Methodology article

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

Torstein Tengs¹ , Haibo Zhang^1,2 , Arne Holst-Jensen¹ , Jon Bohlin³ , Melinka A Butenko⁴ , Anja Bråthen Kristoffersen³ , Hilde-Gunn Opsahl Sorteberg⁵ and Knut G Berdal¹

¹National Veterinary Institute, Section for Food Bacteriology and GMO, PO Box 750 Sentrum, 0106 Oslo, Norway

²School of Life Science and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China

³National Veterinary Institute, Section for Epidemiology, PO Box 750 Sentrum, 0106 Oslo, Norway

⁴University of Oslo, Department of Molecular Biosciences, PO Box 1041, Blindern, 0316 Oslo, Norway

⁵Agricultural University of Norway, Department of Plant and Environmental Sciences, PO Box 5003, 1432 Ås, Norway

author email corresponding author email

BMC Biotechnology 2009, 9:87doi:10.1186/1472-6750-9-87

Published:	8 October 2009

Abstract

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.