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Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing
Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensit...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769840/ https://www.ncbi.nlm.nih.gov/pubmed/31500242 http://dx.doi.org/10.3390/ijms20184403 |
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author | Pös, Ondrej Budis, Jaroslav Kubiritova, Zuzana Kucharik, Marcel Duris, Frantisek Radvanszky, Jan Szemes, Tomas |
author_facet | Pös, Ondrej Budis, Jaroslav Kubiritova, Zuzana Kucharik, Marcel Duris, Frantisek Radvanszky, Jan Szemes, Tomas |
author_sort | Pös, Ondrej |
collection | PubMed |
description | Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study. |
format | Online Article Text |
id | pubmed-6769840 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67698402019-10-30 Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing Pös, Ondrej Budis, Jaroslav Kubiritova, Zuzana Kucharik, Marcel Duris, Frantisek Radvanszky, Jan Szemes, Tomas Int J Mol Sci Communication Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study. MDPI 2019-09-07 /pmc/articles/PMC6769840/ /pubmed/31500242 http://dx.doi.org/10.3390/ijms20184403 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Pös, Ondrej Budis, Jaroslav Kubiritova, Zuzana Kucharik, Marcel Duris, Frantisek Radvanszky, Jan Szemes, Tomas Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing |
title | Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing |
title_full | Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing |
title_fullStr | Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing |
title_full_unstemmed | Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing |
title_short | Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing |
title_sort | identification of structural variation from ngs-based non-invasive prenatal testing |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769840/ https://www.ncbi.nlm.nih.gov/pubmed/31500242 http://dx.doi.org/10.3390/ijms20184403 |
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