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

BMC Biotechnol. 2009 Oct 8;9:87. doi: 10.1186/1472-6750-9-87.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Arabidopsis / genetics
  • Computational Biology / methods*
  • DNA, Complementary / genetics
  • Expressed Sequence Tags
  • Gene Library
  • Genetic Engineering / methods*
  • Plants, Genetically Modified / genetics*
  • RNA, Plant / genetics
  • Sequence Analysis, RNA / methods*


  • DNA, Complementary
  • RNA, Plant