La Cognata V, Morello G, Gentile G, Cavalcanti F, Cittadella R, Conforti FL, De Marco EV, Magariello A, Muglia M, Patitucci A, Spadafora P, D’Agata V, Ruggieri M, Cavallaro S.
NeuroArray: A Customized aCGH for the Analysis of Copy Number Variations in Neurological Disorders.
Curr Genomics 2018;
19:431-443. [PMID:
30258275 PMCID:
PMC6128384 DOI:
10.2174/1389202919666180404105451]
[Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 02/02/2018] [Accepted: 03/13/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND
Neurological disorders are a highly heterogeneous group of pathological conditions that affect both the peripheral and the central nervous system. These pathologies are characterized by a complex and multifactorial etiology involving numerous environmental agents and genetic susceptibility factors. For this reason, the investigation of their pathogenetic basis by means of traditional methodological approaches is rather arduous. High-throughput genotyping technologies, including the microarray-based comparative genomic hybridization (aCGH), are currently replacing classical detection methods, providing powerful molecular tools to identify genomic unbalanced structural rearrangements and explore their role in the pathogenesis of many complex human diseases.
METHODS
In this report, we comprehensively describe the design method, the procedures, validation, and implementation of an exon-centric customized aCGH (NeuroArray 1.0), tailored to detect both single and multi-exon deletions or duplications in a large set of multi- and monogenic neurological diseases. This focused platform enables a targeted measurement of structural imbalances across the human genome, targeting the clinically relevant genes at exon-level resolution.
CONCLUSION
An increasing use of the NeuroArray platform may offer new insights in investigating potential overlapping gene signatures among neurological conditions and defining genotype-phenotype relationships.
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