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      p53-mediated redox control promotes liver regeneration and maintains liver function in response to CCl 4

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          Abstract

          The p53 transcription factor coordinates wide-ranging responses to stress that contribute to its function as a tumour suppressor. The responses to p53 induction are complex and range from mediating the elimination of stressed or damaged cells to promoting survival and repair. These activities of p53 can modulate tumour development but may also play a role in pathological responses to stress such as tissue damage and repair. Using a p53 reporter mouse, we have previously detected strong induction of p53 activity in the liver of mice treated with the hepatotoxin carbon tetrachloride (CCl 4). Here, we show that p53 functions to support repair and recovery from CCl 4-mediated liver damage, control reactive oxygen species (ROS) and limit the development of hepatocellular carcinoma (HCC), in part through the activation of a detoxification cytochrome P450, CYP2A5 (CYP2A6 in humans). Our work demonstrates an important role for p53-mediated redox control in facilitating the hepatic regenerative response after damage and identifies CYP2A5/CYP2A6 as a mediator of this pathway with potential prognostic utility in human HCC.

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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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            Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

            The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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                Author and article information

                Contributors
                tim.humpton@crick.ac.uk
                Karen.vousden@crick.ac.uk
                Journal
                Cell Death Differ
                Cell Death Differ
                Cell Death and Differentiation
                Nature Publishing Group UK (London )
                1350-9047
                1476-5403
                9 October 2021
                9 October 2021
                March 2022
                : 29
                : 3
                : 514-526
                Affiliations
                [1 ]GRID grid.451388.3, ISNI 0000 0004 1795 1830, The Francis Crick Institute, ; London, NW1 1AT UK
                [2 ]GRID grid.23636.32, ISNI 0000 0000 8821 5196, Cancer Research UK Beatson Institute, ; Glasgow, G61 1BD UK
                [3 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, Institute of Cancer Sciences, , University of Glasgow, ; Glasgow, G61 1QH UK
                [4 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, MRC Centre for Inflammation Research, The Queen’s Medical Research Institute, , University of Edinburgh, ; Edinburgh, EH16 4TJ UK
                Author information
                http://orcid.org/0000-0002-8030-9539
                http://orcid.org/0000-0003-2779-2565
                http://orcid.org/0000-0002-8085-2160
                http://orcid.org/0000-0002-7365-1766
                Article
                871
                10.1038/s41418-021-00871-3
                8901761
                34628485
                a76511e8-cc0e-4ecb-8bd3-76bcdbdb78db
                © 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
                : 27 November 2020
                : 26 August 2021
                : 7 September 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000289, Cancer Research UK (CRUK);
                Award ID: C596/A26855
                Award ID: FC001557
                Award ID: C596/A17196
                Award ID: C596/A17196
                Award ID: C596/A17196
                Award ID: A26813
                Award ID: C596/A17196
                Award ID: C596/A26855
                Award ID: FC001557
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100009187, RCUK | MRC | Medical Research Foundation;
                Award ID: FC001557
                Award ID: FC001557
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100004440, Wellcome Trust (Wellcome);
                Award ID: FC001557
                Award ID: WT107492Z
                Award ID: WT107492Z
                Award ID: WT107492Z
                Award ID: FC001557
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/N017005/2
                Award Recipient :
                Categories
                Article
                Custom metadata
                © ADMC Associazione Differenziamento e Morte Cellulare 2022

                Cell biology
                tumour-suppressor proteins,physiology
                Cell biology
                tumour-suppressor proteins, physiology

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