Correlation analyses of isoprenoid accumulation in the various accessions and in the mapping population- a statistical meta-analysis
As a final step, we conducted a detailed statistical meta-analysis of the studied traits in the different Arabidopsis accessions and in the lines of the EstC mapping population. Numerous correlations were found for the content of seven isoprenoid compounds estimated in the seedlings of natural accessions and the mapping population (Figure 5A and 5B, respectively). Moreover, we clearly identified some outliers (Grubbs test at significance level α=0.001) (Grubbs 1950). For plastoquinone, seven values corresponding to three accessions (Er-0, Est-1, and Fei-0) were unequivocally assigned as outliers, for carotenoids – three values corresponding to a single accession (Ren-1), for phytosterols a single outlier was identified in the natural accessions and for Dols in the mapping population (Figure S7). All these outliers, denoted by red triangles in Figure 5, were filtered out in the statistical analysis of metabolite distribution and the correlation analyses (Figure 5A and 5B). For both datasets, the analysis of metabolite correlations revealed the highest correlation for chlorophylls vs. carotenoids (R>0.97), while four other metabolites – phytosterols, Prens, plastoquinone, and Dols – also correlated with each other significantly (p<0.0001) Table S6. Tocopherol accumulation correlated only occasionally with the other metabolites (Table S6). Based on the structural similarity between Prens and Dols, some level of similarity between the mechanisms of their accumulation might be expected. However, the obtained values for the correlation between Prens and Dols among the tested accessions (0.325, p=0.0001) and among the AI-RILs (0.608, p=0.0001) suggest differences between these two subgroups of polyisoprenoids. Relationships between levels of metabolites analyzed in this report were also confirmed using hierarchical clustering Figure S8.
Importantly, all the strongest genetic correlations detected for particular metabolites (Table S4) were also identified as the most significant (p <0.0001) for metabolic data-based analysis and this is valid both for the natural accessions and for the EstC mapping population lines (Table S6). Moreover, a consistent trend of correlations (either positive or negative) between individual metabolites in the natural accessions was observed for both genetic- and metabolic-based analysis (Table S4 and Table S6). Taken together, results of the meta-analysis indicate genetic co-regulation of the biosynthesis of specific isoprenoids.