Selection of the best comparator for the risk assessment of GM plants- conventional counterpart vs. negative segregant

Fonseca, Cátia; Planchon, Sébastien; Serra, Tânia; Chandler, Subhash; Saibo, Nelson; Renaut, Jenny; Oliveira, Margarida; Batista, Rita

http://hdl.handle.net/10400.18/1030

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
poster_ISBGMO12.pdf		1.09 MB	Adobe PDF	Download

Send Feedback

Authors

Abstract(s)

Abstract for 12th international Symposium on biosafety of genetically modified organisms The identification of similarities and differences between GM plants and derived food/feed and their comparators plays a central role in risk assessment strategy. Therefore, selecting the right comparators must be one of the top priorities. The question is which control would allow us to better evaluate the potential unintended effects related directly to the transgene and/or DNA rearrangements, discounting the potential effects caused by in vitro culture procedures; since, these are non-controversial procedures also used in conventional breeding. Aiming to answer the previous question we have used Multiplex fluorescence 2D gel electrophoresis technology (DyeAGNOSTICS Refraction-2D) coupled with MS to characterize the proteome of three different rice lines (Oriza sativa L. ssp. Japonica cv Nipponbare): A control conventional counterpart. An Agrobacterium transformed transgenic line. A negative segregant (homozygous negative progeny) from a different transgenic line. We have observed that transgenic and negative segregant plant lines grouped together (only 1 differentially regulated spot - fold difference > 1.5, ANOVA, P<0.05,) and apart from control (49 spots with fold difference >1.5, ANOVA, P<0.05, in both transgenic and negative segregant lines comparing to control line). Additionally, the 35 proteins identified (using MS) in this study, were already associated with stress response by other authors. The only feature in common between the transgenic and negative segregant lines is that they have both suffered in vitro culture procedures. Hence, the results obtained indicate that, in this study, different gene disruption and/or DNA rearrangements and the presence/absence of transgene were factors with less impact on rice proteome than the proteomic promoted differences caused by in vitro culture, and eventually the stress caused by this process. This work highlights the importance of continuous revision and upgrade of the guidance criteria to be followed for the selection of suitable comparators in GMO risk assessment.