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Background  Molecular characterization is an essential step of risk/safety assessment of genetically modified (GM) crops. Holistic approaches for molecular characterization using  omics  platforms can be used to confirm the intended impact of the genetic engineering, but can also reveal the unintended changes at the  omics  level as a first assessment of potential risks. The potential of  omics  platforms for risk assessment of GM crops has rarely been used for this purpose because of the lack of a consensus reference and statistical methods to judge the significance or importance of the pleiotropic changes in GM plants. Here we propose a  meta data  analysis approach to the analysis of GM plants, by measuring the transcriptome distance to untransformed wild-types.    Results  In the statistical analysis of the transcriptome distance between GM and wild-type plants, values are compared with naturally occurring transcriptome distances in non-GM counterparts obtained from a database. Using this approach we show that the pleiotropic effect of genes involved in indirect insect defence traits is substantially equivalent to the variation in gene expression occurring naturally in  Arabidopsis .    Conclusion  Transcriptome distance is a useful screening method to obtain insight in the pleiotropic effects of genetic modification.

Assessment of pleiotropic transcriptome perturbations in Arabidopsis engineered for indirect insect defence