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Clinically relevant copy-number variants in exome sequencing data of patients with dystonia
Institution:1. Medical Science Laboratory, Children''s Hospital, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning 530003, People''s Republic of China;2. Department of Genetic Metabolism, Children''s Hospital, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning 530003, People''s Republic of China;3. Division of Genetics and Genomics, Boston Children''s Hospital and Harvard Medical School, Boston, MA 02115, USA;4. The Manton Center for Orphan Disease Research, Boston Children''s Hospital and Harvard Medical School, Boston, MA 02115, USA;5. Division of Newborn Medicine, Boston Children''s Hospital and Harvard Medical School, Boston, MA 02115, USA
Abstract:IntroductionNext-generation sequencing is now used on a routine basis for molecular testing but studies on copy-number variant (CNV) detection from next-generation sequencing data are underrepresented. Utilizing an existing whole-exome sequencing (WES) dataset, we sought to investigate the contribution of rare CNVs to the genetic causality of dystonia.MethodsThe CNV read-depth analysis tool ExomeDepth was applied to the exome sequences of 953 unrelated patients with dystonia (600 with isolated dystonia and 353 with combined dystonia; 33% with additional neurological involvement). We prioritized rare CNVs that affected known disease genes and/or were known to be associated with defined microdeletion/microduplication syndromes. Pathogenicity assessment of CNVs was based on recently published standards of the American College of Medical Genetics and Genomics and the Clinical Genome Resource.ResultsWe identified pathogenic or likely pathogenic CNVs in 14 of 953 patients (1.5%). Of the 14 different CNVs, 12 were deletions and 2 were duplications, ranging in predicted size from 124bp to 17 Mb. Within the deletion intervals, BRPF1, CHD8, DJ1, EFTUD2, FGF14, GCH1, PANK2, SGCE, UBE3A, VPS16, WARS2, and WDR45 were determined as the most clinically relevant genes. The duplications involved chromosomal regions 6q21-q22 and 15q11-q13. CNV analysis increased the diagnostic yield in the total cohort from 18.4% to 19.8%, as compared to the assessment of single-nucleotide variants and small insertions and deletions alone.ConclusionsWES-based CNV analysis in dystonia is feasible, increases the diagnostic yield, and should be combined with the assessment of single-nucleotide variants and small insertions and deletions.
Keywords:Copy-number variant  Dystonia  Read-depth analysis  Diagnostic yield
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