Large-scale identification of RBP-RNA interactions by RAPseq refines essentials of post-transcriptional gene regulation

Over the past decade, thousands of putative human RNA binding proteins (RBPs) have been identified and increased the demand for specifying RNA binding capacities. Here, we developed RNA affinity purification followed by sequencing (RAPseq) that enables in vitro large-scale profiling of RBP binding to native RNAs. First, by employing RAPseq, we found that vertebrate HURs recognize a conserved RNA binding motif and bind predominantly to introns in zebrafish compared to 3'UTRs in human RNAs. Second, our dual RBP assays (co-RAPseq) uncovered cooperative RNA binding of HUR and PTBP1 within an optimal distance of 27 nucleotides. Third, we developed T7-RAPseq to discern m6A-dependent and -independent RNA binding sites of YTHDF1. Fourth, RAPseq of 26 novel non-canonical RBPs revealed specialized moonlighting interactions. Last, five pathological IGF2BP family variants exhibited different RNA binding patterns. Overall, our simple, scalable and versatile method enables to fast-forward RBP-related questions.

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SSMART: Sequence-structure motif identification for RNA-binding proteins

10.1101/287953 ◽

2018 ◽

Cited By ~ 2

Author(s):

Alina Munteanu ◽

Neelanjan Mukherjee ◽

Uwe Ohler

Keyword(s):

Binding Sites ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Sequence Motif ◽

Primary Sequence ◽

Sequence Structure ◽

Rna Targets

AbstractMotivationRNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized.ResultsWe developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3‘UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP.AvailabilitySSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/[email protected]

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Concurrent binding to DNA and RNA facilitates the pluripotency reprogramming activity of Sox2

Nucleic Acids Research ◽

10.1093/nar/gkaa067 ◽

2020 ◽

Vol 48 (7) ◽

pp. 3869-3887 ◽

Cited By ~ 1

Author(s):

Linlin Hou ◽

Yuanjie Wei ◽

Yingying Lin ◽

Xiwei Wang ◽

Yiwei Lai ◽

...

Keyword(s):

Dna Sequences ◽

Target Genes ◽

Rna Binding ◽

Rna Binding Proteins ◽

High Mobility ◽

Binding Motif ◽

Dna And Rna ◽

Somatic Cell Reprogramming ◽

Double Stranded Dna

Abstract Some transcription factors that specifically bind double-stranded DNA appear to also function as RNA-binding proteins. Here, we demonstrate that the transcription factor Sox2 is able to directly bind RNA in vitro as well as in mouse and human cells. Sox2 targets RNA via a 60-amino-acid RNA binding motif (RBM) positioned C-terminally of the DNA binding high mobility group (HMG) box. Sox2 can associate with RNA and DNA simultaneously to form ternary RNA/Sox2/DNA complexes. Deletion of the RBM does not affect selection of target genes but mitigates binding to pluripotency related transcripts, switches exon usage and impairs the reprogramming of somatic cells to a pluripotent state. Our findings designate Sox2 as a multi-functional factor that associates with RNA whilst binding to cognate DNA sequences, suggesting that it may co-transcriptionally regulate RNA metabolism during somatic cell reprogramming.

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HNRNPA1 promotes recognition of splice site decoys by U2AF2 in vivo

10.1101/175901 ◽

2017 ◽

Author(s):

Jonathan M. Howard ◽

Hai Lin ◽

Garam Kim ◽

Jolene M Draper ◽

Maximilian Haeussler ◽

...

Keyword(s):

Splice Site ◽

Binding Sites ◽

Rna Binding ◽

Rna Binding Proteins ◽

Regulatory Elements ◽

Splice Sites ◽

Spliceosome Assembly ◽

Over Expression

AbstractAlternative pre-mRNA splicing plays a major role in expanding the transcript output of human genes. This process is regulated, in part, by the interplay of trans-acting RNA binding proteins (RBPs) with myriad cis-regulatory elements scattered throughout pre-mRNAs. These molecular recognition events are critical for defining the protein coding sequences (exons) within pre-mRNAs and directing spliceosome assembly on non-coding regions (introns). One of the earliest events in this process is recognition of the 3’ splice site by U2 small nuclear RNA auxiliary factor 2 (U2AF2). Splicing regulators, such as the heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1), influence spliceosome assembly both in vitro and in vivo, but their mechanisms of action remain poorly described on a global scale. HNRNPA1 also promotes proof reading of 3’ss sequences though a direct interaction with the U2AF heterodimer. To determine how HNRNPA1 regulates U2AF-RNA interactions in vivo, we analyzed U2AF2 RNA binding specificity using individual-nucleotide resolution crosslinking immunoprecipitation (iCLIP) in control- and HNRNPA1 over-expression cells. We observed changes in the distribution of U2AF2 crosslinking sites relative to the 3’ splice sites of alternative cassette exons but not constitutive exons upon HNRNPA1 over-expression. A subset of these events shows a concomitant increase of U2AF2 crosslinking at distal intronic regions, suggesting a shift of U2AF2 to “decoy” binding sites. Of the many non-canonical U2AF2 binding sites, Alu-derived RNA sequences represented one of the most abundant classes of HNRNPA1-dependent decoys. Splicing reporter assays demonstrated that mutation of U2AF2 decoy sites inhibited HNRNPA1-dependent exon skipping in vivo. We propose that HNRNPA1 regulates exon definition by modulating the interaction of U2AF2 with decoy or bona fide 3’ splice sites.

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Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks

10.1101/146175 ◽

2017 ◽

Cited By ~ 3

Author(s):

Xiaoyong Pan ◽

Peter Rijnbeek ◽

Junchi Yan ◽

Hong-Bin Shen

Keyword(s):

Neural Networks ◽

Binding Sites ◽

Large Scale ◽

Rna Binding ◽

Short Term Memory ◽

Rna Binding Proteins ◽

Point Of View ◽

Rna Sequences ◽

Close Relationship ◽

Binding Sequence

AbstractRNA regulation is significantly dependent on its binding protein partner, which is known as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs are still not well characterized, especially on the structure point of view. Informative signals hiding and interdependencies between sequence and structure specificities are two challenging problems for both predicting RBP binding sites and accurate sequence and structure motifs mining.In this study, we propose a deep learning-based method, iDeepS, to simultaneously identify the binding sequence and structure motifs from RNA sequences using convolutional neural networks (CNNs) and a bidirectional long short term memory network (BLSTM). We first perform one-hot encoding for both the sequence and predicted secondary structure, which are appropriate for subsequent convolution operations. To reveal the hidden binding knowledge from the observations, the CNNs are applied to learn the abstract motif features. Considering the close relationship between sequences and predicted structures, we use the BLSTM to capture the long range dependencies between binding sequence and structure motifs identified by the CNNs. Finally, the learned weighted representations are fed into a classification layer to predict the RBP binding sites. We evaluated iDeepS on verified RBP binding sites derived from large-scale representative CLIP-seq datasets, and the results demonstrate that iDeepS can reliably predict the RBP binding sites on RNAs, and outperforms the state-of-the-art methods. An important advantage is that iDeepS is able to automatically extract both binding sequence and structure motifs, which will improve our transparent understanding of the mechanisms of binding specificities of RBPs. iDeepS is available at https://github.com/xypan1232/iDeepS.

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Differential Binding of Mitochondrial Transcripts by MRB8170 and MRB4160 Regulates Distinct Editing Fates of Mitochondrial mRNA in Trypanosomes

mBio ◽

10.1128/mbio.02288-16 ◽

2017 ◽

Vol 8 (1) ◽

Cited By ~ 10

Author(s):

Sameer Dixit ◽

Michaela Müller-McNicoll ◽

Vojtěch David ◽

Kathi Zarnack ◽

Jernej Ule ◽

...

Keyword(s):

Trypanosoma Brucei ◽

Rna Editing ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Affinity Purification ◽

Mitochondrial Rna ◽

Nucleotide Resolution ◽

Additional Role

ABSTRACT A dozen mRNAs are edited by multiple insertions and/or deletions of uridine residues in the mitochondrion of Trypanosoma brucei . Several protein complexes have been implicated in performing this type of RNA editing, including the mitochondrial RNA-binding complex 1 (MRB1). Two paralogous novel RNA-binding proteins, MRB8170 and MRB4160, are loosely associated with the core MRB1 complex. Their roles in RNA editing and effects on target mRNAs are so far not well understood. In this study, individual-nucleotide-resolution UV-cross-linking and affinity purification (iCLAP) revealed a preferential binding of both proteins to mitochondrial mRNAs, which was positively correlated with their extent of editing. Integrating additional in vivo and in vitro data, we propose that binding of MRB8170 and/or MRB4160 onto pre-mRNA marks it for the initiation of editing and that initial binding of both proteins may facilitate the recruitment of other components of the RNA editing/processing machinery to ensure efficient editing. Surprisingly, MRB8170 also binds never-edited mRNAs, suggesting that at least this paralog has an additional role outside RNA editing to shape the mitochondrial transcriptome. IMPORTANCE Trypanosoma brucei mitochondrial mRNAs undergo maturation by RNA editing, a unique process involving decrypting open reading frames by the precise deletion and/or insertion of uridine (U) residues at specific positions on an mRNA. This process is catalyzed by multiprotein complexes, such as the RNA editing core complex, which provides the enzymatic activities needed for U insertion/deletion at a single editing site. Less well understood is how RNA editing occurs throughout an mRNA bearing multiple sites. To address this question, we mapped at single-nucleotide resolution the RNA interactions of two unique RNA-binding proteins (RBPs). These RBPs are part of the mitochondrial RNA-binding complex 1, hypothesized to mediate multiple rounds of RNA editing. Both RBPs were shown to mark mRNAs for the process in correlation with the number of editing sites on the transcript. Surprisingly, one also binds mRNAs that bypass RNA editing, indicating that it may have an additional role outside RNA editing.

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Deep neural networks for inferring binding sites of RNA-binding proteins by using distributed representations of RNA primary sequence and secondary structure

BMC Genomics ◽

10.1186/s12864-020-07239-w ◽

2020 ◽

Vol 21 (S13) ◽

Author(s):

Lei Deng ◽

Youzhi Liu ◽

Yechuan Shi ◽

Wenhao Zhang ◽

Chun Yang ◽

...

Keyword(s):

Neural Networks ◽

Secondary Structure ◽

Binding Sites ◽

Large Scale ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Secondary Structures ◽

Rna Sequences ◽

Distributed Representations

Abstract Background RNA binding proteins (RBPs) play a vital role in post-transcriptional processes in all eukaryotes, such as splicing regulation, mRNA transport, and modulation of mRNA translation and decay. The identification of RBP binding sites is a crucial step in understanding the biological mechanism of post-transcriptional gene regulation. However, the determination of RBP binding sites on a large scale is a challenging task due to high cost of biochemical assays. Quite a number of studies have exploited machine learning methods to predict binding sites. Especially, deep learning is increasingly used in the bioinformatics field by virtue of its ability to learn generalized representations from DNA and protein sequences. Results In this paper, we implemented a novel deep neural network model, DeepRKE, which combines primary RNA sequence and secondary structure information to effectively predict RBP binding sites. Specifically, we used word embedding algorithm to extract features of RNA sequences and secondary structures, i.e., distributed representation of k-mers sequence rather than traditional one-hot encoding. The distributed representations are taken as input of convolutional neural networks (CNN) and bidirectional long-term short-term memory networks (BiLSTM) to identify RBP binding sites. Our results show that deepRKE outperforms existing counterpart methods on two large-scale benchmark datasets. Conclusions Our extensive experimental results show that DeepRKE is an efficacious tool for predicting RBP binding sites. The distributed representations of RNA sequences and secondary structures can effectively detect the latent relationship and similarity between k-mers, and thus improve the predictive performance. The source code of DeepRKE is available at https://github.com/youzhiliu/DeepRKE/.

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FLASH: ultra-fast protocol to identify RNA–protein interactions in cells

Nucleic Acids Research ◽

10.1093/nar/gkz1141 ◽

2019 ◽

Vol 48 (3) ◽

pp. e15-e15 ◽

Cited By ~ 1

Author(s):

Ibrahim Avsar Ilik ◽

Tugce Aktas ◽

Daniel Maticzka ◽

Rolf Backofen ◽

Asifa Akhtar

Keyword(s):

High Throughput ◽

Protein Interactions ◽

Binding Sites ◽

Binding Proteins ◽

High Throughput Sequencing ◽

Rna Binding ◽

Rna Binding Proteins ◽

Affinity Purification ◽

Sequencing Library

Abstract Determination of the in vivo binding sites of RNA-binding proteins (RBPs) is paramount to understanding their function and how they affect different aspects of gene regulation. With hundreds of RNA-binding proteins identified in human cells, a flexible, high-resolution, high-throughput, highly multiplexible and radioactivity-free method to determine their binding sites has not been described to date. Here we report FLASH (Fast Ligation of RNA after some sort of Affinity Purification for High-throughput Sequencing), which uses a special adapter design and an optimized protocol to determine protein–RNA interactions in living cells. The entire FLASH protocol, starting from cells on plates to a sequencing library, takes 1.5 days. We demonstrate the flexibility, speed and versatility of FLASH by using it to determine RNA targets of both tagged and endogenously expressed proteins under diverse conditions in vivo.

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m6A methyltransferase RBM15 promotes cardiomyocytes survival under hypoxia by increasing Thbs4 RNA methylation and mediating PI3K/Akt signaling

European Heart Journal ◽

10.1093/ehjci/ehaa946.3644 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

H Cheng ◽

X.Y Song ◽

J.Q Xue ◽

L Chen ◽

R.D Xu ◽

...

Keyword(s):

Cell Proliferation ◽

Rna Binding ◽

Rna Binding Proteins ◽

Basic Mechanism ◽

Vital Role ◽

Rna Modification ◽

Binding Motif ◽

Funding Source

Abstract Background mRNA modifications constitute ancient mechanisms in regulating gene expression after transcription. N6-methyladenosis (m6A), which is the most prevalent internal RNA modification, is not only installed by m6A methyltransferases, removed by demethylases, but also specifically bounded by RNA-binding proteins. As a significant component in the m6A methyltransferase complex, RNA binding motif protein 15 (RBM15) plays a vital role in m6A methylation. Nevertheless, its function and mechanism in myocardial infarction (MI) remain poorly defined. Purpose To investigate the role and mechanism of RBM15 in regulating its targets through m6A methylation in MI. The research results will not only add new content to the basic mechanism of myocardial protection but also provide new ideas and new targets for the prevention and treatment of MI. Methods Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to clarify the total m6A level, and Reverse transcription quantitative real-time PCR (RT-qPCR) and Western blot were used to determine the expression of RBM15 in normal and MI tissues. Then the effects of RBM15 on cardiomyocytes were clarified using apoptosis assay, and cell proliferation assay. Methylated RNA immunoprecipitation sequencing (MeRIP-seq), and transcriptomic RNA sequencing (RNA-seq) were used to perform the regulator mechanism of RBM15 on target gene Thbs4 in MI. Results In this research, we showed that total m6A methylation was increased in MI, and RBM15 was a main factor involved with this process. Silencing RBM15 remarkably decreased cell proliferation and increased apoptosis in vitro, and resulted in severe cardiac remodeling and further exacerbation of cardiac dysfunction in vivo, whereas its overexpression caused the opposite effects. Then, Thbs4 was identified as a direct downstream target of RBM15, and RBM15 induced m6A methylation on the 3'UTR of Thbs4 pre-mRNA. We also found that it showed faster Thbs4 mRNA decay and exhibited decreased mRNAs and levels of protein expression in RBM15-deficient cardiomyocytes under hypoxia. Furthermore, we confirmed that RBM15 contributed significantly to regulate the PI3k/Akt pathway. Conclusions Our work uncovers a complex RBM15-Thbs4-PI3K/Akt regulatory model based on m6A methylation and provides a new insight into the epi-transcriptomic dysregulation in MI development. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Natural Science Foundation of China

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Zooming in on protein–RNA interactions: a multi-level workflow to identify interaction partners

Biochemical Society Transactions ◽

10.1042/bst20191059 ◽

2020 ◽

Vol 48 (4) ◽

pp. 1529-1543

Author(s):

Alessio Colantoni ◽

Jakob Rupert ◽

Andrea Vandelli ◽

Gian Gaetano Tartaglia ◽

Elsa Zacco

Keyword(s):

Binding Sites ◽

Rna Binding ◽

Rna Binding Proteins ◽

Rna Sequences ◽

Binding Partners ◽

Interaction Partners ◽

Multi Level ◽

Non Coding Rnas ◽

Computational Predictions

Interactions between proteins and RNA are at the base of numerous cellular regulatory and functional phenomena. The investigation of the biological relevance of non-coding RNAs has led to the identification of numerous novel RNA-binding proteins (RBPs). However, defining the RNA sequences and structures that are selectively recognised by an RBP remains challenging, since these interactions can be transient and highly dynamic, and may be mediated by unstructured regions in the protein, as in the case of many non-canonical RBPs. Numerous experimental and computational methodologies have been developed to predict, identify and verify the binding between a given RBP and potential RNA partners, but navigating across the vast ocean of data can be frustrating and misleading. In this mini-review, we propose a workflow for the identification of the RNA binding partners of putative, newly identified RBPs. The large pool of potential binders selected by in-cell experiments can be enriched by in silico tools such as catRAPID, which is able to predict the RNA sequences more likely to interact with specific RBP regions with high accuracy. The RNA candidates with the highest potential can then be analysed in vitro to determine the binding strength and to precisely identify the binding sites. The results thus obtained can furthermore validate the computational predictions, offering an all-round solution to the issue of finding the most likely RNA binding partners for a newly identified potential RBP.

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RNANetMotif: identifying sequence-structure RNA network motifs in RNA-protein binding sites

10.1101/2021.09.15.460452 ◽

2021 ◽

Author(s):

Hongli Ma ◽

Han Wen ◽

Zhiyuan Xue ◽

Guojun Li ◽

Zhaolei Zhang

Keyword(s):

Binding Sites ◽

Rna Binding ◽

Rna Binding Proteins ◽

Solvent Accessibility ◽

Protein Docking ◽

Theory Approach ◽

Sequence Structure ◽

Structure Information

RNA molecules can adopt stable secondary and tertiary structures, which is essential in mediating physical interactions with other partners such as RNA binding proteins (RBPs) and in carrying out their cellular functions. In vivo and in vitro experiments such as RNAcompete and eCLIP have revealed in vitro binding preferences of RBPs to RNA oligomers and in vivo binding sites in cells. Analysis of these binding data showed that the structure properties of the RNAs in these binding sites are important determinants of the binding events; however, it has been a challenge to incorporate the structure information into an interpretable model. Here we describe a new approach, RNANetMotif, which takes predicted secondary structure of thousands of RNA sequences bound by an RBP as input and uses a graph theory approach to recognize enriched subgraphs. These enriched subgraphs are in essence shared sequence-structure elements that are important in RBP-RNA binding. To validate our approach, we performed RNA structure modeling via discrete molecular dynamics folding simulations for selected 4 RBPs, and RNA-protein docking for LIN28. The simulation results, e.g., solvent accessibility and energetics, further support the biological relevance of the discovered network subgraphs.

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