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Progress in Methods for Copy Number Variation Profiling
Copy number variations (CNVs) are the predominant class of structural genomic variations involved in the processes of evolutionary adaptation, genomic disorders, and disease progression. Compared with single-nucleotide variants, there have been challenges associated with the detection of CNVs owing...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879278/ https://www.ncbi.nlm.nih.gov/pubmed/35216262 http://dx.doi.org/10.3390/ijms23042143 |
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author | Gordeeva, Veronika Sharova, Elena Arapidi, Georgij |
author_facet | Gordeeva, Veronika Sharova, Elena Arapidi, Georgij |
author_sort | Gordeeva, Veronika |
collection | PubMed |
description | Copy number variations (CNVs) are the predominant class of structural genomic variations involved in the processes of evolutionary adaptation, genomic disorders, and disease progression. Compared with single-nucleotide variants, there have been challenges associated with the detection of CNVs owing to their diverse sizes. However, the field has seen significant progress in the past 20–30 years. This has been made possible due to the rapid development of molecular diagnostic methods which ensure a more detailed view of the genome structure, further complemented by recent advances in computational methods. Here, we review the major approaches that have been used to routinely detect CNVs, ranging from cytogenetics to the latest sequencing technologies, and then cover their specific features. |
format | Online Article Text |
id | pubmed-8879278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88792782022-02-26 Progress in Methods for Copy Number Variation Profiling Gordeeva, Veronika Sharova, Elena Arapidi, Georgij Int J Mol Sci Review Copy number variations (CNVs) are the predominant class of structural genomic variations involved in the processes of evolutionary adaptation, genomic disorders, and disease progression. Compared with single-nucleotide variants, there have been challenges associated with the detection of CNVs owing to their diverse sizes. However, the field has seen significant progress in the past 20–30 years. This has been made possible due to the rapid development of molecular diagnostic methods which ensure a more detailed view of the genome structure, further complemented by recent advances in computational methods. Here, we review the major approaches that have been used to routinely detect CNVs, ranging from cytogenetics to the latest sequencing technologies, and then cover their specific features. MDPI 2022-02-15 /pmc/articles/PMC8879278/ /pubmed/35216262 http://dx.doi.org/10.3390/ijms23042143 Text en © 2022 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 | Review Gordeeva, Veronika Sharova, Elena Arapidi, Georgij Progress in Methods for Copy Number Variation Profiling |
title | Progress in Methods for Copy Number Variation Profiling |
title_full | Progress in Methods for Copy Number Variation Profiling |
title_fullStr | Progress in Methods for Copy Number Variation Profiling |
title_full_unstemmed | Progress in Methods for Copy Number Variation Profiling |
title_short | Progress in Methods for Copy Number Variation Profiling |
title_sort | progress in methods for copy number variation profiling |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879278/ https://www.ncbi.nlm.nih.gov/pubmed/35216262 http://dx.doi.org/10.3390/ijms23042143 |
work_keys_str_mv | AT gordeevaveronika progressinmethodsforcopynumbervariationprofiling AT sharovaelena progressinmethodsforcopynumbervariationprofiling AT arapidigeorgij progressinmethodsforcopynumbervariationprofiling |