Multivariate Analysis Tools Allow Visualization of Coregulated Genes and Hormones, and Reveal Contrasts between Treatments and Genotypes
Many individual changes in transcript and hormone levels are reported here, with significance initially assessed by univariate procedures based on ANOVA (Supplemental Tables S2 and S3). To aid visualization and interpretation of the complex relationships, we subjected all data sets to multivariate analysis. Similar approaches were reported in relation to hormonal regulation of dormancy (Chope et al., 2012) and responses to abiotic stresses (Albacete et al., 2010; Pinheiro et al., 2011). Such analyses facilitate detection of groupings of variables and discrimination of differences between genotypes and treatments. We used the shifts between clusters of genotypes and treatments from the transcript and hormone scores plots (Figs. 3B and 7, B and E) to infer the principal effects associated with decapitation, root removal, auxin response, and SL deficiency. The overall trends are depicted in Figures 3C and 7, C and F, as arrows derived from geometric means of means for each of these factors. Directions of the arrows enable deduction of the main transcripts and hormones affected, by comparing with directions on the loadings plots (Figs. 3A and 7, A and D). Some trends matched predictions, such as the opposite responses to auxin and decapitation for auxin transporter and IPT expression in stems, with the latter positively correlated with levels of stem CKs.
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