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svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing
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 f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10167630/ https://www.ncbi.nlm.nih.gov/pubmed/37181851 http://dx.doi.org/10.1093/nargab/lqad042 |
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author | Wilson, Thomas E Ahmed, Samreen Higgins, Jake Salk, Jesse J Glover, Thomas W |
author_facet | Wilson, Thomas E Ahmed, Samreen Higgins, Jake Salk, Jesse J Glover, Thomas W |
author_sort | Wilson, Thomas E |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10167630 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101676302023-05-10 svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing Wilson, Thomas E Ahmed, Samreen Higgins, Jake Salk, Jesse J Glover, Thomas W NAR Genom Bioinform Standard Article 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. Oxford University Press 2023-05-09 /pmc/articles/PMC10167630/ /pubmed/37181851 http://dx.doi.org/10.1093/nargab/lqad042 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Standard Article Wilson, Thomas E Ahmed, Samreen Higgins, Jake Salk, Jesse J Glover, Thomas W svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
title | svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
title_full | svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
title_fullStr | svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
title_full_unstemmed | svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
title_short | svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
title_sort | svcapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing |
topic | Standard Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10167630/ https://www.ncbi.nlm.nih.gov/pubmed/37181851 http://dx.doi.org/10.1093/nargab/lqad042 |
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