Efficient CNV breakpoint analysis reveals unexpected structural complexity and correlation of dosage-sensitive genes with clinical severity in genomic disorders
Genomic disorders are the clinical conditions manifested by submicroscopic genomic rearrangements including copy number variants (CNVs). The CNVs can be identified by array-based comparative genomic hybridization (aCGH), the most commonly used technology for molecular diagnostics of genomic disorders. However, clinical aCGH only informs CNVs in the probe-interrogated regions. Neither orientational information nor the resulting genomic rearrangement structure is provided, which is a key to uncovering mutational and pathogenic mechanisms underlying genomic disorders. Long-range polymerase chain reaction (PCR) is a traditional approach to obtain CNV breakpoint junction, but this method is inefficient when challenged by structural complexity such as often found at the PLP1 locus in association with Pelizaeus-Merzbacher disease (PMD). Here we introduced ‘capture and single-molecule real-time sequencing’ (cap-SMRT-seq) and newly developed ‘asymmetry linker-mediated nested PCR walking’ (ALN-walking) for CNV breakpoint sequencing in 49 subjects with PMD-associated CNVs. Remarkably, 29 (94%) of the 31 CNV breakpoint junctions unobtainable by conventional long-range PCR were resolved by cap-SMRT-seq and ALN-walking. Notably, unexpected CNV complexities, including inter-chromosomal rearrangements that cannot be resolved by aCGH, were revealed by efficient breakpoint sequencing. These sequence-based structures of PMD-associated CNVs further support the role of DNA replicative mechanisms in CNV mutagenesis, and facilitate genotype-phenotype correlation studies. Intriguingly, the lengths of gained segments by CNVs are strongly correlated with clinical severity in PMD, potentially reflecting the functional contribution of other dosage-sensitive genes besides PLP1. Our study provides new efficient experimental approaches (especially ALN-walking) for CNV breakpoint sequencing and highlights their importance in uncovering CNV mutagenesis and pathogenesis in genomic disorders.