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      Whole-Genome Sequencing in Diagnostics of Selected Slovenian Undiagnosed Patients with Rare Disorders

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          Abstract

          Several patients with rare genetic disorders remain undiagnosed following comprehensive diagnostic testing using whole-exome sequencing (WES). In these patients, pathogenic genetic variants may reside in intronic or regulatory regions or they may emerge through mutational mechanisms not detected by WES. For this reason, we implemented whole-genome sequencing (WGS) in routine clinical diagnostics of patients with undiagnosed genetic disorders and report on the outcome in 30 patients. Criteria for consideration included (1) negative WES, (2) a high likelihood of a genetic cause for the disorders, (3) positive family history, (4) detection of large blocks of homozygosity or (5) detection of a single pathogenic variant in a gene associated with recessive conditions. We successfully discovered a causative genetic variant in 6 cases, a retrotranspositional event in the APC gene, non-coding variants in the intronic region of the OTC gene and the promotor region of the UFM1 gene, repeat expansion in the RFC1 gene and a single exon duplication in the CNGB3 gene. We also discovered one coding variant, an indel, which was missed by variant caller during WES data analysis. Our study demonstrates the impact of WGS in the group of patients with undiagnosed genetic diseases after WES in the clinical setting and the diversity of mutational mechanisms discovered, which would remain undetected using other methods.

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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 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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              From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline.

              This unit describes how to use BWA and the Genome Analysis Toolkit (GATK) to map genome sequencing data to a reference and produce high-quality variant calls that can be used in downstream analyses. The complete workflow includes the core NGS data processing steps that are necessary to make the raw data suitable for analysis by the GATK, as well as the key methods involved in variant discovery using the GATK.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Life (Basel)
                Life (Basel)
                life
                Life
                MDPI
                2075-1729
                05 March 2021
                March 2021
                : 11
                : 3
                : 205
                Affiliations
                Clinical Institute of Genomic Medicine, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; gaber.bergant@ 123456kclj.si (G.B.); ales.maver@ 123456kclj.si (A.M.)
                Author notes
                Author information
                https://orcid.org/0000-0003-4498-1042
                Article
                life-11-00205
                10.3390/life11030205
                8001615
                33807868
                3a968e11-e7fb-4e33-8b9c-2a7f1295eb08
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 January 2021
                : 01 March 2021
                Categories
                Article

                whole-genome sequencing,exome sequencing,bioinformatics,repeat expansion,retrotransposition,diagnostic yield,clinical setting

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