Improved binding site assignment by high-resolution mapping of RNA–protein interactions using iCLIP

Hauer, Christian; Curk, Tomaž; Anders, Simon; Schwarzl, Thomas; Alleaume, Anne-Marie; Sieber, Jana; Hollerer, Ina; Bhuvanagiri, Madhuri; Huber, Wolfgang; Hentze, Matthias W.; Kulozik, Andreas E.

doi:10.1038/ncomms8921

Cited by 33 publications

(42 citation statements)

References 38 publications

(84 reference statements)

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“…1b). eIF4A3-iCLIP1 refers to data generated in the previous study [8], while eIF4A3-iCLIP2 and eIF4A3-iCLIP3 were newly produced by the Le Hir and Ule labs, respectively. These are compared to the published eIF4A3 CLIP [11].…”

Section: Resultsmentioning

confidence: 99%

“…It was proposed that presence of non-coinciding cDNA-starts might indicate that some of these cDNAs have read through the crosslink site during reverse transcription [8]. It has been shown previously that such readthrough cDNAs often contain deletions, which are introduced into cDNAs at the crosslink site during reverse transcription [4, 16].…”

Section: Resultsmentioning

confidence: 99%

“…However, a recent study observed that the starts of long and short iCLIP cDNAs often map to different genomic positions for several RBPs, which leads to non-coinciding cDNA-starts [8]. Here, we focused on experiments produced for polypyrimidine tract binding protein 1 (PTBP1), eukaryotic initiation factor 4A-III (eIF4A3) and the splicing factor U2 auxiliary factor 65 kDa subunit (U2AF2), which represent examples of non-coinciding or coinciding cDNA-starts in introns or exons.…”

Section: Introductionmentioning

confidence: 99%

“…However, further studies showed that the sequence and structure of a nascent messenger RNA (mRNA) can shift EJC deposition as far as 10 nt away from this expected site [10]. The non-coinciding cDNA-starts in eIF4A3 iCLIP data produced by the previous study were shifted upstream of this expected region and it was proposed that the presence of non-coinciding cDNA-starts might be related to this shift [8]. The study concluded that the use of cDNA-starts may not be appropriate in iCLIP whenever non-coinciding cDNA-starts are prevalent.…”

Section: Introductionmentioning

confidence: 99%

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Insights into the design and interpretation of iCLIP experiments

et al. 2017

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BackgroundUltraviolet (UV) crosslinking and immunoprecipitation (CLIP) identifies the sites on RNAs that are in direct contact with RNA-binding proteins (RBPs). Several variants of CLIP exist, which require different computational approaches for analysis. This variety of approaches can create challenges for a novice user and can hamper insights from multi-study comparisons. Here, we produce data with multiple variants of CLIP and evaluate the data with various computational methods to better understand their suitability.ResultsWe perform experiments for PTBP1 and eIF4A3 using individual-nucleotide resolution CLIP (iCLIP), employing either UV-C or photoactivatable 4-thiouridine (4SU) combined with UV-A crosslinking and compare the results with published data. As previously noted, the positions of complementary DNA (cDNA)-starts depend on cDNA length in several iCLIP experiments and we now find that this is caused by constrained cDNA-ends, which can result from the sequence and structure constraints of RNA fragmentation. These constraints are overcome when fragmentation by RNase I is efficient and when a broad cDNA size range is obtained. Our study also shows that if RNase does not efficiently cut within the binding sites, the original CLIP method is less capable of identifying the longer binding sites of RBPs. In contrast, we show that a broad size range of cDNAs in iCLIP allows the cDNA-starts to efficiently delineate the complete RNA-binding sites.ConclusionsWe demonstrate the advantage of iCLIP and related methods that can amplify cDNAs that truncate at crosslink sites and we show that computational analyses based on cDNAs-starts are appropriate for such methods.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1130-x) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Insights into the design and interpretation of iCLIP experiments

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“…The identification of binding motifs will provide a deep understanding of RNA-binding mechanisms, such as molecular characteristics and affinity distributions [9, 13]. These findings are often based on sequence-based approaches in CLIP data [14, 15] and focus on the nucleotide residue patterns from the side of RNAs [16]. To date, there are numerous unique RNA-binding domains listed in Pfam [17] and other databases of RNA-binding specificities such as RBPDB [18] and CLIPZ [19].…”

Section: Introductionmentioning

confidence: 99%

Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces

Liu

Chen

et al. 2017

BMC Bioinformatics

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BackgroundMany critical biological processes are strongly related to protein-RNA interactions. Revealing the protein structure motifs for RNA-binding will provide valuable information for deciphering protein-RNA recognition mechanisms and benefit complementary structural design in bioengineering. RNA-binding events often take place at pockets on protein surfaces. The structural classification of local binding pockets determines the major patterns of RNA recognition.ResultsIn this work, we provide a novel framework for systematically identifying the structure motifs of protein-RNA binding sites in the form of pockets on regional protein surfaces via a structure alignment-based method. We first construct a similarity network of RNA-binding pockets based on a non-sequential-order structure alignment method for local structure alignment. By using network community decomposition, the RNA-binding pockets on protein surfaces are clustered into groups with structural similarity. With a multiple structure alignment strategy, the consensus RNA-binding pockets in each group are identified. The crucial recognition patterns, as well as the protein-RNA binding motifs, are then identified and analyzed.ConclusionsLarge-scale RNA-binding pockets on protein surfaces are grouped by measuring their structural similarities. This similarity network-based framework provides a convenient method for modeling the structural relationships of functional pockets. The local structural patterns identified serve as structure motifs for the recognition with RNA on protein surfaces.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1410-1) contains supplementary material, which is available to authorized users.

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Bioinformatic tools for analysis of CLIP ribonucleoprotein data

Gorospe

2016

WIREs RNA

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Investigating the interactions of RNA-binding proteins (RBPs) with RNAs is a complex task for molecular and computational biologists. The molecular biology techniques and the computational approaches to understand RBP–RNA (or ribonucleoprotein, RNP) interactions have advanced considerably over the past few years and numerous and diverse software tools have been developed to analyze these data. Accordingly, laboratories interested in RNP biology face the challenge of choosing adequately among the available software tools those that best address the biological problem they are studying. Here, we focus on state-of-the-art molecular biology techniques that employ crosslinking and immunoprecipitation (CLIP) of an RBP to study and map RNP interactions. We review the different software tools and databases available to analyze the most widely used CLIP methods, HITS-CLIP, PAR-CLIP, and iCLIP.

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Improved binding site assignment by high-resolution mapping of RNA–protein interactions using iCLIP

Cited by 33 publications

References 38 publications

Insights into the design and interpretation of iCLIP experiments

Insights into the design and interpretation of iCLIP experiments

Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces

Bioinformatic tools for analysis of CLIP ribonucleoprotein data

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