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      Discovery of an unusually high number of de novo mutations in sperm of older men using duplex sequencing

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          Abstract

          De novo mutations (DNMs) are important players in heritable diseases and evolution. Of particular interest are highly recurrent DNMs associated with congenital disorders that have been described as selfish mutations expanding in the male germline, thus becoming more frequent with age. Here, we have adapted duplex sequencing (DS), an ultradeep sequencing method that renders sequence information on both DNA strands; thus, one mutation can be reliably called in millions of sequenced bases. With DS, we examined ∼4.5 kb of the FGFR3 coding region in sperm DNA from older and younger donors. We identified sites with variant allele frequencies (VAFs) of 10 −4 to 10 −5, with an overall mutation frequency of the region of ∼6 × 10 −7. Some of the substitutions are recurrent and are found at a higher VAF in older donors than in younger ones or are found exclusively in older donors. Also, older donors harbor more mutations associated with congenital disorders. Other mutations are present in both age groups, suggesting that these might result from a different mechanism (e.g., postzygotic mosaicism). We also observe that independent of age, the frequency and deleteriousness of the mutational spectra are more similar to COSMIC than to gnomAD variants. Our approach is an important strategy to identify mutations that could be associated with a gain of function of the receptor tyrosine kinase activity, with unexplored consequences in a society with delayed fatherhood.

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          Most cited references68

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          The mutational constraint spectrum quantified from variation in 141,456 humans

          Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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            The Ensembl Variant Effect Predictor

            The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
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              COSMIC: the Catalogue Of Somatic Mutations In Cancer

              Abstract COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC’s deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.
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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 2022
                March 2022
                : 32
                : 3
                : 499-511
                Affiliations
                [1 ]Institute of Biophysics, Johannes Kepler University, Linz, Austria 4020;
                [2 ]Department of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Linz, Austria 4020;
                [3 ]Center for Medical Research, Faculty of Medicine, Johannes Kepler University, Linz, Austria 4020
                Author notes

                Present addresses: 4Department of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University, Linz, Austria 4020; 5Department of Biosciences and Medical Biology, University of Salzburg, Salzburg, Austria 5020

                Corresponding author: irene.tiemann@ 123456jku.at
                Author information
                http://orcid.org/0000-0001-8436-9304
                http://orcid.org/0000-0001-8367-1560
                http://orcid.org/0000-0003-3793-9049
                http://orcid.org/0000-0002-9000-2290
                http://orcid.org/0000-0002-4522-2999
                http://orcid.org/0000-0002-6917-1364
                http://orcid.org/0000-0001-7402-3369
                http://orcid.org/0000-0002-8583-6071
                http://orcid.org/0000-0002-0635-2598
                http://orcid.org/0000-0002-3621-7020
                Article
                9509184
                10.1101/gr.275695.121
                8896467
                35210354
                ab19b242-7cf9-42b7-acb1-37a5c53cf28c
                © 2022 Salazar 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
                : 26 April 2021
                : 14 January 2022
                Page count
                Pages: 13
                Funding
                Funded by: Austrian Science Fund , doi 10.13039/501100002428;
                Funded by: FWF
                Funded by: Austrian Science Fund , doi 10.13039/501100002428;
                Award ID: FWFP30867000
                Funded by: FWF Doctoral College “NanoCell”
                Award ID: FWFW1250
                Funded by: European Regional Development Fund , doi 10.13039/501100008530;
                Award ID: REGGEN ATCZ207
                Funded by: Linz Institute of Technology
                Award ID: LIT213201001
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