Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples

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• dc.contributor.author Wijngaard, Robin
• dc.contributor.author Laurie, Steven, 1973-
• dc.contributor.author Gilissen, Christian
• dc.date.accessioned 2024-01-17T08:22:57Z
• dc.date.available 2024-01-17T08:22:57Z
• dc.date.issued 2023
• dc.description.abstract Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES.
• dc.description.sponsorship Funding The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 779257. RW received an international fellowship from the José Luis Castaño-SEQC Foundation. FM is supported by the Edmond J. Safra Foundation through the Edmond J. Safra Fellowship in Movement Disorders.
• dc.format.mimetype application/pdf
• dc.identifier.citation Wijngaard R, Demidov G, O'Gorman L, Corominas-Galbany J, Yaldiz B, Steyaert W, et al. Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples. Eur J Hum Genet. 2023 Oct 19. DOI: 10.1038/s41431-023-01478-7
• dc.identifier.doi http://dx.doi.org/10.1038/s41431-023-01478-7
• dc.identifier.issn 1018-4813
• dc.identifier.uri http://hdl.handle.net/10230/58739
• dc.language.iso eng
• dc.publisher Nature Research
• dc.relation.ispartof Eur J Hum Genet. 2023 Oct 19
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/779257
• dc.rights © The Author(s) 2023, corrected publication 2023. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Computational biology and bioinformatics
• dc.subject.keyword Genetics
• dc.title Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion