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      CAPRI enables comparison of evolutionarily conserved RNA interacting regions

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          Abstract

          RNA-protein complexes play essential regulatory roles at nearly all levels of gene expression. Using in vivo crosslinking and RNA capture, we report a comprehensive RNA-protein interactome in a metazoan at four levels of resolution: single amino acids, domains, proteins and multisubunit complexes. We devise CAPRI, a method to map RNA-binding domains (RBDs) by simultaneous identification of RNA interacting crosslinked peptides and peptides adjacent to such crosslinked sites. CAPRI identifies more than 3000 RNA proximal peptides in Drosophila and human proteins with more than 45% of them forming new interaction interfaces. The comparison of orthologous proteins enables the identification of evolutionary conserved RBDs in globular domains and intrinsically disordered regions (IDRs). By comparing the sequences of IDRs through evolution, we classify them based on the type of motif, accumulation of tandem repeats, conservation of amino acid composition and high sequence divergence.

          Abstract

          Comprehensive characterisation of RNA-protein interactions requires different levels of resolution. Here, the authors present an integrated mass spectrometry-based approach that allows them to define the Drosophila RNA-protein interactome from the level of multisubunit complexes down to the RNA-binding amino acid.

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          Most cited references36

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          CLIP identifies Nova-regulated RNA networks in the brain.

          Nova proteins are neuron-specific antigens targeted in paraneoplastic opsoclonus myoclonus ataxia (POMA), an autoimmune neurologic disease characterized by abnormal motor inhibition. Nova proteins regulate neuronal pre-messenger RNA splicing by directly binding to RNA. To identify Nova RNA targets, we developed a method to purify protein-RNA complexes from mouse brain with the use of ultraviolet cross-linking and immunoprecipitation (CLIP).Thirty-four transcripts were identified multiple times by Nova CLIP.Three-quarters of these encode proteins that function at the neuronal synapse, and one-third are involved in neuronal inhibition.Splicing targets confirmed in Nova-/- mice include c-Jun N-terminal kinase 2, neogenin, and gephyrin; the latter encodes a protein that clusters inhibitory gamma-aminobutyric acid and glycine receptors, two previously identified Nova splicing targets.Thus, CLIP reveals that Nova coordinately regulates a biologically coherent set of RNAs encoding multiple components of the inhibitory synapse, an observation that may relate to the cause of abnormal motor inhibition in POMA.
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            PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry.

            A number of different approaches have been described to identify proteins from tandem mass spectrometry (MS/MS) data. The most common approaches rely on the available databases to match experimental MS/MS data. These methods suffer from several drawbacks and cannot be used for the identification of proteins from unknown genomes. In this communication, we describe a new de novo sequencing software package, PEAKS, to extract amino acid sequence information without the use of databases. PEAKS uses a new model and a new algorithm to efficiently compute the best peptide sequences whose fragment ions can best interpret the peaks in the MS/MS spectrum. The output of the software gives amino acid sequences with confidence scores for the entire sequences, as well as an additional novel positional scoring scheme for portions of the sequences. The performance of PEAKS is compared with Lutefisk, a well-known de novo sequencing software, using quadrupole-time-of-flight (Q-TOF) data obtained for several tryptic peptides from standard proteins. Copyright 2003 John Wiley & Sons, Ltd.
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              Cell lines derived from late embryonic stages of Drosophila melanogaster.

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                Author and article information

                Contributors
                mittler@ie-freiburg.mpg.de
                akhtar@ie-freiburg.mpg.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                18 June 2019
                18 June 2019
                2019
                : 10
                : 2682
                Affiliations
                ISNI 0000 0004 0491 4256, GRID grid.429509.3, Max Planck Institute of Immunobiology and Epigenetics, ; 79108 Freiburg im Breisgau, Germany
                Author information
                http://orcid.org/0000-0002-9812-6036
                http://orcid.org/0000-0002-9142-417X
                http://orcid.org/0000-0003-3761-4535
                http://orcid.org/0000-0003-3702-0868
                http://orcid.org/0000-0001-8973-6193
                Article
                10585
                10.1038/s41467-019-10585-3
                6581911
                31213602
                e4cbccbb-6815-456a-88d6-08c08a357d05
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 June 2018
                : 21 May 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: CRC992
                Award ID: CRC1140
                Award ID: CRC746
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                rna-binding proteins,rna,proteomics
                Uncategorized
                rna-binding proteins, rna, proteomics

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