Abstract
Structural variation (SV) is a major cause of genetic disorders. In this paper, we show that low-depth (specifically, 4×) whole-genome sequencing using a single Oxford Nanopore MinION flow cell suffices to support sensitive detection of SV, particularly pathogenic SV for supporting clinical diagnosis. When using 4× ONT WGS data, existing SV calling software often fails to detect pathogenic SV, especially in the form of long deletion, terminal deletion, duplication, and unbalanced translocation. Our new SV calling software SENSV can achieve high sensitivity for all types of SV and a breakpoint precision typically ± 100 bp; both features are important for clinical concerns. The improvement achieved by SENSV stems from several new algorithms. We evaluated SENSV and other software using both real and simulated data. The former was based on 24 patient samples, each diagnosed with a genetic disorder. SENSV found the pathogenic SV in 22 out of 24 cases (all heterozygous, size from hundreds of kbp to a few Mbp), reporting breakpoints within 100 bp of the true answers. On the other hand, no existing software can detect the pathogenic SV in more than 10 out of 24 cases, even when the breakpoint requirement is relaxed to ± 2000 bp.
Highlights
Structural variation (SV) is a major cause of genetic disorders
We used (1) real data from 24 patients with genetic disorders and experimentally verified SVs; (2) HG002 sequenced by a single MinION flow cell; evaluation is based on a recently published SV set; and (3) two simulated datasets, each with 35 planted SVs of various types
All DNA samples were prepared using an in-house protocol optimized based on the Oxford Nanopore Technologies (ONT) SQK-LSK109 ligation protocol (GDE_9063_v109_revY_14Aug2019) with a target read-length N50 of approx. 10 kbp before MinION sequencing
Summary
Structural variation (SV) is a major cause of genetic disorders. In this paper, we show that low-depth (4×) whole-genome sequencing using a single Oxford Nanopore MinION flow cell suffices to support sensitive detection of SV, pathogenic SV for supporting clinical diagnosis. SENSV outperformed others with breakpoint detected as precise as ± 100 bp, especially for handling difficult cases including long deletion (i.e., over 100 kbp), duplication, terminal deletion and unbalanced translocation, by recovering misaligned split reads. SENSV has demonstrated the best sensitivity among the software in detecting the 532 GIAB-confirmed HG002 deletions (≥ 1 kbp) and seven types of pathogenic variants implanted in two simulated low-depth datasets.
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