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

Revealing insect herbivory‐induced phenolamide metabolism: from single genes to metabolic network plasticity analysis

“…Indeed, most induced defense secondary metabolism genes investigated in N. attenuata in the context of W+OS treatments show amplified expression in response to by OS‐activated mobile signals that are transported into systemic tissues from OS‐elicited ones (Schittko et al ., ; Schittko and Baldwin, ; Kim et al ., ; Gulati et al ., ). This further confirms that only OS perception alone, but not mechanical wounding alone, leads to deployment of robust systemic signals (Gulati et al ., ,b).…”

“…Experiments designed to assess the dynamic rewiring of the gene networks that control the spread of herbivory‐induced systemic responses often have a complex factorial structure resulting from the different conditions/treatments and tissue types analyzed, and necessarily involve time‐series analysis. Based on the targeted interpretation of metabolic gene regulation presented above, we recently designed a dimensionality reduction method based on multifactorial analysis to categorize genes according to their degree of tissue specificity and responses to W+OS elicitation (Gulati et al ., ,b) (Figure ). The procedure utilizes bootstrap‐based non‐parametric anova models implemented in the R package tanova (Zhou et al ., ; Zhou and Wong, ).…”

“…(a) A multifactorial analysis workflow was developed by Gulati et al . (,b)z. This strategy was applied to analysis of multidimensional transcriptomic datasets acquired from multifactorial experimental designs (different tissue types, treatment, etc…) including time‐series experiments.…”

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology

“…A plant defence response is a highly dynamic process and the defence transcriptome is differentially regulated in time and space. From several microarray experiments conducted to uncover transcriptional response patterns to different abiotic and biotic stresses, it is now understood that the transcriptional response initially is composed of a core set of genes responsive to multiple stresses, but becomes gradually more stress specific (De Vos et al, 2005;Eulgem, 2005;Gulati et al, 2013). The chronology and co-ordinated regulation of such a defence transcriptome can be deciphered by employing high-resolution temporal transcriptomic analysis as demonstrated by Windram et al (2012), generating data from 24 time points using 2 h intervals over a 48 h period (Windram et al, 2012).…”

“…VirtualPlant integrates genomic data and provides visualization and analysis tools for rapid and efficient exploration of genomic data (Katari et al, 2010). Gulati et al (2013) have described an integrative statistical method to explore herbivory-specific responses in plants through the construction of interactive motifs by combining an extended self-organizing maps-(SOM) based dimensionality reduction method with bootstrap-based non-parametric analysis of variance (ANOVA) models.…”