Cargando…

Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction

BACKGROUND: When generating a genetically modified organism (GMO), the primary goal is to give a target organism one or several novel traits by using biotechnology techniques. A GMO will differ from its parental strain in that its pool of transcripts will be altered. Currently, there are no methods...

Descripción completa

Detalles Bibliográficos
Autores principales: Tengs, Torstein, Zhang, Haibo, Holst-Jensen, Arne, Bohlin, Jon, Butenko, Melinka A, Kristoffersen, Anja Bråthen, Sorteberg, Hilde-Gunn Opsahl, Berdal, Knut G
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764706/
https://www.ncbi.nlm.nih.gov/pubmed/19814792
http://dx.doi.org/10.1186/1472-6750-9-87
_version_ 1782173122050392064
author Tengs, Torstein
Zhang, Haibo
Holst-Jensen, Arne
Bohlin, Jon
Butenko, Melinka A
Kristoffersen, Anja Bråthen
Sorteberg, Hilde-Gunn Opsahl
Berdal, Knut G
author_facet Tengs, Torstein
Zhang, Haibo
Holst-Jensen, Arne
Bohlin, Jon
Butenko, Melinka A
Kristoffersen, Anja Bråthen
Sorteberg, Hilde-Gunn Opsahl
Berdal, Knut G
author_sort Tengs, Torstein
collection PubMed
description BACKGROUND: When generating a genetically modified organism (GMO), the primary goal is to give a target organism one or several novel traits by using biotechnology techniques. A GMO will differ from its parental strain in that its pool of transcripts will be altered. Currently, there are no methods that are reliably able to determine if an organism has been genetically altered if the nature of the modification is unknown. RESULTS: We show that the concept of computational subtraction can be used to identify transgenic cDNA sequences from genetically modified plants. Our datasets include 454-type sequences from a transgenic line of Arabidopsis thaliana and published EST datasets from commercially relevant species (rice and papaya). CONCLUSION: We believe that computational subtraction represents a powerful new strategy for determining if an organism has been genetically modified as well as to define the nature of the modification. Fewer assumptions have to be made compared to methods currently in use and this is an advantage particularly when working with unknown GMOs.
format Text
id pubmed-2764706
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-27647062009-10-21 Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction Tengs, Torstein Zhang, Haibo Holst-Jensen, Arne Bohlin, Jon Butenko, Melinka A Kristoffersen, Anja Bråthen Sorteberg, Hilde-Gunn Opsahl Berdal, Knut G BMC Biotechnol Methodology Article BACKGROUND: When generating a genetically modified organism (GMO), the primary goal is to give a target organism one or several novel traits by using biotechnology techniques. A GMO will differ from its parental strain in that its pool of transcripts will be altered. Currently, there are no methods that are reliably able to determine if an organism has been genetically altered if the nature of the modification is unknown. RESULTS: We show that the concept of computational subtraction can be used to identify transgenic cDNA sequences from genetically modified plants. Our datasets include 454-type sequences from a transgenic line of Arabidopsis thaliana and published EST datasets from commercially relevant species (rice and papaya). CONCLUSION: We believe that computational subtraction represents a powerful new strategy for determining if an organism has been genetically modified as well as to define the nature of the modification. Fewer assumptions have to be made compared to methods currently in use and this is an advantage particularly when working with unknown GMOs. BioMed Central 2009-10-08 /pmc/articles/PMC2764706/ /pubmed/19814792 http://dx.doi.org/10.1186/1472-6750-9-87 Text en Copyright © 2009 Tengs et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Tengs, Torstein
Zhang, Haibo
Holst-Jensen, Arne
Bohlin, Jon
Butenko, Melinka A
Kristoffersen, Anja Bråthen
Sorteberg, Hilde-Gunn Opsahl
Berdal, Knut G
Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
title Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
title_full Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
title_fullStr Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
title_full_unstemmed Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
title_short Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
title_sort characterization of unknown genetic modifications using high throughput sequencing and computational subtraction
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764706/
https://www.ncbi.nlm.nih.gov/pubmed/19814792
http://dx.doi.org/10.1186/1472-6750-9-87
work_keys_str_mv AT tengstorstein characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT zhanghaibo characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT holstjensenarne characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT bohlinjon characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT butenkomelinkaa characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT kristoffersenanjabrathen characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT sorteberghildegunnopsahl characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction
AT berdalknutg characterizationofunknowngeneticmodificationsusinghighthroughputsequencingandcomputationalsubtraction