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Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation
The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurate...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611741/ https://www.ncbi.nlm.nih.gov/pubmed/37891200 http://dx.doi.org/10.1038/s41467-023-42531-9 |
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author | Steyaert, Wouter Haer-Wigman, Lonneke Pfundt, Rolph Hellebrekers, Debby Steehouwer, Marloes Hampstead, Juliet de Boer, Elke Stegmann, Alexander Yntema, Helger Kamsteeg, Erik-Jan Brunner, Han Hoischen, Alexander Gilissen, Christian |
author_facet | Steyaert, Wouter Haer-Wigman, Lonneke Pfundt, Rolph Hellebrekers, Debby Steehouwer, Marloes Hampstead, Juliet de Boer, Elke Stegmann, Alexander Yntema, Helger Kamsteeg, Erik-Jan Brunner, Han Hoischen, Alexander Gilissen, Christian |
author_sort | Steyaert, Wouter |
collection | PubMed |
description | The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurately identifies single nucleotide variants and small insertions/deletions (SNVs/Indels), copy number variants and ectopic gene conversion events in duplicated genomic regions using whole-exome sequencing data. Application to a cohort of 41,755 exome samples yields 20,432 rare homozygous deletions and 2,529,791 rare SNVs/Indels, of which we show that 338,084 are due to gene conversion events. None of the SNVs/Indels are detectable using regular analysis techniques. Validation by high-fidelity long-read sequencing in 20 samples confirms >88% of called variants. Focusing on variation in known disease genes leads to a direct molecular diagnosis in 25 previously undiagnosed patients. Our method can readily be applied to existing exome data. |
format | Online Article Text |
id | pubmed-10611741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106117412023-10-29 Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation Steyaert, Wouter Haer-Wigman, Lonneke Pfundt, Rolph Hellebrekers, Debby Steehouwer, Marloes Hampstead, Juliet de Boer, Elke Stegmann, Alexander Yntema, Helger Kamsteeg, Erik-Jan Brunner, Han Hoischen, Alexander Gilissen, Christian Nat Commun Article The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurately identifies single nucleotide variants and small insertions/deletions (SNVs/Indels), copy number variants and ectopic gene conversion events in duplicated genomic regions using whole-exome sequencing data. Application to a cohort of 41,755 exome samples yields 20,432 rare homozygous deletions and 2,529,791 rare SNVs/Indels, of which we show that 338,084 are due to gene conversion events. None of the SNVs/Indels are detectable using regular analysis techniques. Validation by high-fidelity long-read sequencing in 20 samples confirms >88% of called variants. Focusing on variation in known disease genes leads to a direct molecular diagnosis in 25 previously undiagnosed patients. Our method can readily be applied to existing exome data. Nature Publishing Group UK 2023-10-27 /pmc/articles/PMC10611741/ /pubmed/37891200 http://dx.doi.org/10.1038/s41467-023-42531-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Steyaert, Wouter Haer-Wigman, Lonneke Pfundt, Rolph Hellebrekers, Debby Steehouwer, Marloes Hampstead, Juliet de Boer, Elke Stegmann, Alexander Yntema, Helger Kamsteeg, Erik-Jan Brunner, Han Hoischen, Alexander Gilissen, Christian Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
title | Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
title_full | Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
title_fullStr | Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
title_full_unstemmed | Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
title_short | Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
title_sort | systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611741/ https://www.ncbi.nlm.nih.gov/pubmed/37891200 http://dx.doi.org/10.1038/s41467-023-42531-9 |
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