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      Gnathodiaphyseal dysplasia with a novel genetic variant in a large family from Iran

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          Abstract

          Background

          Gnathodiaphyseal dysplasia (GDD) is an ultrarare autosomal dominant bone dysplasia characterized by cementoosseous lesions of the jawbones, bone fragility, frequent bone fractures at the young age, bowing of tubular bones, and diaphyseal sclerosis of long bones associated with generalized osteopenia. GDD is caused by point mutations in anoctamin‐5 ( ANO5) on chromosome 11p14.3. For the past few years, next generation sequencing (NGS) technology has facilitated the discovery of causative variants in genetically heterogeneous diseases.

          Methods

          In this study, exome sequencing (ES) was performed using the DNA sample of the proband. Family histories and clinical information were collected through comprehensive medical examination and genetic counseling.

          Results

          ES results identified a heterozygous variant, NM_213599.3:c.1078T>C(p.Cys360Arg) in the ANO5 gene. Sanger sequencing was performed to confirm the detected pathogenic variant in DNA samples of the entire family (except deceased individuals), which segregated with the disease within the family. Finally, in silico analysis was applied to test the pathogenicity of the variant using various online software.

          Conclusion

          In summary, our investigation identified a novel pathogenic variant in the ANO5, responsible for gnathodiaphyseal dysplasia in a large Iranian family. Therefore, based on the present study, this variant can be helpful for diagnosis and effective management of GDD patients.

          Abstract

          Gnathodiaphyseal dysplasia (GDD) is an ultrarare autosomal dominant bone dysplasia characterized by cementoosseous lesions of the jawbones, bone fragility, frequent bone fractures at the young age. In this study, Exome Sequencing results identified a heterozygous mutation, NM_213599.3:c.1078T>C(p.Cys360Arg) in the ANO5 confirmed by Sanger sequencing.

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          Most cited references29

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

            The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Contributors
                v.yassaee-grc@sbmu.ac.ir
                Journal
                Mol Genet Genomic Med
                Mol Genet Genomic Med
                10.1002/(ISSN)2324-9269
                MGG3
                Molecular Genetics & Genomic Medicine
                John Wiley and Sons Inc. (Hoboken )
                2324-9269
                27 June 2022
                September 2022
                : 10
                : 9 ( doiID: 10.1002/mgg3.v10.9 )
                : e2004
                Affiliations
                [ 1 ] Genomic Research Center Shahid Beheshti University of Medical Sciences Tehran Iran
                [ 2 ] Department of Medical Genetics, School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran
                [ 3 ] Dental Research Center, Research Institute of Dental Sciences Shahid Beheshti University of Medical Sciences Tehran Iran
                [ 4 ] Student Research Committee, Dental School Shahid Beheshti University of Medical Sciences Tehran Iran
                Author notes
                [*] [* ] Correspondence

                Vahid Reza Yassaee, Genomic Research Center, Shahid Beheshti University of Medical Sciences, Tehran 19395‐4719, Iran.

                Email: v.yassaee-grc@ 123456sbmu.ac.ir

                Author information
                https://orcid.org/0000-0002-1879-3905
                https://orcid.org/0000-0002-5378-852X
                https://orcid.org/0000-0002-9996-9406
                https://orcid.org/0000-0001-9599-6151
                https://orcid.org/0000-0002-0236-0849
                https://orcid.org/0000-0003-1709-8975
                Article
                MGG32004 MGG3-2021-12-1945.R1
                10.1002/mgg3.2004
                9482395
                35758145
                ded0b3a3-a2bf-44e8-9f08-cee7834e8572
                © 2022 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 May 2022
                : 11 December 2021
                : 08 June 2022
                Page count
                Figures: 5, Tables: 3, Pages: 9, Words: 4563
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                September 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.8 mode:remove_FC converted:17.09.2022

                ano5,bone dysplasia,bone fractures,exome sequencing,gnathodiaphyseal dysplasia (gdd)

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