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      Revealing the Arabidopsis AtGRP7 mRNA binding proteome by specific enhanced RNA interactome capture

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          Abstract

          Background

          The interaction of proteins with RNA in the cell is crucial to orchestrate all steps of RNA processing. RNA interactome capture (RIC) techniques have been implemented to catalogue RNA- binding proteins in the cell. In RIC, RNA-protein complexes are stabilized by UV crosslinking in vivo. Polyadenylated RNAs and associated proteins are pulled down from cell lysates using oligo(dT) beads and the RNA-binding proteome is identified by quantitative mass spectrometry. However, insights into the RNA-binding proteome of a single RNA that would yield mechanistic information on how RNA expression patterns are orchestrated, are scarce.

          Results

          Here, we explored RIC in Arabidopsis to identify proteins interacting with a single mRNA, using the circadian clock-regulated Arabidopsis thaliana GLYCINE-RICH RNA-BINDING PROTEIN 7 ( AtGRP7) transcript, one of the most abundant transcripts in Arabidopsis, as a showcase. Seedlings were treated with UV light to covalently crosslink RNA and proteins. The AtGRP7 transcript was captured from cell lysates with antisense oligonucleotides directed against the 5’untranslated region (UTR). The efficiency of RNA capture was greatly improved by using locked nucleic acid (LNA)/DNA oligonucleotides, as done in the enhanced RIC protocol. Furthermore, performing a tandem capture with two rounds of pulldown with the 5’UTR oligonucleotide increased the yield. In total, we identified 356 proteins enriched relative to a pulldown from atgrp7 mutant plants. These were benchmarked against proteins pulled down from nuclear lysates by AtGRP7 in vitro transcripts immobilized on beads. Among the proteins validated by in vitro interaction we found the family of Acetylation Lowers Binding Affinity (ALBA) proteins. Interaction of ALBA4 with the AtGRP7 RNA was independently validated via individual-nucleotide resolution crosslinking and immunoprecipitation (iCLIP). The expression of the AtGRP7 transcript in an alba loss-of-function mutant was slightly changed compared to wild-type, demonstrating the functional relevance of the interaction.

          Conclusion

          We adapted specific RNA interactome capture with LNA/DNA oligonucleotides for use in plants using AtGRP7 as a showcase. We anticipate that with further optimization and up scaling the protocol should be applicable for less abundant transcripts.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12870-024-05249-4.

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            A Revised Medium for Rapid Growth and Bio Assays with Tobacco Tissue Cultures

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              The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences

              The PRoteomics IDEntifications (PRIDE) database ( https://www.ebi.ac.uk/pride/ ) is the world's largest data repository of mass spectrometry-based proteomics data. PRIDE is one of the founding members of the global ProteomeXchange (PX) consortium and an ELIXIR core data resource. 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 2019. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 500 datasets per month during 2021. In addition to continuous improvements in PRIDE Archive data pipelines and infrastructure, the PRIDE Spectra Archive has been developed to provide direct access to the submitted mass spectra using Universal Spectrum Identifiers. As a key point, the file format MAGE-TAB for proteomics has been developed to enable the improvement of sample metadata annotation. Additionally, the resource PRIDE Peptidome provides access to aggregated peptide/protein evidences across PRIDE Archive. Furthermore, we will describe how PRIDE has increased its efforts to reuse and disseminate high-quality proteomics data into other added-value resources such as UniProt, Ensembl and Expression Atlas.
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                Author and article information

                Contributors
                marlene.reichel@bio.ku.dk
                dorothee.staiger@uni-bielefeld.de
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                14 June 2024
                14 June 2024
                2024
                : 24
                : 552
                Affiliations
                [1 ]RNA Biology and Molecular Physiology, Faculty of Biology, Bielefeld University, ( https://ror.org/02hpadn98) 33615 Bielefeld, Germany
                [2 ]Department of Biology, University of Copenhagen, ( https://ror.org/035b05819) København N, 2200 Denmark
                [3 ]GRID grid.4709.a, ISNI 0000 0004 0495 846X, Proteomics Core Facility, , EMBL, ; 69117 Heidelberg, Germany
                [4 ]Institute of Molecular Biology (IMB), ( https://ror.org/05kxtq558) Ackermannweg 4, 55128 Mainz, Germany
                Article
                5249
                10.1186/s12870-024-05249-4
                11177498
                38877390
                e8aafa47-9081-4e38-baf0-a9e8c9a53e9f
                © The Author(s) 2024

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 14 March 2024
                : 5 June 2024
                Funding
                Funded by: Universität Bielefeld (3146)
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Plant science & Botany
                enhanced rna interactome capture,arabidopsis,lna oligonucleotides,iclip
                Plant science & Botany
                enhanced rna interactome capture, arabidopsis, lna oligonucleotides, iclip

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