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      The variability of SMCHD1 gene in FSHD patients: evidence of new mutations

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          Abstract

          In this study, we investigated the sequence of ( Structural Maintenance of Chromosomes flexible Hinge Domain containing 1) SMCHD1 gene in a cohort of clinically defined FSHD (facioscapulohumeral muscular dystrophy) patients in order to assess the distribution of SMCHD1 variants, considering the D4Z4 fragment size in terms of repeated units (RUs; short fragment: 1–7 RU, borderline: 8-10RU and normal fragment: >11RU). The analysis of SMCHD1 revealed the presence of 82 variants scattered throughout the introns, exons and 3’untranslated region (3′UTR) of the gene. Among them, 64 were classified as benign polymorphisms and 6 as VUS (variants of uncertain significance). Interestingly, seven pathogenic/likely pathogenic variants were identified in patients carrying a borderline or normal D4Z4 fragment size, namely c.182_183dupGT (p.Q62Vfs *48), c.2129dupC (p.A711Cfs *11), c.3469G>T (p.G1157 *), c.5150_5151delAA (p.K1717Rfs *16) and c.1131+2_1131+5delTAAG, c.3010A>T (p.K1004 *), c.853G>C (p.G285R). All of them were predicted to disrupt the structure and conformation of SMCHD1, resulting in the loss of GHKL-ATPase and SMC hinge essential domains. These results are consistent with the FSHD symptomatology and the Clinical Severity Score (CSS) of patients. In addition, five variants (c. *1376A>C, rs7238459; c. *1579G>A, rs559994; c. *1397A>G, rs150573037; c. *1631C>T, rs193227855; c. *1889G>C, rs149259359) were identified in the 3′UTR region of SMCHD1, suggesting a possible miRNA-dependent regulatory effect on FSHD-related pathways. The present study highlights the clinical utility of next-generation sequencing (NGS) platforms for the molecular diagnosis of FSHD and the importance of integrating molecular findings and clinical data in order to improve the accuracy of genotype–phenotype correlations.

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          UniProt: a worldwide hub of protein knowledge

          (2018)
          Abstract The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of these proteins. These annotations are supplemented by annotations provided by rule based automated systems, and those imported from other resources. In this article we describe significant updates that we have made over the last 2 years to the resource. We have greatly expanded the number of Reference Proteomes that we provide and in particular we have focussed on improving the number of viral Reference Proteomes. The UniProt website has been augmented with new data visualizations for the subcellular localization of proteins as well as their structure and interactions. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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            SMART: recent updates, new developments and status in 2015

            SMART (Simple Modular Architecture Research Tool) is a web resource (http://smart.embl.de/) providing simple identification and extensive annotation of protein domains and the exploration of protein domain architectures. In the current version, SMART contains manually curated models for more than 1200 protein domains, with ∼200 new models since our last update article. The underlying protein databases were synchronized with UniProt, Ensembl and STRING, bringing the total number of annotated domains and other protein features above 100 million. SMART's ‘Genomic’ mode, which annotates proteins from completely sequenced genomes was greatly expanded and now includes 2031 species, compared to 1133 in the previous release. SMART analysis results pages have been completely redesigned and include links to several new information sources. A new, vector-based display engine has been developed for protein schematics in SMART, which can also be exported as high-resolution bitmap images for easy inclusion into other documents. Taxonomic tree displays in SMART have been significantly improved, and can be easily navigated using the integrated search engine.
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              Can Predicted Protein 3D Structures Provide Reliable Insights into whether Missense Variants Are Disease Associated?

              Knowledge of protein structure can be used to predict the phenotypic consequence of a missense variant. Since structural coverage of the human proteome can be roughly tripled to over 50% of the residues if homology-predicted structures are included in addition to experimentally determined coordinates, it is important to assess the reliability of using predicted models when analyzing missense variants. Accordingly, we assess whether a missense variant is structurally damaging by using experimental and predicted structures. We considered 606 experimental structures and show that 40% of the 1965 disease-associated missense variants analyzed have a structurally damaging change in the mutant structure. Only 11% of the 2134 neutral variants are structurally damaging. Importantly, similar results are obtained when 1052 structures predicted using Phyre2 algorithm were used, even when the model shares low (< 40%) sequence identity to the template. Thus, structure-based analysis of the effects of missense variants can be effectively applied to homology models. Our in-house pipeline, Missense3D, for structurally assessing missense variants was made available at http://www.sbg.bio.ic.ac.uk/~missense3d
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                Author and article information

                Journal
                Hum Mol Genet
                Hum. Mol. Genet
                hmg
                Human Molecular Genetics
                Oxford University Press
                0964-6906
                1460-2083
                01 December 2019
                10 October 2019
                10 October 2019
                : 28
                : 23
                : 3912-3920
                Affiliations
                [1 ] Genomic Medicine Laboratory UILDM , Santa Lucia Foundation, Rome, 00142, Italy
                [2 ] Department of Biomedicine and Prevention , Tor Vergata University, Rome, 00133, Italy
                [3 ] Department of Veterinary Medicine (DIMEVET) , University of Milan, Milan, 20100, Italy
                [4 ] vCardiomyology and Medical Genetics , Department of Experimental Medicine, University of Campania Luigi Vanvitelli, Naples, 80131, Italy
                [5 ] Unità Operativa Complessa di Neurologia , Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, 00168, Italy
                [6 ] Neuromed Institute IRCCS , Pozzilli, 86077, Italy
                [7 ] Istituto di Neurologia , Università Cattolica del Sacro Cuore, Rome, 00168, Italy
                [8 ] Department of Biomedical Sciences , Catholic University Our Lady of Good Counsel, Tirana, 1000, Albania
                Author notes
                To whom correspondence should be addressed at: via Montpellier, 1, 00133, Rome. Tel: 0672596007; Fax: 065032097; Email: claudia.strafella@ 123456gmail.com

                These authors contributed equally to the manuscript.

                Author information
                http://orcid.org/0000-0003-1334-0920
                Article
                ddz239
                10.1093/hmg/ddz239
                6969370
                31600781
                e7ddfa34-967d-47ba-9734-d779568c2a0b
                © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 July 2019
                : 10 September 2019
                : 12 September 2019
                Page count
                Pages: 09
                Funding
                Funded by: Italian Ministry of Health
                Award ID: 5X1000-2016
                Award ID: 5x2017 MINSAL.3
                Categories
                General Article

                Genetics
                Genetics

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