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Scalable detection of technically challenging variants through modified next‐generation sequencing
BACKGROUND: Some clinically important genetic variants are not easily evaluated with next‐generation sequencing (NGS) methods due to technical challenges arising from high‐ similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats,...
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/PMC9747563/ https://www.ncbi.nlm.nih.gov/pubmed/36251442 http://dx.doi.org/10.1002/mgg3.2072 |
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author | Rojahn, Susan Hambuch, Tina Adrian, Jessika Gafni, Erik Gileta, Alex Hatchell, Hannah Johnson, Britt Kallman, Ben Karfilis, Kate Kautzer, Curtis Kennemer, Michael Kirk, Lloyd Kvitek, Daniel Lettes, Jessica Macrae, Fenner Mendez, Fernando Paul, Joshua Pellegrino, Maurizio Preciado, Ronny Risinger, Jan Schultz, Matthew Spurka, Lindsay Swamy, Sajani Truty, Rebecca Usem, Nathan Velenich, Andrea Aradhya, Swaroop |
author_facet | Rojahn, Susan Hambuch, Tina Adrian, Jessika Gafni, Erik Gileta, Alex Hatchell, Hannah Johnson, Britt Kallman, Ben Karfilis, Kate Kautzer, Curtis Kennemer, Michael Kirk, Lloyd Kvitek, Daniel Lettes, Jessica Macrae, Fenner Mendez, Fernando Paul, Joshua Pellegrino, Maurizio Preciado, Ronny Risinger, Jan Schultz, Matthew Spurka, Lindsay Swamy, Sajani Truty, Rebecca Usem, Nathan Velenich, Andrea Aradhya, Swaroop |
author_sort | Rojahn, Susan |
collection | PubMed |
description | BACKGROUND: Some clinically important genetic variants are not easily evaluated with next‐generation sequencing (NGS) methods due to technical challenges arising from high‐ similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats, FMR1 AGG interruptions in CGG repeats, CFTR poly‐T/TG repeats), and other complexities (e.g., MSH2 Boland inversions). METHODS: We customized our NGS processes to detect the technically challenging variants mentioned above with adaptations including target enrichment and bioinformatic masking of similar sequences. Adaptations were validated with samples of known genotypes. RESULTS: Our adaptations provided high‐sensitivity and high‐specificity detection for most of the variants and provided a high‐sensitivity primary assay to be followed with orthogonal disambiguation for the others. The sensitivity of the NGS adaptations was 100% for all of the technically challenging variants. Specificity was 100% for those in PMS2, GBA1, SMN1/SMN2, and HBA1/HBA2, and for the MSH2 Boland inversion; 97.8%–100% for CYP21A2 variants; and 85.7% for ARX polyalanine repeats. CONCLUSIONS: NGS assays can detect technically challenging variants when chemistries and bioinformatics are jointly refined. The adaptations described support a scalable, cost‐effective path to identifying all clinically relevant variants within a single sample. |
format | Online Article Text |
id | pubmed-9747563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97475632022-12-14 Scalable detection of technically challenging variants through modified next‐generation sequencing Rojahn, Susan Hambuch, Tina Adrian, Jessika Gafni, Erik Gileta, Alex Hatchell, Hannah Johnson, Britt Kallman, Ben Karfilis, Kate Kautzer, Curtis Kennemer, Michael Kirk, Lloyd Kvitek, Daniel Lettes, Jessica Macrae, Fenner Mendez, Fernando Paul, Joshua Pellegrino, Maurizio Preciado, Ronny Risinger, Jan Schultz, Matthew Spurka, Lindsay Swamy, Sajani Truty, Rebecca Usem, Nathan Velenich, Andrea Aradhya, Swaroop Mol Genet Genomic Med Original Articles BACKGROUND: Some clinically important genetic variants are not easily evaluated with next‐generation sequencing (NGS) methods due to technical challenges arising from high‐ similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats, FMR1 AGG interruptions in CGG repeats, CFTR poly‐T/TG repeats), and other complexities (e.g., MSH2 Boland inversions). METHODS: We customized our NGS processes to detect the technically challenging variants mentioned above with adaptations including target enrichment and bioinformatic masking of similar sequences. Adaptations were validated with samples of known genotypes. RESULTS: Our adaptations provided high‐sensitivity and high‐specificity detection for most of the variants and provided a high‐sensitivity primary assay to be followed with orthogonal disambiguation for the others. The sensitivity of the NGS adaptations was 100% for all of the technically challenging variants. Specificity was 100% for those in PMS2, GBA1, SMN1/SMN2, and HBA1/HBA2, and for the MSH2 Boland inversion; 97.8%–100% for CYP21A2 variants; and 85.7% for ARX polyalanine repeats. CONCLUSIONS: NGS assays can detect technically challenging variants when chemistries and bioinformatics are jointly refined. The adaptations described support a scalable, cost‐effective path to identifying all clinically relevant variants within a single sample. John Wiley and Sons Inc. 2022-10-17 /pmc/articles/PMC9747563/ /pubmed/36251442 http://dx.doi.org/10.1002/mgg3.2072 Text en © 2022 Invitae Corporation. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Rojahn, Susan Hambuch, Tina Adrian, Jessika Gafni, Erik Gileta, Alex Hatchell, Hannah Johnson, Britt Kallman, Ben Karfilis, Kate Kautzer, Curtis Kennemer, Michael Kirk, Lloyd Kvitek, Daniel Lettes, Jessica Macrae, Fenner Mendez, Fernando Paul, Joshua Pellegrino, Maurizio Preciado, Ronny Risinger, Jan Schultz, Matthew Spurka, Lindsay Swamy, Sajani Truty, Rebecca Usem, Nathan Velenich, Andrea Aradhya, Swaroop Scalable detection of technically challenging variants through modified next‐generation sequencing |
title | Scalable detection of technically challenging variants through modified next‐generation sequencing |
title_full | Scalable detection of technically challenging variants through modified next‐generation sequencing |
title_fullStr | Scalable detection of technically challenging variants through modified next‐generation sequencing |
title_full_unstemmed | Scalable detection of technically challenging variants through modified next‐generation sequencing |
title_short | Scalable detection of technically challenging variants through modified next‐generation sequencing |
title_sort | scalable detection of technically challenging variants through modified next‐generation sequencing |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747563/ https://www.ncbi.nlm.nih.gov/pubmed/36251442 http://dx.doi.org/10.1002/mgg3.2072 |
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