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      Translation-dependent and -independent mRNA decay occur through mutually exclusive pathways defined by ribosome density during T cell activation

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          Abstract

          mRNA translation and decay are tightly interconnected processes both in the context of mRNA quality-control pathways and for the degradation of functional mRNAs. Cotranslational mRNA degradation through codon usage, ribosome collisions, and the recruitment of specific proteins to ribosomes is an important determinant of mRNA turnover. However, the extent to which translation-dependent mRNA decay (TDD) and translation-independent mRNA decay (TID) pathways participate in the degradation of mRNAs has not been studied yet. Here we describe a comprehensive analysis of basal and signal-induced TDD and TID in mouse primary CD4 + T cells. Our results indicate that most cellular transcripts are decayed to some extent in a translation-dependent manner. Our analysis further identifies the length of untranslated regions, the density of ribosomes, and GC3 content as important determinants of TDD magnitude. Consistently, all transcripts that undergo changes in ribosome density within their coding sequence upon T cell activation display a corresponding change in their TDD level. Moreover, we reveal a dynamic modulation in the relationship between GC3 content and TDD upon T cell activation, with a reversal in the impact of GC3- and AU3-rich codons. Altogether, our data show a strong and dynamic interconnection between mRNA translation and decay in mammalian primary cells.

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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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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

              DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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                Author and article information

                Journal
                Genome Res
                Genome Res
                genome
                GENOME
                Genome Research
                Cold Spring Harbor Laboratory Press
                1088-9051
                1549-5469
                March 2024
                March 2024
                : 34
                : 3
                : 394-409
                Affiliations
                [1 ]RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA;
                [2 ]Laboratory of Biology and Modeling of the Cell (LBMC), Université de Lyon, ENS de Lyon, Université Claude Bernard, CNRS UMR 5239, Inserm U1293, 69007 Lyon, France;
                [3 ]ADLIN Science, 9100 Evry-Courcouronnes, France;
                [4 ]Centre International de Recherche en Infectiologie Université de Lyon, Inserm U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, F-69007 Lyon, France
                Author notes
                [5]

                These authors contributed equally to this work.

                [6]

                Present address: Moderna, Inc., Cambridge, MA 02139, USA

                Author information
                http://orcid.org/0000-0001-6314-7809
                http://orcid.org/0000-0002-8018-8765
                http://orcid.org/0000-0002-1839-1789
                http://orcid.org/0000-0003-4200-0079
                http://orcid.org/0000-0002-0774-7719
                http://orcid.org/0000-0002-3757-0002
                http://orcid.org/0000-0002-4905-8727
                http://orcid.org/0000-0002-9789-5837
                Article
                9509184
                10.1101/gr.277863.123
                11067875
                38508694
                8b88b696-8608-4fee-a308-587d9c8cb7a0
                © 2024 Mercier et al.; Published by Cold Spring Harbor Laboratory Press

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

                History
                : 7 March 2023
                : 9 March 2024
                Page count
                Pages: 16
                Funding
                Funded by: European Research Council , doi 10.13039/100010663;
                Award ID: ERC-StG-LS6-805500
                Categories
                Research

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