Cargando…

Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH

Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disord...

Descripción completa

Detalles Bibliográficos
Autores principales: Kucharík, Marcel, Budiš, Jaroslav, Hýblová, Michaela, Minárik, Gabriel, Szemes, Tomáš
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8071346/
https://www.ncbi.nlm.nih.gov/pubmed/33920867
http://dx.doi.org/10.3390/diagnostics11040708
_version_ 1783683679193661440
author Kucharík, Marcel
Budiš, Jaroslav
Hýblová, Michaela
Minárik, Gabriel
Szemes, Tomáš
author_facet Kucharík, Marcel
Budiš, Jaroslav
Hýblová, Michaela
Minárik, Gabriel
Szemes, Tomáš
author_sort Kucharík, Marcel
collection PubMed
description Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disorders. At present, several methods for CNV detection are applied, ranging from the conventional cytogenetic analysis, through microarray-based methods (aCGH), to next-generation sequencing (NGS). In this paper, we present GenomeScreen, an NGS-based CNV detection method for low-coverage, whole-genome sequencing. We determined the theoretical limits of its accuracy and obtained confirmation in an extensive in silico study and in real patient samples with known genotypes. In theory, at least 6 M uniquely mapped reads are required to detect a CNV with the length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in silico analysis required at least 8 M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has mean resolution of 200 kb. GenomeScreen and aCGH both detected 59 deviations, while GenomeScreen furthermore detected 134 other (usually) smaller variations. When compared to aCGH, overall performance of the proposed GenemoScreen tool is comparable or superior in terms of accuracy, turn-around time, and cost-effectiveness, thus providing reasonable benefits, particularly in a prenatal diagnosis setting.
format Online
Article
Text
id pubmed-8071346
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-80713462021-04-26 Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH Kucharík, Marcel Budiš, Jaroslav Hýblová, Michaela Minárik, Gabriel Szemes, Tomáš Diagnostics (Basel) Article Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disorders. At present, several methods for CNV detection are applied, ranging from the conventional cytogenetic analysis, through microarray-based methods (aCGH), to next-generation sequencing (NGS). In this paper, we present GenomeScreen, an NGS-based CNV detection method for low-coverage, whole-genome sequencing. We determined the theoretical limits of its accuracy and obtained confirmation in an extensive in silico study and in real patient samples with known genotypes. In theory, at least 6 M uniquely mapped reads are required to detect a CNV with the length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in silico analysis required at least 8 M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has mean resolution of 200 kb. GenomeScreen and aCGH both detected 59 deviations, while GenomeScreen furthermore detected 134 other (usually) smaller variations. When compared to aCGH, overall performance of the proposed GenemoScreen tool is comparable or superior in terms of accuracy, turn-around time, and cost-effectiveness, thus providing reasonable benefits, particularly in a prenatal diagnosis setting. MDPI 2021-04-15 /pmc/articles/PMC8071346/ /pubmed/33920867 http://dx.doi.org/10.3390/diagnostics11040708 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kucharík, Marcel
Budiš, Jaroslav
Hýblová, Michaela
Minárik, Gabriel
Szemes, Tomáš
Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH
title Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH
title_full Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH
title_fullStr Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH
title_full_unstemmed Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH
title_short Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH
title_sort copy number variant detection with low-coverage whole-genome sequencing represents a viable alternative to the conventional array-cgh
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8071346/
https://www.ncbi.nlm.nih.gov/pubmed/33920867
http://dx.doi.org/10.3390/diagnostics11040708
work_keys_str_mv AT kucharikmarcel copynumbervariantdetectionwithlowcoveragewholegenomesequencingrepresentsaviablealternativetotheconventionalarraycgh
AT budisjaroslav copynumbervariantdetectionwithlowcoveragewholegenomesequencingrepresentsaviablealternativetotheconventionalarraycgh
AT hyblovamichaela copynumbervariantdetectionwithlowcoveragewholegenomesequencingrepresentsaviablealternativetotheconventionalarraycgh
AT minarikgabriel copynumbervariantdetectionwithlowcoveragewholegenomesequencingrepresentsaviablealternativetotheconventionalarraycgh
AT szemestomas copynumbervariantdetectionwithlowcoveragewholegenomesequencingrepresentsaviablealternativetotheconventionalarraycgh