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Phasing of de novo mutations using a scaled‐up multiple amplicon long‐read sequencing approach
De novo mutations (DNMs) play an important role in severe genetic disorders that reduce fitness. To better understand their role in disease, it is important to determine the parent‐of‐origin and timing of mutational events that give rise to these mutations, especially in sex‐specific developmental d...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826063/ https://www.ncbi.nlm.nih.gov/pubmed/36047340 http://dx.doi.org/10.1002/humu.24450 |
Sumario: | De novo mutations (DNMs) play an important role in severe genetic disorders that reduce fitness. To better understand their role in disease, it is important to determine the parent‐of‐origin and timing of mutational events that give rise to these mutations, especially in sex‐specific developmental disorders such as male infertility. However, currently available short‐read sequencing approaches are not ideally suited for phasing, as this requires long continuous DNA strands that span both the DNM and one or more informative single‐nucleotide polymorphisms. To overcome these challenges, we optimized and implemented a multiplexed long‐read sequencing approach using Oxford Nanopore technologies MinION platform. We focused on improving target amplification, integrating long‐read sequenced data with high‐quality short‐read sequence data, and developing an anchored phasing computational method. This approach handled the inherent phasing challenges of long‐range target amplification and the normal accumulation of sequencing error associated with long‐read sequencing. In total, 77 of 109 DNMs (71%) were successfully phased and parent‐of‐origin identified. The majority of phased DNMs were prezygotic (90%), the accuracy of which is highlighted by an average mutant allele frequency of 49.6% and standard error of 0.84%. This study demonstrates the benefits of employing an integrated short‐read and long‐read sequencing approach for large‐scale DNM phasing. |
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