Current safety assessment for novel crops, including transgenic crops, uses a targeted approach, which relies on compositional analysis. The possibility that transgene expression could lead to unintended effects remains a debated issue. This study used transcriptome profiling as a nontargeted approach to evaluate overall molecular changes in transgenic soybean cultivars. Global gene expression was measured in the first trifoliate leaves of two transgenic and three conventional soybean cultivars using the soybean Affymetrix GeneChip. It was found that gene expression differs more between the two conventional cultivars than between the transgenics and their closest conventional cultivar investigated and that the magnitudes of differences measured in gene expression and genotype (determined by SSR analysis) do not necessarily correlate. A MySQL database coupled with a CGI Web interface was developed to store and present the results ( http://soyxpress.agrenv.mcgill.ca/). By integrating the microarray data with gene annotations and other soybean data, a comprehensive view of differences in gene expression is explored between cultivars.

Background: Experiments using whole transcriptome microarrays produce massive amounts of data. To gain a comprehensive understanding of this gene expression data it needs to be integrated with other available information such as gene function and metabolic pathways. Bioinformatics tools are essential to handle, organize and interpret the results. To date, no database provides whole transcriptome analysis capabilities integrated with terms describing biological functions for soybean (Glycine max (L) Merr.). To this end we have developed SoyXpress, a relational database with a suite of web interfaces to allow users to easily retrieve data and results of the microarray experiment with cross-referenced annotations of expressed sequence tags (EST) and hyperlinks to external public databases. This environment makes it possible to explore differences in gene expression, if any, between for instance transgenic and non-transgenic soybean cultivars and to interpret the results based on gene functional annotations to determine any changes that could potentially alter biological processes.

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