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      Somatic mutation rates scale with lifespan across mammals

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      1 , , 1 , 1 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 3 , 3 , 3 , 4 , 3 , 3 , 3 , 3 , 5 , 5 , 6 , 7 , 6 , 7 , 6 , 7 , 8 , 9 , 10 , 10 , 10 , 11 , 10 , 12 , 13 , 14 , 1 , 10 , 1 , 1 ,
      Nature
      Nature Publishing Group UK
      Comparative genomics, Cancer genomics, Genomics, Ageing

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          Abstract

          The rates and patterns of somatic mutation in normal tissues are largely unknown outside of humans 17 . Comparative analyses can shed light on the diversity of mutagenesis across species, and on long-standing hypotheses about the evolution of somatic mutation rates and their role in cancer and ageing. Here we performed whole-genome sequencing of 208 intestinal crypts from 56 individuals to study the landscape of somatic mutation across 16 mammalian species. We found that somatic mutagenesis was dominated by seemingly endogenous mutational processes in all species, including 5-methylcytosine deamination and oxidative damage. With some differences, mutational signatures in other species resembled those described in humans 8 , although the relative contribution of each signature varied across species. Notably, the somatic mutation rate per year varied greatly across species and exhibited a strong inverse relationship with species lifespan, with no other life-history trait studied showing a comparable association. Despite widely different life histories among the species we examined—including variation of around 30-fold in lifespan and around 40,000-fold in body mass—the somatic mutation burden at the end of lifespan varied only by a factor of around 3. These data unveil common mutational processes across mammals, and suggest that somatic mutation rates are evolutionarily constrained and may be a contributing factor in ageing.

          Abstract

          Whole-genome sequencing is used to analyse the landscape of somatic mutation in intestinal crypts from 16 mammalian species, revealing that rates of somatic mutation inversely scale with the lifespan of the animal across species.

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          Most cited references73

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          BEDTools: a flexible suite of utilities for comparing genomic features

          Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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            The Hallmarks of Aging

            Aging is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death. This deterioration is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular disorders, and neurodegenerative diseases. Aging research has experienced an unprecedented advance over recent years, particularly with the discovery that the rate of aging is controlled, at least to some extent, by genetic pathways and biochemical processes conserved in evolution. This Review enumerates nine tentative hallmarks that represent common denominators of aging in different organisms, with special emphasis on mammalian aging. These hallmarks are: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. A major challenge is to dissect the interconnectedness between the candidate hallmarks and their relative contributions to aging, with the final goal of identifying pharmaceutical targets to improve human health during aging, with minimal side effects. Copyright © 2013 Elsevier Inc. All rights reserved.
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              The repertoire of mutational signatures in human cancer

              Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature 1 . Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses 3–15 , enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated—but distinct—DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.
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                Author and article information

                Contributors
                ac36@sanger.ac.uk
                im3@sanger.ac.uk
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                13 April 2022
                13 April 2022
                2022
                : 604
                : 7906
                : 517-524
                Affiliations
                [1 ]Cancer, Ageing and Somatic Mutation (CASM), Wellcome Sanger Institute, Hinxton, UK
                [2 ]Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
                [3 ]Wildlife Health Services, Zoological Society of London, London, UK
                [4 ]The Natural History Museum, London, UK
                [5 ]Institute of Zoology, Zoological Society of London, London, UK
                [6 ]Division of Experimental Hematology, German Cancer Research Center (DKFZ), Heidelberg, Germany
                [7 ]Heidelberg Institute for Stem Cell Technology and Experimental Medicine GmbH (HI-STEM), Heidelberg, Germany
                [8 ]Wellcome Trust–Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
                [9 ]Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
                [10 ]Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
                [11 ]Bristol Veterinary School, Faculty of Health Sciences, University of Bristol, Langford, UK
                [12 ]Department of Pathology, Faculty of Veterinary Medicine, Universitatea de Stiinte Agricole si Medicina Veterinara, Cluj-Napoca, Romania
                [13 ]Department of Pharmacology, University of Cambridge, Cambridge, UK
                [14 ]European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
                Author information
                http://orcid.org/0000-0002-7857-4771
                http://orcid.org/0000-0002-6201-1587
                http://orcid.org/0000-0002-5826-3554
                http://orcid.org/0000-0003-3592-1005
                http://orcid.org/0000-0002-7638-2899
                http://orcid.org/0000-0002-0407-0386
                http://orcid.org/0000-0001-5803-1035
                http://orcid.org/0000-0002-9621-2192
                http://orcid.org/0000-0002-3567-254X
                http://orcid.org/0000-0003-0219-8818
                http://orcid.org/0000-0002-2699-1979
                http://orcid.org/0000-0001-6709-963X
                http://orcid.org/0000-0002-3921-0510
                http://orcid.org/0000-0001-7462-8907
                http://orcid.org/0000-0001-6035-153X
                http://orcid.org/0000-0003-1122-4416
                Article
                4618
                10.1038/s41586-022-04618-z
                9021023
                35418684
                3407629a-b951-4a18-85b2-f2a9bc83bef8
                © The Author(s) 2022

                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
                : 17 August 2021
                : 7 March 2022
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

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                comparative genomics,cancer genomics,genomics,ageing
                Uncategorized
                comparative genomics, cancer genomics, genomics, ageing

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