An integrative statistical method to explore herbivory-specific responses in plants.

Spatial-temporal coordination between multiple processes/pathways is a key determinant of whole-organism transcriptome and metabolome reconfigurations in plants' response to biotic stresses. To explore tissue-based interdependencies in Nicotiana attenuata's resistance to insect attack, we performed time course analyses of the plant's transcriptome and metabolome in herbivory-elicited source leaves and unelicited sink leaves and roots. To dissect the multidimensionality of these responses, we have recently designed a novel approach of constructing interactive motifs by combining an extended self-organizing maps (SOM) based dimensionality reduction method with bootstrap-based non-parametric AN OVA models. In this previous study, we used this method to study nonlinearities in gene-metabolite associations involved in the acyclic diterpene glucoside pathway. Here, we extend the application of this method to the extraction of genes showing herbivory-elicitation specifically in systemic (distal from the treatment sites) tissues using motif analysis for different combinations of treatment applied to Nicotiana attenuata.