Mini‐Exome Coupled to Read‐Depth Based Copy Number Variation Analysis in Patients with Inherited Ataxias. Issue 12 (2nd September 2016) - Marelli, Cecilia; Guissart, Claire; Hubsch, Cecile; Renaud, Mathilde; Villemin, Jean‐Philippe; Larrieu, Lise; Charles, Perrine; Ayrignac, Xavier; Sacconi, Sabrina; Collignon, Patrick; Cuntz‐Shadfar, Danielle; Perrin, Laurine; et al.
Abstract : Identification of nucleotide variations, copy number variations, and expansion in inherited ataxias by next generation sequencing: – Pathogenicity prediction of nucleotide (nt) variation (Figure A): multiscoring predicts both missense and splice site pathogenicity for the same heterozygous SETX variation in patient ATX163 – CNV detection (Figure B): heterozygous SETX exon 4 to 7 deletion in patient ATX163 – Expansion detection (Figure C): ATXN2, CAG expansion (arrows) in patient ATX340 ABSTRACT: Next‐generation sequencing (NGS) has an established diagnostic value for inherited ataxia. However, the need of a rigorous process of analysis and validation remains challenging. Moreover, copy number variations (CNV) or dynamic expansions of repeated sequence are classically considered not adequately detected by exome sequencing technique. We applied a strategy of mini‐exome coupled to read‐depth based CNV analysis to a series of 33 patients with probable inherited ataxia and onset <50 years. The mini‐exome consisted of the capture of 4, 813 genes having associated clinical phenotypes. Pathogenic variants were found in 42% and variants of uncertain significance in 24% of the patients. These results are comparable to those from whole exome sequencing and better than previous targeted NGS studies. CNV and dynamic expansions of repeated CAG sequence were identified in three patients. We identified both atypical presentation of known ataxia genes ( ATM, NPC1 ) and mutations in genes very rarely associated with ataxia ( ERCC4, HSD17B4) . We show that mini‐exome bioinformatics data analysis allows the identification of CNV and dynamic expansions of repeated sequence. Our study confirms the diagnostic value of the proposed genetic analysis strategy. We also provide an algorithm for the multidisciplinary process of analysis, interpretation, and validation of NGS data.