Cargando…

Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing

Integration of viral vectors into a host genome is associated with insertional mutagenesis and subjects in clinical gene therapy trials must be monitored for this adverse event. Several PCR based methods such as ligase-mediated (LM) PCR, linear-amplification-mediated (LAM) PCR and non-restrictive (n...

Descripción completa

Detalles Bibliográficos
Autores principales: Gao, Hongyu, Hawkins, Troy, Jasti, Aparna, Chen, Yu-Hsiang, Mockaitis, Keithanne, Dinauer, Mary, Cornetta, Kenneth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423470/
https://www.ncbi.nlm.nih.gov/pubmed/28548067
http://dx.doi.org/10.3390/biomedicines2020195
_version_ 1783234953033547776
author Gao, Hongyu
Hawkins, Troy
Jasti, Aparna
Chen, Yu-Hsiang
Mockaitis, Keithanne
Dinauer, Mary
Cornetta, Kenneth
author_facet Gao, Hongyu
Hawkins, Troy
Jasti, Aparna
Chen, Yu-Hsiang
Mockaitis, Keithanne
Dinauer, Mary
Cornetta, Kenneth
author_sort Gao, Hongyu
collection PubMed
description Integration of viral vectors into a host genome is associated with insertional mutagenesis and subjects in clinical gene therapy trials must be monitored for this adverse event. Several PCR based methods such as ligase-mediated (LM) PCR, linear-amplification-mediated (LAM) PCR and non-restrictive (nr) LAM PCR were developed to identify sites of vector integration. Coupling the power of next-generation sequencing technologies with various PCR approaches will provide a comprehensive and genome-wide profiling of insertion sites and increase throughput. In this bioinformatics study, we aimed to develop and apply quality metrics to viral insertion data obtained using next-generation sequencing. We developed five simple metrics for assessing next-generation sequencing data from different PCR products and showed how the metrics can be used to objectively compare runs performed with the same methodology as well as data generated using different PCR techniques. The results will help researchers troubleshoot complex methodologies, understand the quality of sequencing data, and provide a starting point for developing standardization of vector insertion site data analysis.
format Online
Article
Text
id pubmed-5423470
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-54234702017-05-23 Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing Gao, Hongyu Hawkins, Troy Jasti, Aparna Chen, Yu-Hsiang Mockaitis, Keithanne Dinauer, Mary Cornetta, Kenneth Biomedicines Article Integration of viral vectors into a host genome is associated with insertional mutagenesis and subjects in clinical gene therapy trials must be monitored for this adverse event. Several PCR based methods such as ligase-mediated (LM) PCR, linear-amplification-mediated (LAM) PCR and non-restrictive (nr) LAM PCR were developed to identify sites of vector integration. Coupling the power of next-generation sequencing technologies with various PCR approaches will provide a comprehensive and genome-wide profiling of insertion sites and increase throughput. In this bioinformatics study, we aimed to develop and apply quality metrics to viral insertion data obtained using next-generation sequencing. We developed five simple metrics for assessing next-generation sequencing data from different PCR products and showed how the metrics can be used to objectively compare runs performed with the same methodology as well as data generated using different PCR techniques. The results will help researchers troubleshoot complex methodologies, understand the quality of sequencing data, and provide a starting point for developing standardization of vector insertion site data analysis. MDPI 2014-05-06 /pmc/articles/PMC5423470/ /pubmed/28548067 http://dx.doi.org/10.3390/biomedicines2020195 Text en © 2014 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 license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Gao, Hongyu
Hawkins, Troy
Jasti, Aparna
Chen, Yu-Hsiang
Mockaitis, Keithanne
Dinauer, Mary
Cornetta, Kenneth
Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing
title Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing
title_full Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing
title_fullStr Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing
title_full_unstemmed Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing
title_short Development and Evaluation of Quality Metrics for Bioinformatics Analysis of Viral Insertion Site Data Generated Using High Throughput Sequencing
title_sort development and evaluation of quality metrics for bioinformatics analysis of viral insertion site data generated using high throughput sequencing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423470/
https://www.ncbi.nlm.nih.gov/pubmed/28548067
http://dx.doi.org/10.3390/biomedicines2020195
work_keys_str_mv AT gaohongyu developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing
AT hawkinstroy developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing
AT jastiaparna developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing
AT chenyuhsiang developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing
AT mockaitiskeithanne developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing
AT dinauermary developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing
AT cornettakenneth developmentandevaluationofqualitymetricsforbioinformaticsanalysisofviralinsertionsitedatageneratedusinghighthroughputsequencing