High-resolution map of copy number variations in motor cortex of Control and Sporadic Amyotrphic Lateral Sclerosis patients by using a customized exon-centric comparative genomic hybridization array.

Amyotrophic lateral sclerosis (ALS) is an incurable and fatal neurodegenerative disease. Increasing the chances of success for future clinical strategies requires more in-depth knowledge of the molecular basis underlying disease heterogeneity. We recently laid the foundation for a molecular taxonomy of ALS by whole transcriptome expression profiling of motor cortex from sporadic ALS (SALS) patients. Here, we analyzed genomic structural aberrations occurring in the same patients, by using a customized exon-centered comparative genomic hybridization array (aCGH) covering a large panel of ALS-related genes. Integrative analysis of copy number profiles with their associated transcriptomic data revealed subtype-specific genomic perturbations and candidate driver genes positively correlated with transcriptional signatures, which might represent novel potential biomarkers and therapeutic targets. This study represents the first comprehensive “omics” analysis of molecular events characterizing SALS pathology, providing a road map to facilitate genome-guided personalized diagnosis and treatments for this devastating disease. Motor cortex samples from 30 patients with clear SALS diagnosis and 10 control individuals were analysed by using an 8x60K custom exon-centric NeuroArray platform v. 2.0 (Agilent Technologies, Santa Clara, CA), tailored to detect single/multi-exon deletions and duplications in a large panel of ALS-related genes and to others additional neurological disorders. Two experimental conditions: DNA test and a reference of the same sex (Euro Reference, Agilent Technologies, Santa Clara, CA) were processed according to the manufacturer’s protocol (Agilent Technologies, Santa Clara, CA). SALS patient DNAs were labeled with Cy5-dUTP and reference DNAs for reference DNAs. Arrays were scanned at 3 µm resolution using an Agilent G4900DA SureScan Microarray Scanner System and aCGH image data were processed using Agilent’s Feature Extraction software. Feature extracted raw data was normalized, analyzed and visualized using Agilent CytoGenomics v. 4.0.3.12 and Genomic Workbench v. 7.0.4.0 software (Agilent Technologies, Santa Clara, CA, USA). GC correction with a window size of 2 kb and Diploid Peak Centralization were used for normalization. The Centralization Normalization Algorithm with a threshold of 6.0 and a bin size of 10 was also used for detecting aberrant regions or regions of constant CNVs. Aberrations were detected by the Aberration Detection Method II algorithm (ADM-2), with a sensitivity threshold of 6.0 and moving average window of 2Mb. Human reference sequence hg19 assembly was used to define the genomic coordinates of detected CNVs.