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  1. Article ; Online: PRIESSTESS: interpretable, high-performing models of the sequence and structure preferences of RNA-binding proteins.

    Laverty, Kaitlin U / Jolma, Arttu / Pour, Sara E / Zheng, Hong / Ray, Debashish / Morris, Quaid / Hughes, Timothy R

    Nucleic acids research

    2022  Volume 50, Issue 19, Page(s) e111

    Abstract: Modelling both primary sequence and secondary structure preferences for RNA binding proteins (RBPs) remains an ongoing challenge. Current models use varied RNA structure representations and can be difficult to interpret and evaluate. To address these ... ...

    Abstract Modelling both primary sequence and secondary structure preferences for RNA binding proteins (RBPs) remains an ongoing challenge. Current models use varied RNA structure representations and can be difficult to interpret and evaluate. To address these issues, we present a universal RNA motif-finding/scanning strategy, termed PRIESSTESS (Predictive RBP-RNA InterpretablE Sequence-Structure moTif regrESSion), that can be applied to diverse RNA binding datasets. PRIESSTESS identifies dozens of enriched RNA sequence and/or structure motifs that are subsequently reduced to a set of core motifs by logistic regression with LASSO regularization. Importantly, these core motifs are easily visualized and interpreted, and provide a measure of RBP secondary structure specificity. We used PRIESSTESS to interrogate new HTR-SELEX data for 23 RBPs with diverse RNA binding modes and captured known primary sequence and secondary structure preferences for each. Moreover, when applying PRIESSTESS to 144 RBPs across 202 RNA binding datasets, 75% showed an RNA secondary structure preference but only 10% had a preference besides unpaired bases, suggesting that most RBPs simply recognize the accessibility of primary sequences.
    MeSH term(s) Binding Sites ; Algorithms ; RNA-Binding Proteins/metabolism ; Nucleotide Motifs ; RNA/chemistry ; Protein Binding
    Chemical Substances RNA-Binding Proteins ; RNA (63231-63-0)
    Language English
    Publishing date 2022-08-26
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ZDB-ID 186809-3
    ISSN 1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
    ISSN (online) 1362-4962 ; 1362-4954
    ISSN 0301-5610 ; 0305-1048
    DOI 10.1093/nar/gkac694
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Motif models for RNA-binding proteins.

    Sasse, Alexander / Laverty, Kaitlin U / Hughes, Timothy R / Morris, Quaid D

    Current opinion in structural biology

    2018  Volume 53, Page(s) 115–123

    Abstract: Identifying the binding preferences of RNA-binding proteins (RBPs) is important in understanding their contribution to post-transcriptional regulation. Here, we review the current state-of-the art of RNA motif identification tools for RBPs. New in vivo ... ...

    Abstract Identifying the binding preferences of RNA-binding proteins (RBPs) is important in understanding their contribution to post-transcriptional regulation. Here, we review the current state-of-the art of RNA motif identification tools for RBPs. New in vivo and in vitro data sets provide sufficient statistical power to enable detection of relatively long and complex sequence and sequence-structure binding preferences, and recent computational methods are geared towards quantitative identification of these patterns. We classify methods by their motif model's representational power and describe the underlying considerations for RNA-protein interactions. All classical motif identification algorithms apply physically motivated architectures, consisting of a motif and an occupancy model, we call these explicit motif models. Recent methods, such as convolutional neural networks and support vector machines, abandon the classical architecture and implicitly model RNA binding without defining a motif model. Although they achieve high accuracy on held-out data they may be unsuitable to solve the ultimate goal of the field, using motifs trained on in vitro data to predict in vivo binding sites. For this task methods need to separate intrinsic binding preferences from cellular effects from protein and RNA concentrations, cooperativity, and competition. To tackle this problem, we advocate for the use of a `three-layer' architecture, consisting of motif model, occupancy model, and extrinsic factor model, which enables separation and adjustment to cellular conditions.
    MeSH term(s) Algorithms ; Binding Sites ; Computational Biology/methods ; Models, Molecular ; Molecular Conformation ; Nucleic Acid Conformation ; Nucleotide Motifs ; Protein Binding ; RNA/chemistry ; RNA-Binding Proteins/chemistry
    Chemical Substances RNA-Binding Proteins ; RNA (63231-63-0)
    Language English
    Publishing date 2018-08-29
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 1068353-7
    ISSN 1879-033X ; 0959-440X
    ISSN (online) 1879-033X
    ISSN 0959-440X
    DOI 10.1016/j.sbi.2018.08.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: RNA-binding proteins that lack canonical RNA-binding domains are rarely sequence-specific.

    Ray, Debashish / Laverty, Kaitlin U / Jolma, Arttu / Nie, Kate / Samson, Reuben / Pour, Sara E / Tam, Cyrus L / von Krosigk, Niklas / Nabeel-Shah, Syed / Albu, Mihai / Zheng, Hong / Perron, Gabrielle / Lee, Hyunmin / Najafabadi, Hamed / Blencowe, Benjamin / Greenblatt, Jack / Morris, Quaid / Hughes, Timothy R

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 5238

    Abstract: Thousands of RNA-binding proteins (RBPs) crosslink to cellular mRNA. Among these are numerous unconventional RBPs (ucRBPs)-proteins that associate with RNA but lack known RNA-binding domains (RBDs). The vast majority of ucRBPs have uncharacterized RNA- ... ...

    Abstract Thousands of RNA-binding proteins (RBPs) crosslink to cellular mRNA. Among these are numerous unconventional RBPs (ucRBPs)-proteins that associate with RNA but lack known RNA-binding domains (RBDs). The vast majority of ucRBPs have uncharacterized RNA-binding specificities. We analyzed 492 human ucRBPs for intrinsic RNA-binding in vitro and identified 23 that bind specific RNA sequences. Most (17/23), including 8 ribosomal proteins, were previously associated with RNA-related function. We identified the RBDs responsible for sequence-specific RNA-binding for several of these 23 ucRBPs and surveyed whether corresponding domains from homologous proteins also display RNA sequence specificity. CCHC-zf domains from seven human proteins recognized specific RNA motifs, indicating that this is a major class of RBD. For Nudix, HABP4, TPR, RanBP2-zf, and L7Ae domains, however, only isolated members or closely related homologs yielded motifs, consistent with RNA-binding as a derived function. The lack of sequence specificity for most ucRBPs is striking, and we suggest that many may function analogously to chromatin factors, which often crosslink efficiently to cellular DNA, presumably via indirect recruitment. Finally, we show that ucRBPs tend to be highly abundant proteins and suggest their identification in RNA interactome capture studies could also result from weak nonspecific interactions with RNA.
    MeSH term(s) Humans ; RNA-Binding Proteins/genetics ; RNA-Binding Proteins/metabolism ; RNA/metabolism ; Ribosomal Proteins/metabolism ; RNA, Messenger/genetics ; RNA, Messenger/metabolism ; RNA-Binding Motifs/genetics ; Protein Binding ; Myogenic Regulatory Factors/metabolism
    Chemical Substances RNA-Binding Proteins ; RNA (63231-63-0) ; Ribosomal Proteins ; RNA, Messenger ; HABP4 protein, human ; Myogenic Regulatory Factors
    Language English
    Publishing date 2023-03-31
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-32245-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Binding specificities of human RNA-binding proteins toward structured and linear RNA sequences.

    Jolma, Arttu / Zhang, Jilin / Mondragón, Estefania / Morgunova, Ekaterina / Kivioja, Teemu / Laverty, Kaitlin U / Yin, Yimeng / Zhu, Fangjie / Bourenkov, Gleb / Morris, Quaid / Hughes, Timothy R / Maher, Louis James / Taipale, Jussi

    Genome research

    2020  Volume 30, Issue 7, Page(s) 962–973

    Abstract: RNA-binding proteins (RBPs) regulate RNA metabolism at multiple levels by affecting splicing of nascent transcripts, RNA folding, base modification, transport, localization, translation, and stability. Despite their central role in RNA function, the RNA- ... ...

    Abstract RNA-binding proteins (RBPs) regulate RNA metabolism at multiple levels by affecting splicing of nascent transcripts, RNA folding, base modification, transport, localization, translation, and stability. Despite their central role in RNA function, the RNA-binding specificities of most RBPs remain unknown or incompletely defined. To address this, we have assembled a genome-scale collection of RBPs and their RNA-binding domains (RBDs) and assessed their specificities using high-throughput RNA-SELEX (HTR-SELEX). Approximately 70% of RBPs for which we obtained a motif bound to short linear sequences, whereas ∼30% preferred structured motifs folding into stem-loops. We also found that many RBPs can bind to multiple distinctly different motifs. Analysis of the matches of the motifs in human genomic sequences suggested novel roles for many RBPs. We found that three cytoplasmic proteins-ZC3H12A, ZC3H12B, and ZC3H12C-bound to motifs resembling the splice donor sequence, suggesting that these proteins are involved in degradation of cytoplasmic viral and/or unspliced transcripts. Structural analysis revealed that the RNA motif was not bound by the conventional C3H1 RNA-binding domain of ZC3H12B. Instead, the RNA motif was bound by the ZC3H12B's PilT N terminus (PIN) RNase domain, revealing a potential mechanism by which unconventional RBDs containing active sites or molecule-binding pockets could interact with short, structured RNA molecules. Our collection containing 145 high-resolution binding specificity models for 86 RBPs is the largest systematic resource for the analysis of human RBPs and will greatly facilitate future analysis of the various biological roles of this important class of proteins.
    MeSH term(s) Base Sequence ; Genome, Human ; Humans ; Nucleic Acid Conformation ; Nucleotide Motifs ; Protein Binding ; Protein Domains ; Protein Multimerization ; RNA/chemistry ; RNA/metabolism ; RNA-Binding Proteins/chemistry ; RNA-Binding Proteins/metabolism ; Ribonucleases/chemistry ; Ribonucleases/metabolism ; SELEX Aptamer Technique
    Chemical Substances RNA-Binding Proteins ; RNA (63231-63-0) ; Ribonucleases (EC 3.1.-) ; ZC3H12B protein, human (EC 3.1.-)
    Language English
    Publishing date 2020-07-23
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1284872-4
    ISSN 1549-5469 ; 1088-9051 ; 1054-9803
    ISSN (online) 1549-5469
    ISSN 1088-9051 ; 1054-9803
    DOI 10.1101/gr.258848.119
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: RNAcompete-S: Combined RNA sequence/structure preferences for RNA binding proteins derived from a single-step in vitro selection.

    Cook, Kate B / Vembu, Shankar / Ha, Kevin C H / Zheng, Hong / Laverty, Kaitlin U / Hughes, Timothy R / Ray, Debashish / Morris, Quaid D

    Methods (San Diego, Calif.)

    2017  Volume 126, Page(s) 18–28

    Abstract: RNA-binding proteins recognize RNA sequences and structures, but there is currently no systematic and accurate method to derive large (>12base) motifs de novo that reflect a combination of intrinsic preference to both sequence and structure. To address ... ...

    Abstract RNA-binding proteins recognize RNA sequences and structures, but there is currently no systematic and accurate method to derive large (>12base) motifs de novo that reflect a combination of intrinsic preference to both sequence and structure. To address this absence, we introduce RNAcompete-S, which couples a single-step competitive binding reaction with an excess of random RNA 40-mers to a custom computational pipeline for interrogation of the bound RNA sequences and derivation of SSMs (Sequence and Structure Models). RNAcompete-S confirms that HuR, QKI, and SRSF1 prefer binding sites that are single stranded, and recapitulates known 8-10bp sequence and structure preferences for Vts1p and RBMY. We also derive an 18-base long SSM for Drosophila SLBP, which to our knowledge has not been previously determined by selections from pure random sequence, and accurately discriminates human replication-dependent histone mRNAs. Thus, RNAcompete-S enables accurate identification of large, intrinsic sequence-structure specificities with a uniform assay.
    Language English
    Publishing date 2017-08-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1066584-5
    ISSN 1095-9130 ; 1046-2023
    ISSN (online) 1095-9130
    ISSN 1046-2023
    DOI 10.1016/j.ymeth.2017.06.024
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  6. Article ; Online: A physical and genetic map of

    Laverty, Kaitlin U / Stout, Jake M / Sullivan, Mitchell J / Shah, Hardik / Gill, Navdeep / Holbrook, Larry / Deikus, Gintaras / Sebra, Robert / Hughes, Timothy R / Page, Jonathan E / van Bakel, Harm

    Genome research

    2018  Volume 29, Issue 1, Page(s) 146–156

    Abstract: ... Cannabis ... ...

    Abstract Cannabis sativa
    MeSH term(s) Cannabinoids/biosynthesis ; Cannabinoids/genetics ; Cannabis/genetics ; Cannabis/metabolism ; Chromosome Mapping ; Chromosomes, Plant/genetics ; Chromosomes, Plant/metabolism ; Gene Rearrangement ; Ligases/genetics ; Ligases/metabolism ; Plant Proteins/genetics ; Plant Proteins/metabolism
    Chemical Substances Cannabinoids ; Plant Proteins ; Ligases (EC 6.-)
    Language English
    Publishing date 2018-11-08
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 1284872-4
    ISSN 1549-5469 ; 1088-9051 ; 1054-9803
    ISSN (online) 1549-5469
    ISSN 1088-9051 ; 1054-9803
    DOI 10.1101/gr.242594.118
    Database MEDical Literature Analysis and Retrieval System OnLINE

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