De Novo Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function
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{"title"=>"De Novo Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function", "type"=>"journal", "authors"=>[{"first_name"=>"Areum", "last_name"=>"Han", "scopus_author_id"=>"36843269600"}, {"first_name"=>"Peter", "last_name"=>"Stoilov", "scopus_author_id"=>"7801597689"}, {"first_name"=>"Anthony J.", "last_name"=>"Linares", "scopus_author_id"=>"56031509600"}, {"first_name"=>"Yu", "last_name"=>"Zhou", "scopus_author_id"=>"15023827400"}, {"first_name"=>"Xiang Dong", "last_name"=>"Fu", "scopus_author_id"=>"7402204673"}, {"first_name"=>"Douglas L.", "last_name"=>"Black", "scopus_author_id"=>"7402568558"}], "year"=>2014, "source"=>"PLoS Computational Biology", "identifiers"=>{"pui"=>"372348763", "sgr"=>"84893743482", "issn"=>"1553734X", "pmid"=>"24499931", "scopus"=>"2-s2.0-84893743482", "doi"=>"10.1371/journal.pcbi.1003442", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)"}, "id"=>"9193976b-39c1-38f4-acfa-3f0cd5cb80ee", "abstract"=>"A key step in the regulation of mammalian genes is the splicing of the messenger RNA precursor to produce a mature mRNA that can be translated into a particular protein needed by the cell. Through the process of alternative splicing, mRNAs encoding different proteins can be derived from the same primary gene transcript. The regulation of this process plays essential roles in the development of differentiated tissues and is mediated by special pre-mRNA binding proteins. To understand how these proteins control gene expression, one must characterize what they recognize in RNA and identify these binding sites across the genome in order to predict their targets. Models that allow this prediction are essential to understanding developmental regulatory programs and their perturbation by disease causing mutations. In this study, we use statistical methods to build models of RNA recognition by the important splicing regulator PTBP1 and then apply these models to predict PTBP1 regulation of new gene transcripts. We show that PTBP1 has different specificity for RNA than was previously recognized and that its target exons are more diverse than was known before. There are many similar splicing regulators in mammalian cells, and these analyses provide a general framework for the computational analysis of their RNA binding and target identification.", "link"=>"http://www.mendeley.com/research/novo-prediction-ptbp1-binding-splicing-targets-reveals-unexpected-features-rna-recognition-function", "reader_count"=>53, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Researcher"=>10, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>19, "Student > Postgraduate"=>3, "Student > Master"=>8, "Other"=>4, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Researcher"=>10, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>19, "Student > Postgraduate"=>3, "Student > Master"=>8, "Other"=>4, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>10, "Mathematics"=>1, "Agricultural and Biological Sciences"=>34, "Medicine and Dentistry"=>3, "Neuroscience"=>1, "Chemistry"=>2, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Neuroscience"=>{"Neuroscience"=>1}, "Chemistry"=>{"Chemistry"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>34}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>10}, "Mathematics"=>{"Mathematics"=>1}}, "reader_count_by_country"=>{"United States"=>2, "China"=>1, "Switzerland"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1368381"], "description"=>"<p><b>A</b>. Candidate PTBP1-repressed exons with probability greater than 0.65 were validated by RT-PCR following <i>Ptbp1</i> knockdown. Data shown are averages ± standard error of PSI (Percent of Spliced In) from biological triplicates. Statistical analysis was performed using paired one-tailed Student's t-test (p-values<0.01**, <0.05*). <b>B</b>. Exons with low PTBP1 repression probabilities (≤0.2) were also validated by RT-PCR following <i>Ptbp1</i> knockdown in biological triplicates.</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "ptbp1-repressed", "exons"], "article_id"=>919584, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.g005", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_of_novel_PTBP1_repressed_exons_by_RT_PCR_/919584", "title"=>"Validation of novel PTBP1-repressed exons by RT-PCR.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368384"], "description"=>"<p><b>A</b>. Validation of the PTBP1 splicing model using RNA-seq. After <i>Ptbp1</i> knockdown, we performed RNA-seq experiments and estimated changes in PSI (Percent of Spliced In) for 573 cassette exons. The graph shows average delta PSI values for exons, grouped by their probabilities to be repressed by PTBP1. The number of exons in the corresponding probability bin is given by n. P-values were calculated from one-tailed Student's t-test. <b>B</b>. A genome browser screenshot of a novel PTBP1-regulated exon: exon 2 of the <i>Kcnq2</i> gene. For whole internal mouse exons, we created custom genome browser tracks to visualize the PTBP1 splicing model and mapped RNA seq reads.</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "validation", "ptbp1-repressed", "exons"], "article_id"=>919587, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.g006", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Large_scale_validation_of_novel_PTBP1_repressed_exons_by_RNA_seq_/919587", "title"=>"Large-scale validation of novel PTBP1-repressed exons by RNA-seq.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368385"], "description"=>"<p>The 50 highest scoring exons predicted to be repressed by PTBP1 based on sequence alone.</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "repressed", "exons", "splicing"], "article_id"=>919588, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.t001", "stats"=>{"downloads"=>7, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_PTBP1_repressed_exons_identified_by_the_splicing_model_/919588", "title"=>"PTBP1 repressed exons identified by the splicing model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368389", "https://ndownloader.figshare.com/files/1368390", "https://ndownloader.figshare.com/files/1368391", "https://ndownloader.figshare.com/files/1368392", "https://ndownloader.figshare.com/files/1368393", "https://ndownloader.figshare.com/files/1368394", "https://ndownloader.figshare.com/files/1368395", "https://ndownloader.figshare.com/files/1368396", "https://ndownloader.figshare.com/files/1368397", "https://ndownloader.figshare.com/files/1368398", "https://ndownloader.figshare.com/files/1368399", "https://ndownloader.figshare.com/files/1368400", "https://ndownloader.figshare.com/files/1368401", "https://ndownloader.figshare.com/files/1368402", "https://ndownloader.figshare.com/files/1368403"], "description"=>"<div><p>The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many <i>in vivo</i> targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (ρ = −0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation.</p></div>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "ptbp1", "binding", "splicing", "targets", "reveals"], "article_id"=>919592, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1003442.s001", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s002", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s003", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s004", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s005", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s006", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s007", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s008", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s009", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s010", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s011", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s012", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s013", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s014", "https://dx.doi.org/10.1371/journal.pcbi.1003442.s015"], "stats"=>{"downloads"=>7, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_De_Novo_Prediction_of_PTBP1_Binding_and_Splicing_Targets_Reveals_Unexpected_Features_of_Its_RNA_Recognition_and_Function/919592", "title"=>"<i>De Novo</i> Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368374"], "description"=>"<p><b>A</b>. Scheme of the PTBP1 binding model. The two-state HMM model was trained on PTBP1 bound RNA sequences (48,604 clusters) from published PTBP1-CLIP experiments. Triplets from these CLIP clusters were predictive of two states, with all of the pyrimidine triplets preferred by State 1. The diagram presents the structure of the PTBP1 HMM (Hidden Markov Model) and its trained transition probabilities. <b>B</b>. The probabilities that triplets are seen states 1 or 2 (emission probabilities) are plotted in black and gray bars, respectively. Asterisks indicate G containing pyrimidine triplets.</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "binding"], "article_id"=>919577, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.g001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_PTBP1_binding_model_/919577", "title"=>"PTBP1 binding model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368375"], "description"=>"<p><b>A</b>. To validate binding scores, thirteen RNAs with various PTBP1 binding scores were transcribed <i>in vitro</i> and subjected to binding assay. Apparent <i>Kd</i>'s (dissociation constant) were highly negatively correlated with PTBP1 binding scores (Pearson correlation = −0.9). <b>B</b>. Four RNA sequences with predicted PTBP1 binding scores (Full data binding data in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003442#pcbi.1003442.s003\" target=\"_blank\">Figure S3</a>). Potential PTBP1 binding sites are underlined and in bold. Experimental binding affinities were assessed by electrophoretic mobility shift of RNA by PTBP1 and compared with prediction scores. Apparent dissociation constants (<i>Kd</i>) were defined as the concentration at which half the protein was bound to RNA.</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "ptbp1", "binding"], "article_id"=>919578, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.g002", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_of_the_PTBP1_binding_model_/919578", "title"=>"Validation of the PTBP1 binding model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368377"], "description"=>"<p><b>A</b>. An RNA map shows enrichment of predicted PTBP1 binding sites near PTBP1-dependent exons. The Y-axis plots average density of predicted PTBP1 binding states within a 24 nt window; the length of overlap between two adjacent windows was 8 nt. <b>B</b>. To assess PTBP1 binding signatures of individual exons, known PTBP1 regulated exons were clustered by their PTBP1 binding score profiles and visualized as heat maps. These heat maps indicate wide variation in the positions of PTBP1 binding sites between individual exons. <b>C</b>. Four sequence features including the PTBP1 binding scores and 3′ splice site strength show statistically significant differences between regulated and control exon groups (one-tailed Student's t-tests).</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "ptbp1-dependent", "alternatively", "spliced"], "article_id"=>919580, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.g003", "stats"=>{"downloads"=>2, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sequence_characteristics_of_PTBP1_dependent_alternatively_spliced_exons_/919580", "title"=>"Sequence characteristics of PTBP1-dependent alternatively spliced exons.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-30 03:56:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1368378"], "description"=>"<p><b>A</b>. The PTBP1 splicing regulation model was trained on known PTBP1-regulated and non-regulated exons and used to predict new PTBP1-dependent exons. Prediction results were compared to changes in exon inclusion (PSI) measured by RT-PCR and RNA-seq. An exon from <i>Ptbp3</i> is presented as a prediction example. From intron and exon sequences, PTBP1 binding scores and 3′ splice site strength were calculated and fed into the regulation model. <b>B</b>. The model predicts exon 2 of <i>Ptbp3</i> as repressed by PTBP1 with high probability (0.89). <i>Ptbp1</i> knockdown in mouse neuroblastoma cells (<i>N2A</i>) confirmed de-repression of the exon (from PSI = 45 to PSI = 70).</p>", "links"=>[], "tags"=>["Biochemistry", "Nucleic acids", "rna", "RNA processing", "Computational biology", "Molecular genetics", "Gene regulation", "gene expression", "Sequence analysis", "genetics", "Gene splicing", "ptbp1", "splicing", "exon"], "article_id"=>919581, "categories"=>["Biological Sciences"], "users"=>["Areum Han", "Peter Stoilov", "Anthony J. Linares", "Yu Zhou", "Xiang-Dong Fu", "Douglas L. Black"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003442.g004", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scheme_of_the_PTBP1_splicing_regulation_model_and_its_application_to_an_exon_in_Ptbp3_/919581", "title"=>"Scheme of the PTBP1 splicing regulation model and its application to an exon in <i>Ptbp3</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-30 03:56:32"}

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Relative Metric

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