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.