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      Chiari 1 malformation and exome sequencing in 51 trios: the emerging role of rare missense variants in chromatin-remodeling genes

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          Abstract

          Type 1 Chiari malformation (C1M) is characterized by cerebellar tonsillar herniation of 3–5 mm or more, the frequency of which is presumably much higher than one in 1000 births, as previously believed. Its etiology remains undefined, although a genetic basis is strongly supported by C1M presence in numerous genetic syndromes associated with different genes. Whole-exome sequencing (WES) in 51 between isolated and syndromic pediatric cases and their relatives was performed after confirmation of the defect by brain magnetic resonance image (MRI). Moreover, in all the cases showing an inherited candidate variant, brain MRI was performed in both parents and not only in the carrier one to investigate whether the defect segregated with the variant. More than half of the variants were Missense and belonged to the same chromatin-remodeling genes whose protein truncation variants are associated with severe neurodevelopmental syndromes. In the remaining cases, variants have been detected in genes with a role in cranial bone sutures, microcephaly, neural tube defects, and RASopathy. This study shows that the frequency of C1M is widely underestimated, in fact many of the variants, in particular those in the chromatin-remodeling genes, were inherited from a parent with C1M, either asymptomatic or with mild symptoms. In addition, C1M is a Mendelian trait, in most cases inherited as dominant. Finally, we demonstrate that modifications of the genes that regulate chromatin architecture can cause localized anatomical alterations, with symptoms of varying degrees.

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          Genetic diagnosis of Mendelian disorders via RNA sequencing

          Across a variety of Mendelian disorders, ∼50–75% of patients do not receive a genetic diagnosis by exome sequencing indicating disease-causing variants in non-coding regions. Although genome sequencing in principle reveals all genetic variants, their sizeable number and poorer annotation make prioritization challenging. Here, we demonstrate the power of transcriptome sequencing to molecularly diagnose 10% (5 of 48) of mitochondriopathy patients and identify candidate genes for the remainder. We find a median of one aberrantly expressed gene, five aberrant splicing events and six mono-allelically expressed rare variants in patient-derived fibroblasts and establish disease-causing roles for each kind. Private exons often arise from cryptic splice sites providing an important clue for variant prioritization. One such event is found in the complex I assembly factor TIMMDC1 establishing a novel disease-associated gene. In conclusion, our study expands the diagnostic tools for detecting non-exonic variants and provides examples of intronic loss-of-function variants with pathological relevance.
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            Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria

            (2017)
            Purpose The 2015 American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG–AMP) guidelines were a major step toward establishing a common framework for variant classification. In practice, however, several aspects of the guidelines lack specificity, are subject to varied interpretations, or fail to capture relevant aspects of clinical molecular genetics. A simple implementation of the guidelines in their current form is insufficient for consistent and comprehensive variant classification. Methods We undertook an iterative process of refining the ACMG–AMP guidelines. We used the guidelines to classify more than 40,000 clinically observed variants, assessed the outcome, and refined the classification criteria to capture exceptions and edge cases. During this process, the criteria evolved through eight major and minor revisions. Results Our implementation: (i) separated ambiguous ACMG–AMP criteria into a set of discrete but related rules with refined weights; (ii) grouped certain criteria to protect against the overcounting of conceptually related evidence; and (iii) replaced the “clinical criteria” style of the guidelines with additive, semiquantitative criteria. Conclusion Sherloc builds on the strong framework of 33 rules established by the ACMG–AMP guidelines and introduces 108 detailed refinements, which support a more consistent and transparent approach to variant classification.
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              Lessons from the cancer genome.

              Systematic studies of the cancer genome have exploded in recent years. These studies have revealed scores of new cancer genes, including many in processes not previously known to be causal targets in cancer. The genes affect cell signaling, chromatin, and epigenomic regulation; RNA splicing; protein homeostasis; metabolism; and lineage maturation. Still, cancer genomics is in its infancy. Much work remains to complete the mutational catalog in primary tumors and across the natural history of cancer, to connect recurrent genomic alterations to altered pathways and acquired cellular vulnerabilities, and to use this information to guide the development and application of therapies. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                aldesia.provenzano@unifi.it
                Journal
                Hum Genet
                Hum Genet
                Human Genetics
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0340-6717
                1432-1203
                18 December 2020
                18 December 2020
                2021
                : 140
                : 4
                : 625-647
                Affiliations
                [1 ]GRID grid.8404.8, ISNI 0000 0004 1757 2304, Medical Genetics Unit, Department of Clinical and Experimental Biomedical Sciences “Mario Serio”, , University of Florence, ; Florence, Italy
                [2 ]Department of Neurosurgery, “A. Meyer” Children Hospital of Florence, Florence, Italy
                [3 ]Medical Genetics Unit, “A. Meyer” Children Hospital of Florence, Florence, Italy
                [4 ]Department of Experimental and Clinical Medicine, Atherothrombotic Diseases Center, University of Florence, Careggi Hospital, Florence, Italy
                [5 ]Department of Radiology, “A. Meyer” Children Hospital of Florence, Florence, Italy
                [6 ]GRID grid.8404.8, ISNI 0000 0004 1757 2304, Department of Information Engineering, , University of Florence, ; Florence, Italy
                [7 ]Medical Genetics Unit, Department of Mother and Child, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, Italy
                [8 ]GRID grid.8982.b, ISNI 0000 0004 1762 5736, Unit of Medical Genetics, Department of Molecular Medicine, , University of Pavia, ; Pavia, Italy
                Author information
                http://orcid.org/0000-0002-4249-8412
                http://orcid.org/0000-0003-0606-8404
                http://orcid.org/0000-0002-8463-8495
                http://orcid.org/0000-0002-9128-6264
                http://orcid.org/0000-0001-8498-3400
                http://orcid.org/0000-0003-4271-0863
                http://orcid.org/0000-0001-9330-1360
                http://orcid.org/0000-0001-7800-8094
                http://orcid.org/0000-0002-2810-7905
                http://orcid.org/0000-0002-9006-9225
                http://orcid.org/0000-0002-5519-2551
                http://orcid.org/0000-0003-4978-6537
                http://orcid.org/0000-0002-7421-0663
                http://orcid.org/0000-0002-7684-3982
                http://orcid.org/0000-0002-8708-9444
                http://orcid.org/0000-0002-4359-0798
                http://orcid.org/0000-0002-1466-4559
                http://orcid.org/0000-0002-3954-326X
                Article
                2231
                10.1007/s00439-020-02231-6
                7981314
                33337535
                e1117ba8-3072-4aac-bb33-76aae16358ff
                © The Author(s) 2020

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 August 2020
                : 20 October 2020
                Funding
                Funded by: Università degli Studi di Firenze
                Categories
                Original Investigation
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2021

                Genetics
                Genetics

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