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      RBP-Maps enables robust generation of splicing regulatory maps

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          Abstract

          Alternative splicing of pre-messenger RNA transcripts enables the generation of multiple protein isoforms from the same gene locus, providing a major source of protein diversity in mammalian genomes. RNA binding proteins (RBPs) bind to RNA to control splice site choice and define which exons are included in the resulting mature RNA transcript. However, depending on where the RBPs bind relative to splice sites, they can activate or repress splice site usage. To explore this position-specific regulation, in vivo binding sites identified by methods such as cross-linking and immunoprecipitation (CLIP) are integrated with alternative splicing events identified by RNA-seq or microarray. Merging these data sets enables the generation of a “splicing map,” where CLIP signal relative to a merged meta-exon provides a simple summary of the position-specific effect of binding on splicing regulation. Here, we provide RBP-Maps, a software tool to simplify generation of these maps and enable researchers to rapidly query regulatory patterns of an RBP of interest. Further, we discuss various alternative approaches to generate such splicing maps, focusing on how decisions in construction (such as the use of peak versus read density, or whole-reads versus only single-nucleotide candidate crosslink positions) can affect the interpretation of these maps using example eCLIP data from the 150 RBPs profiled by the ENCODE consortium.

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          Most cited references25

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          Alternative Isoform Regulation in Human Tissue Transcriptomes

          Through alternative processing of pre-mRNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes based on deep sequencing of cDNA fragments, yielding a digital inventory of gene and mRNA isoform expression. Analysis of mappings of sequence reads to exon-exon junctions indicated that 92-94% of human genes undergo alternative splicing (AS), ∼86% with a minor isoform frequency of 15% or more. Differences in isoform-specific read densities indicated that a majority of AS and of alternative cleavage and polyadenylation (APA) events vary between tissues, while variation between individuals was ∼2- to 3-fold less common. Extreme or ‘switch-like’ regulation of splicing between tissues was associated with increased sequence conservation in regulatory regions and with generation of full-length open reading frames. Patterns of AS and APA were strongly correlated across tissues, suggesting coordinated regulation of these processes, and sequence conservation of a subset of known regulatory motifs in both alternative introns and 3′ UTRs suggested common involvement of specific factors in tissue-level regulation of both splicing and polyadenylation.
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            rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

            Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.
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              HITS-CLIP yields genome-wide insights into brain alternative RNA processing

              Summary Protein-RNA interactions play critical roles in all aspects of gene expression. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova2 revealed extremely reproducible RNA binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3′ UTRs, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.
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                Author and article information

                Journal
                RNA
                RNA
                RNA
                RNA
                Cold Spring Harbor Laboratory Press
                1355-8382
                1469-9001
                February 2019
                February 2019
                : 25
                : 2
                : 193-204
                Affiliations
                [1 ]Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, California 92093, USA
                [2 ]Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA
                [3 ]Bioinformatics and Systems Biology Graduate Program, University of California at San Diego, La Jolla, California 92093, USA
                [4 ]Department of Genetics and Genome Sciences, Institute for Systems Genomics, UConn Health, Farmington, Connecticut 06030, USA
                Author notes
                Article
                9509184 RA
                10.1261/rna.069237.118
                6348990
                30413564
                b63f6d15-a41a-47d5-b099-d8552ffa27d4
                © 2019 Yee et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society

                This article, published in RNA, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 October 2018
                : 1 November 2018
                Page count
                Pages: 12
                Funding
                Funded by: National Human Genome Research Institute ENCODE Project , open-funder-registry 10.13039/100000051;
                Award ID: HG007005
                Award ID: HG009889
                Funded by: National Science Foundation , open-funder-registry 10.13039/100000001;
                Funded by: Damon Runyon Cancer Research Foundation , open-funder-registry 10.13039/100001021;
                Award ID: DRG-2172-13
                Award ID: K99
                Funded by: National Human Genome Research Institute , open-funder-registry 10.13039/100000051;
                Award ID: HG009530
                Funded by: National Institutes of Health , open-funder-registry 10.13039/100000002;
                Award ID: HG004659
                Award ID: NS075499
                Funded by: National Institute of Neurological Disorders and Stroke , open-funder-registry 10.13039/100000065;
                Categories
                Bioinformatics

                alternative splicing,eclip,splicing map,rna binding protein

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