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      TSSC4 is a component of U5 snRNP that promotes tri-snRNP formation

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          Abstract

          U5 snRNP is a complex particle essential for RNA splicing. U5 snRNPs undergo intricate biogenesis that ensures that only a fully mature particle assembles into a splicing competent U4/U6•U5 tri-snRNP and enters the splicing reaction. During splicing, U5 snRNP is substantially rearranged and leaves as a U5/PRPF19 post-splicing particle, which requires re-generation before the next round of splicing. Here, we show that a previously uncharacterized protein TSSC4 is a component of U5 snRNP that promotes tri-snRNP formation. We provide evidence that TSSC4 associates with U5 snRNP chaperones, U5 snRNP and the U5/PRPF19 particle. Specifically, TSSC4 interacts with U5-specific proteins PRPF8, EFTUD2 and SNRNP200. We also identified TSSC4 domains critical for the interaction with U5 snRNP and the PRPF19 complex, as well as for TSSC4 function in tri-snRNP assembly. TSSC4 emerges as a specific chaperone that acts in U5 snRNP de novo biogenesis as well as post-splicing recycling.

          Abstract

          The correct assembly and recycling of the multicomponent spliceosome remains largely elusive. Here, the authors show that a previously uncharacterized protein TSSC4 associates with de novo formed spliceosomal U5 snRNP as well as with a post-splicing U5-PRPF19 particle, and that TSSC4 is important for assembly of the splicing competent tri-snRNP.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            The PRIDE database and related tools and resources in 2019: improving support for quantification data

            Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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              T-Coffee: A novel method for fast and accurate multiple sequence alignment.

              We describe a new method (T-Coffee) for multiple sequence alignment that provides a dramatic improvement in accuracy with a modest sacrifice in speed as compared to the most commonly used alternatives. The method is broadly based on the popular progressive approach to multiple alignment but avoids the most serious pitfalls caused by the greedy nature of this algorithm. With T-Coffee we pre-process a data set of all pair-wise alignments between the sequences. This provides us with a library of alignment information that can be used to guide the progressive alignment. Intermediate alignments are then based not only on the sequences to be aligned next but also on how all of the sequences align with each other. This alignment information can be derived from heterogeneous sources such as a mixture of alignment programs and/or structure superposition. Here, we illustrate the power of the approach by using a combination of local and global pair-wise alignments to generate the library. The resulting alignments are significantly more reliable, as determined by comparison with a set of 141 test cases, than any of the popular alternatives that we tried. The improvement, especially clear with the more difficult test cases, is always visible, regardless of the phylogenetic spread of the sequences in the tests. Copyright 2000 Academic Press.
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                Author and article information

                Contributors
                stanek@img.cas.cz
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                15 June 2021
                15 June 2021
                2021
                : 12
                : 3646
                Affiliations
                [1 ]GRID grid.418827.0, ISNI 0000 0004 0620 870X, Institute of Molecular Genetics, Czech Academy of Sciences, ; Prague, Czech Republic
                [2 ]GRID grid.461890.2, ISNI 0000 0004 0383 2080, Institut de Génomique Fonctionnelle, University of Montpellier, CNRS, INSERM, ; Montpellier, France
                [3 ]GRID grid.429192.5, ISNI 0000 0004 0599 0285, Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS, ; Montpellier, France
                [4 ]Equipe labélisée Ligue Nationale Contre le Cancer, Montpellier, France
                [5 ]GRID grid.121334.6, ISNI 0000 0001 2097 0141, Present Address: Institut de Génétique Humaine, ; Montpellier, France
                Author information
                http://orcid.org/0000-0001-5828-3363
                http://orcid.org/0000-0002-8263-6277
                http://orcid.org/0000-0001-9484-9002
                http://orcid.org/0000-0001-5724-7037
                http://orcid.org/0000-0002-9642-7994
                http://orcid.org/0000-0003-2459-9700
                http://orcid.org/0000-0002-5865-175X
                Article
                23934
                10.1038/s41467-021-23934-y
                8206348
                34131137
                4ca706e6-32d7-4b64-8c1f-a24ba9f9fc1c
                © The Author(s) 2021

                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
                : 3 November 2020
                : 19 May 2021
                Categories
                Article
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                © The Author(s) 2021

                Uncategorized
                rna quality control,rna splicing
                Uncategorized
                rna quality control, rna splicing

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