svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing

Author:

Wilson Thomas E12ORCID,Ahmed Samreen12,Higgins Jake3,Salk Jesse J3,Glover Thomas W12

Affiliation:

1. Department of Pathology, University of Michigan , Ann Arbor , MI 48109, USA

2. Department of Human Genetics, University of Michigan , Ann Arbor , MI 48109, USA

3. TwinStrand Biosciences Inc. , Seattle , WA 98121, USA

Abstract

Abstract Error-corrected sequencing of genomic targets enriched by probe-based capture has become a standard approach for detecting single-nucleotide variants (SNVs) and small insertion/deletions (indels) present at very low variant allele frequencies. Less attention has been given to comparable strategies for rare structural variant (SV) junctions, where different error mechanisms must be addressed. Working from samples with known SV properties, we demonstrate that duplex sequencing (DuplexSeq), which demands confirmation of variants on both strands of a source DNA molecule, eliminates false SV junctions arising from chimeric PCR. DuplexSeq could not address frequent intermolecular ligation artifacts that arise during Y-adapter addition prior to strand denaturation without requiring multiple source molecules. In contrast, tagmentation libraries coupled with data filtering based on strand family size greatly reduced both artifact classes and enabled efficient and specific detection of single-molecule SV junctions. The throughput of SV capture sequencing (svCapture) and base-level accuracy of DuplexSeq provided detailed views of the microhomology profile and limited occurrence of de novo SNVs near the junctions of hundreds of newly created SVs, suggesting end joining as a possible formation mechanism. The open source svCapture pipeline enables rare SV detection as a routine addition to SNVs/indels in properly prepared capture sequencing libraries.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computer Science Applications,Genetics,Molecular Biology,Structural Biology

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