Cargando…

Detection of Genomic Structural Variants from Next-Generation Sequencing Data

Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting s...

Descripción completa

Detalles Bibliográficos
Autores principales: Tattini, Lorenzo, D’Aurizio, Romina, Magi, Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479793/
https://www.ncbi.nlm.nih.gov/pubmed/26161383
http://dx.doi.org/10.3389/fbioe.2015.00092
_version_ 1782378061114638336
author Tattini, Lorenzo
D’Aurizio, Romina
Magi, Alberto
author_facet Tattini, Lorenzo
D’Aurizio, Romina
Magi, Alberto
author_sort Tattini, Lorenzo
collection PubMed
description Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools – and their underlying algorithms – designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication – with particular emphasis on human genetics and copy number variants – for researchers involved in the investigation of these genomic events.
format Online
Article
Text
id pubmed-4479793
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-44797932015-07-09 Detection of Genomic Structural Variants from Next-Generation Sequencing Data Tattini, Lorenzo D’Aurizio, Romina Magi, Alberto Front Bioeng Biotechnol Bioengineering and Biotechnology Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools – and their underlying algorithms – designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication – with particular emphasis on human genetics and copy number variants – for researchers involved in the investigation of these genomic events. Frontiers Media S.A. 2015-06-25 /pmc/articles/PMC4479793/ /pubmed/26161383 http://dx.doi.org/10.3389/fbioe.2015.00092 Text en Copyright © 2015 Tattini, D’Aurizio and Magi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Tattini, Lorenzo
D’Aurizio, Romina
Magi, Alberto
Detection of Genomic Structural Variants from Next-Generation Sequencing Data
title Detection of Genomic Structural Variants from Next-Generation Sequencing Data
title_full Detection of Genomic Structural Variants from Next-Generation Sequencing Data
title_fullStr Detection of Genomic Structural Variants from Next-Generation Sequencing Data
title_full_unstemmed Detection of Genomic Structural Variants from Next-Generation Sequencing Data
title_short Detection of Genomic Structural Variants from Next-Generation Sequencing Data
title_sort detection of genomic structural variants from next-generation sequencing data
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479793/
https://www.ncbi.nlm.nih.gov/pubmed/26161383
http://dx.doi.org/10.3389/fbioe.2015.00092
work_keys_str_mv AT tattinilorenzo detectionofgenomicstructuralvariantsfromnextgenerationsequencingdata
AT daurizioromina detectionofgenomicstructuralvariantsfromnextgenerationsequencingdata
AT magialberto detectionofgenomicstructuralvariantsfromnextgenerationsequencingdata