A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark

The identification of structural variants (SVs) in genomic data represents an ongoing challenge because of difficulties in reliable SV calling leading to reduced sensitivity and specificity. We prepared high-quality DNA from 9 parent–child trios, who had previously undergone short-read whole-genome...

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Auteurs principaux: Pei, Y, Tanguy, M, Giess, A, Dixit, A, Wilson, LC, Gibbons, RJ, Twigg, SRF, Elgar, G, Wilkie, AOM
Format: Journal article
Langue:English
Publié: MDPI 2024
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author Pei, Y
Tanguy, M
Giess, A
Dixit, A
Wilson, LC
Gibbons, RJ
Twigg, SRF
Elgar, G
Wilkie, AOM
author_facet Pei, Y
Tanguy, M
Giess, A
Dixit, A
Wilson, LC
Gibbons, RJ
Twigg, SRF
Elgar, G
Wilkie, AOM
author_sort Pei, Y
collection OXFORD
description The identification of structural variants (SVs) in genomic data represents an ongoing challenge because of difficulties in reliable SV calling leading to reduced sensitivity and specificity. We prepared high-quality DNA from 9 parent–child trios, who had previously undergone short-read whole-genome sequencing (Illumina platform) as part of the Genomics England 100,000 Genomes Project. We reanalysed the genomes using both Bionano optical genome mapping (OGM; 8 probands and one trio) and Nanopore long-read sequencing (Oxford Nanopore Technologies [ONT] platform; all samples). To establish a “truth” dataset, we asked whether rare proband SV calls (n = 234) made by the Bionano Access (version 1.6.1)/Solve software (version 3.6.1_11162020) could be verified by individual visualisation using the Integrative Genomics Viewer with either or both of the Illumina and ONT raw sequence. Of these, 222 calls were verified, indicating that Bionano OGM calls have high precision (positive predictive value 95%). We then asked what proportion of the 222 true Bionano SVs had been identified by SV callers in the other two datasets. In the Illumina dataset, sensitivity varied according to variant type, being high for deletions (115/134; 86%) but poor for insertions (13/58; 22%). In the ONT dataset, sensitivity was generally poor using the original Sniffles variant caller (48% overall) but improved substantially with use of Sniffles2 (36/40; 90% and 17/23; 74% for deletions and insertions, respectively). In summary, we show that the precision of OGM is very high. In addition, when applying the Sniffles2 caller, the sensitivity of SV calling using ONT long-read sequence data outperforms Illumina sequencing for most SV types.
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spelling oxford-uuid:56c0cf83-b5e7-4a8c-8acf-f646d10b6d342025-03-05T15:41:14ZA comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmarkJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:56c0cf83-b5e7-4a8c-8acf-f646d10b6d34EnglishSymplectic ElementsMDPI2024Pei, YTanguy, MGiess, ADixit, AWilson, LCGibbons, RJTwigg, SRFElgar, GWilkie, AOMThe identification of structural variants (SVs) in genomic data represents an ongoing challenge because of difficulties in reliable SV calling leading to reduced sensitivity and specificity. We prepared high-quality DNA from 9 parent–child trios, who had previously undergone short-read whole-genome sequencing (Illumina platform) as part of the Genomics England 100,000 Genomes Project. We reanalysed the genomes using both Bionano optical genome mapping (OGM; 8 probands and one trio) and Nanopore long-read sequencing (Oxford Nanopore Technologies [ONT] platform; all samples). To establish a “truth” dataset, we asked whether rare proband SV calls (n = 234) made by the Bionano Access (version 1.6.1)/Solve software (version 3.6.1_11162020) could be verified by individual visualisation using the Integrative Genomics Viewer with either or both of the Illumina and ONT raw sequence. Of these, 222 calls were verified, indicating that Bionano OGM calls have high precision (positive predictive value 95%). We then asked what proportion of the 222 true Bionano SVs had been identified by SV callers in the other two datasets. In the Illumina dataset, sensitivity varied according to variant type, being high for deletions (115/134; 86%) but poor for insertions (13/58; 22%). In the ONT dataset, sensitivity was generally poor using the original Sniffles variant caller (48% overall) but improved substantially with use of Sniffles2 (36/40; 90% and 17/23; 74% for deletions and insertions, respectively). In summary, we show that the precision of OGM is very high. In addition, when applying the Sniffles2 caller, the sensitivity of SV calling using ONT long-read sequence data outperforms Illumina sequencing for most SV types.
spellingShingle Pei, Y
Tanguy, M
Giess, A
Dixit, A
Wilson, LC
Gibbons, RJ
Twigg, SRF
Elgar, G
Wilkie, AOM
A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark
title A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark
title_full A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark
title_fullStr A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark
title_full_unstemmed A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark
title_short A comparison of structural variant calling from short-read and nanopore-based whole-genome sequencing using optical genome mapping as a benchmark
title_sort comparison of structural variant calling from short read and nanopore based whole genome sequencing using optical genome mapping as a benchmark
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