turnover. Mrn1p is especially important in linking cell wall biogenesis with mitochondrial homeostasis, and it regulates these two cellular compartments in a manner that is responsive to carbon source and cell stress. Together, we present two studies that provide new functional information about yeast RNA binding proteins, with broad implications for a better understanding of post-transcriptional gene expression.

... read more

Topics: RNA-binding protein (59%), Gene expression (58%), RNA (57%) ... show more

2 Citations


248 results found

Open accessJournal ArticleDOI: 10.1093/NAR/GKH073
David L. Wheeler1, Deanna M. Church1, Ron Edgar1, Scott Federhen1  +9 moreInstitutions (1)
Abstract: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, PubMed, PubMed Central, LocusLink, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SARS Coronavirus Resource, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at:

... read more

Topics: Entrez Gene (71%), Molecular Modeling Database (64%), Sequence profiling tool (64%) ... show more

8,599 Citations

Journal ArticleDOI: 10.1126/SCIENCE.2200121
Craig Tuerk1, Larry Gold1Institutions (1)
03 Aug 1990-Science
Abstract: High-affinity nucleic acid ligands for a protein were isolated by a procedure that depends on alternate cycles of ligand selection from pools of variant sequences and amplification of the bound species. Multiple rounds exponentially enrich the population for the highest affinity species that can be clonally isolated and characterized. In particular one eight-base region of an RNA that interacts with the T4 DNA polymerase was chosen and randomized. Two different sequences were selected by this procedure from the calculated pool of 65,536 species. One is the wild-type sequence found in the bacteriophage mRNA; one is varied from wild type at four positions. The binding constants of these two RNA's to T4 DNA polymerase are equivalent. These protocols with minimal modification can yield high-affinity ligands for any protein that binds nucleic acids as part of its function; high-affinity ligands could conceivably be developed for any target molecule.

... read more

8,476 Citations

Journal ArticleDOI: 10.1038/346818A0
Andrew D. Ellington1, Jack W. Szostak1Institutions (1)
30 Aug 1990-Nature
Abstract: Subpopulations of RNA molecules that bind specifically to a variety of organic dyes have been isolated from a population of random sequence RNA molecules. Roughly one in 10(10) random sequence RNA molecules folds in such a way as to create a specific binding site for small ligands.

... read more

Topics: RNA (62%), Riboswitch (62%), Binding site (60%) ... show more

7,927 Citations

Open accessJournal ArticleDOI: 10.1016/J.MOLCEL.2010.05.004
28 May 2010-Molecular Cell
Abstract: Genome-scale studies have revealed extensive, cell type-specific colocalization of transcription factors, but the mechanisms underlying this phenomenon remain poorly understood. Here, we demonstrate in macrophages and B cells that collaborative interactions of the common factor PU.1 with small sets of macrophage- or B cell lineage-determining transcription factors establish cell-specific binding sites that are associated with the majority of promoter-distal H3K4me1-marked genomic regions. PU.1 binding initiates nucleosome remodeling, followed by H3K4 monomethylation at large numbers of genomic regions associated with both broadly and specifically expressed genes. These locations serve as beacons for additional factors, exemplified by liver X receptors, which drive both cell-specific gene expression and signal-dependent responses. Together with analyses of transcription factor binding and H3K4me1 patterns in other cell types, these studies suggest that simple combinations of lineage-determining transcription factors can specify the genomic sites ultimately responsible for both cell identity and cell type-specific responses to diverse signaling inputs.

... read more

Topics: Pioneer factor (61%), General transcription factor (61%), Super-enhancer (61%) ... show more

7,287 Citations

Open accessJournal ArticleDOI: 10.1093/NAR/GKP335
Abstract: The MEME Suite web server provides a unified portal for online discovery and analysis of sequence motifs representing features such as DNA binding sites and protein interaction domains. The popular MEME motif discovery algorithm is now complemented by the GLAM2 algorithm which allows discovery of motifs containing gaps. Three sequence scanning algorithms—MAST, FIMO and GLAM2SCAN—allow scanning numerous DNA and protein sequence databases for motifs discovered by MEME and GLAM2. Transcription factor motifs (including those discovered using MEME) can be compared with motifs in many popular motif databases using the motif database scanning algorithm Tomtom. Transcription factor motifs can be further analyzed for putative function by association with Gene Ontology (GO) terms using the motif-GO term association tool GOMO. MEME output now contains sequence LOGOS for each discovered motif, as well as buttons to allow motifs to be conveniently submitted to the sequence and motif database scanning algorithms (MAST, FIMO and Tomtom), or to GOMO, for further analysis. GLAM2 output similarly contains buttons for further analysis using GLAM2SCAN and for rerunning GLAM2 with different parameters. All of the motif-based tools are now implemented as web services via Opal. Source code, binaries and a web server are freely available for noncommercial use at

... read more

6,070 Citations

No. of citations received by the Paper in previous years
Network Information
Related Papers (5)
A large-scale binding and functional map of human RNA-binding proteins29 Jul 2020, Nature

Eric L. Van Nostrand, Peter Freese +39 more

94% related
CLIP identifies Nova-regulated RNA networks in the brain.14 Nov 2003, Science

Jernej Ule, Kirk B. Jensen +8 more

80% related
A census of human RNA-binding proteins.04 Nov 2014, Nature Reviews Genetics

Stefanie Gerstberger, Markus Hafner +1 more

75% related