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Test development, optimization and validation of a WGS pipeline for genetic disorders
BACKGROUND: With advances in massive parallel sequencing (MPS) technology, whole-genome sequencing (WGS) has gradually evolved into the first-tier diagnostic test for genetic disorders. However, deployment practice and pipeline testing for clinical WGS are lacking. METHODS: In this study, we introdu...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077614/ https://www.ncbi.nlm.nih.gov/pubmed/37020281 http://dx.doi.org/10.1186/s12920-023-01495-x |
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author | Yang, Ziying Yang, Xu Sun, Yan Wang, Yaoshen Song, Lijie Qiao, Zhihong Fang, Zhonghai Wang, Zhonghua Liu, Lipei Chen, Yunmei Yan, Saiying Guo, Xueqin Zhang, Junqing Fan, Chunna Liu, Fengxia Peng, Zhiyu Peng, Huanhuan Sun, Jun Chen, Wei |
author_facet | Yang, Ziying Yang, Xu Sun, Yan Wang, Yaoshen Song, Lijie Qiao, Zhihong Fang, Zhonghai Wang, Zhonghua Liu, Lipei Chen, Yunmei Yan, Saiying Guo, Xueqin Zhang, Junqing Fan, Chunna Liu, Fengxia Peng, Zhiyu Peng, Huanhuan Sun, Jun Chen, Wei |
author_sort | Yang, Ziying |
collection | PubMed |
description | BACKGROUND: With advances in massive parallel sequencing (MPS) technology, whole-genome sequencing (WGS) has gradually evolved into the first-tier diagnostic test for genetic disorders. However, deployment practice and pipeline testing for clinical WGS are lacking. METHODS: In this study, we introduced a whole WGS pipeline for genetic disorders, which included the entire process from obtaining a sample to clinical reporting. All samples that underwent WGS were constructed using polymerase chain reaction (PCR)-free library preparation protocols and sequenced on the MGISEQ-2000 platform. Bioinformatics pipelines were developed for the simultaneous detection of various types of variants, including single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs) and balanced rearrangements, mitochondrial (MT) variants, and other complex variants such as repeat expansion, pseudogenes and absence of heterozygosity (AOH). A semiautomatic pipeline was developed for the interpretation of potential SNVs and CNVs. Forty-five samples (including 14 positive commercially available samples, 23 laboratory-held positive cell lines and 8 clinical cases) with known variants were used to validate the whole pipeline. RESULTS: In this study, a whole WGS pipeline for genetic disorders was developed and optimized. Forty-five samples with known variants (6 with SNVs and Indels, 3 with MT variants, 5 with aneuploidies, 1 with triploidy, 23 with CNVs, 5 with balanced rearrangements, 2 with repeat expansions, 1 with AOHs, and 1 with exon 7–8 deletion of SMN1 gene) validated the effectiveness of our pipeline. CONCLUSIONS: This study has been piloted in test development, optimization, and validation of the WGS pipeline for genetic disorders. A set of best practices were recommended using our pipeline, along with a dataset of positive samples for benchmarking. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01495-x. |
format | Online Article Text |
id | pubmed-10077614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100776142023-04-07 Test development, optimization and validation of a WGS pipeline for genetic disorders Yang, Ziying Yang, Xu Sun, Yan Wang, Yaoshen Song, Lijie Qiao, Zhihong Fang, Zhonghai Wang, Zhonghua Liu, Lipei Chen, Yunmei Yan, Saiying Guo, Xueqin Zhang, Junqing Fan, Chunna Liu, Fengxia Peng, Zhiyu Peng, Huanhuan Sun, Jun Chen, Wei BMC Med Genomics Research BACKGROUND: With advances in massive parallel sequencing (MPS) technology, whole-genome sequencing (WGS) has gradually evolved into the first-tier diagnostic test for genetic disorders. However, deployment practice and pipeline testing for clinical WGS are lacking. METHODS: In this study, we introduced a whole WGS pipeline for genetic disorders, which included the entire process from obtaining a sample to clinical reporting. All samples that underwent WGS were constructed using polymerase chain reaction (PCR)-free library preparation protocols and sequenced on the MGISEQ-2000 platform. Bioinformatics pipelines were developed for the simultaneous detection of various types of variants, including single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs) and balanced rearrangements, mitochondrial (MT) variants, and other complex variants such as repeat expansion, pseudogenes and absence of heterozygosity (AOH). A semiautomatic pipeline was developed for the interpretation of potential SNVs and CNVs. Forty-five samples (including 14 positive commercially available samples, 23 laboratory-held positive cell lines and 8 clinical cases) with known variants were used to validate the whole pipeline. RESULTS: In this study, a whole WGS pipeline for genetic disorders was developed and optimized. Forty-five samples with known variants (6 with SNVs and Indels, 3 with MT variants, 5 with aneuploidies, 1 with triploidy, 23 with CNVs, 5 with balanced rearrangements, 2 with repeat expansions, 1 with AOHs, and 1 with exon 7–8 deletion of SMN1 gene) validated the effectiveness of our pipeline. CONCLUSIONS: This study has been piloted in test development, optimization, and validation of the WGS pipeline for genetic disorders. A set of best practices were recommended using our pipeline, along with a dataset of positive samples for benchmarking. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01495-x. BioMed Central 2023-04-05 /pmc/articles/PMC10077614/ /pubmed/37020281 http://dx.doi.org/10.1186/s12920-023-01495-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Yang, Ziying Yang, Xu Sun, Yan Wang, Yaoshen Song, Lijie Qiao, Zhihong Fang, Zhonghai Wang, Zhonghua Liu, Lipei Chen, Yunmei Yan, Saiying Guo, Xueqin Zhang, Junqing Fan, Chunna Liu, Fengxia Peng, Zhiyu Peng, Huanhuan Sun, Jun Chen, Wei Test development, optimization and validation of a WGS pipeline for genetic disorders |
title | Test development, optimization and validation of a WGS pipeline for genetic disorders |
title_full | Test development, optimization and validation of a WGS pipeline for genetic disorders |
title_fullStr | Test development, optimization and validation of a WGS pipeline for genetic disorders |
title_full_unstemmed | Test development, optimization and validation of a WGS pipeline for genetic disorders |
title_short | Test development, optimization and validation of a WGS pipeline for genetic disorders |
title_sort | test development, optimization and validation of a wgs pipeline for genetic disorders |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077614/ https://www.ncbi.nlm.nih.gov/pubmed/37020281 http://dx.doi.org/10.1186/s12920-023-01495-x |
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