Complementarity of long-read sequencing and optical genome mapping in Parkinson’s disease
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Background
With third-generation long-read sequencing (LRS) platforms and optical genome mapping technologies (OGM), the ability to detect large and complex structural variants (SVs) is rapidly advancing. This has led to the discovery of novel pathogenic variants, such as large deletions and insertions, in neurodegenerative movement disorders. Thus, we aimed to systematically examine the applicability of the combined application of LRS and OGM in Parkinson’s disease (PD).
Methods
Ultra-high molecular weight DNA was derived from blood and fibroblast cultures and used for Oxford Nanopore Technologies (ONT) LRS and OGM. We included 19 patients with mostly early-onset PD. Variant calling was performed with the tools Sniffles2 and Spectre for ONT and the Bionano Solve software for OGM. The size distribution of deletions and insertions was compared, and a subsequent analysis pipeline based on AnnotSV, SVAFotate, and needLR was employed to annotate and filter for rare (population allele frequency ≤1%) or potentially pathogenic (CADD-SV >20) variants affecting 134 known movement disorder genes.
Results
Both methods identified SVs ≥50 kb; however, OGM detected fewer SVs (49,677) with a larger mean size of 25 kb (SD=209 kb) compared to ONT (92,030, mean=17 kb, SD=1.1 Mb). In the size bracket of 50-80 kb, which falls outside the ideal detection range of Sniffles2 and Spectre, OGM detected 384 deletions and insertions, compared to six detected by ONT. OGM detected significantly larger deletions and insertions than ONT (p-value <2.2×10 -16 ). Regarding known movement disorder genes, a heterozygous intergenic deletion (195 kb) near ITPR1 was detected by both methods, and OGM validated a previously published 7 Mb inversion in PRKN . Heterozygous deletions in ATXN2 (1.4 kb), SUCLA2 (1.7 kb), and PNKD (2.6 kb) were detected by OGM and confirmed to be intronic by ONT.
Conclusion
OGM allows for better detection of large insertions and can serve as a powerful first-line method to detect large pathogenic variants. However, it greatly benefits from a high-resolution sequencing technique like ONT to refine breakpoint positions. Despite certain limitations, ONT proved to be highly capable of detecting large variants independently; thus, it allows for a highly complementary assessment and validation of structural variation in combination with OGM.
