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      The role of the 5’ sensing function of ribonuclease E in cyanobacteria

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          ABSTRACT

          RNA degradation is critical for synchronising gene expression with changing conditions in prokaryotic and eukaryotic organisms. In bacteria, the preference of the central ribonucleases RNase E, RNase J and RNase Y for 5’-monophosphorylated RNAs is considered important for RNA degradation. For RNase E, the underlying mechanism is termed 5’ sensing, contrasting to the alternative ‘direct entry’ mode, which is independent of monophosphorylated 5’ ends. Cyanobacteria, such as Synechocystis sp. PCC 6803 ( Synechocystis), encode RNase E and RNase J homologues. Here, we constructed a Synechocystis strain lacking the 5’ sensing function of RNase E and mapped on a transcriptome-wide level 283 5’-sensing-dependent cleavage sites. These included so far unknown targets such as mRNAs encoding proteins related to energy metabolism and carbon fixation. The 5’ sensing function of cyanobacterial RNase E is important for the maturation of rRNA and several tRNAs, including tRNA Glu UUC. This tRNA activates glutamate for tetrapyrrole biosynthesis in plant chloroplasts and in most prokaryotes. Furthermore, we found that increased RNase activities lead to a higher copy number of the major Synechocystis plasmids pSYSA and pSYSM. These results provide a first step towards understanding the importance of the different target mechanisms of RNase E outside Escherichia coli.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

              Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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                Author and article information

                Journal
                RNA Biol
                RNA Biol
                RNA Biology
                Taylor & Francis
                1547-6286
                1555-8584
                12 March 2024
                2024
                12 March 2024
                : 21
                : 1
                : 1-18
                Affiliations
                [a ]Molecular Genetics of Prokaryotes, Institute of Biology III, University of Freiburg; , Freiburg, Germany
                [b ]School of Engineering Sciences in Chemistry, Biotechnology and Health, Science for Life Laboratory, KTH - Royal Institute of Technology; , Stockholm, Sweden
                [c ]Genetics and Experimental Bioinformatics, Faculty of Biology, University of Freiburg; , Freiburg, Germany
                [d ]Bioinformatics Group, Department of Computer Science, University of Freiburg; , Freiburg, Germany
                [e ]Signalling Research Centres BIOSS and CIBSS, University of Freiburg; , Freiburg, Germany
                Author notes
                CONTACT Annegret Wilde annegret.wilde@ 123456biologie.uni-freiburg.de Molecular Genetics of Prokaryotes, Institute of Biology III, University of Freiburg; , Freiburg 79104, Germany
                Author information
                https://orcid.org/0000-0002-9658-2695
                https://orcid.org/0000-0002-4344-4571
                https://orcid.org/0000-0002-9643-4553
                https://orcid.org/0000-0002-3651-5685
                https://orcid.org/0000-0001-8231-3323
                https://orcid.org/0000-0002-4708-6273
                https://orcid.org/0000-0002-5340-3423
                https://orcid.org/0000-0003-0935-8415
                Article
                2328438
                10.1080/15476286.2024.2328438
                10939160
                38469716
                9c5153bc-9b03-4c78-8394-b61534859751
                © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 6, Tables: 3, References: 109, Pages: 18
                Categories
                Research Article
                Research Paper

                Molecular biology
                rna degradation,rnase e,cyanobacteria,synechocystis,5’ sensing,rna-seq,trna maturation
                Molecular biology
                rna degradation, rnase e, cyanobacteria, synechocystis, 5’ sensing, rna-seq, trna maturation

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