# Pigment-Related Mutations Greatly Affect Berry Metabolome in San Marzano Tomatoes
## 3 Results
### Univariate Analysis of NP, P, and VOC Metabolites in the Four Mutated Lines
Indeed, \(\alpha\)- and \(\gamma\)-tocopherol (vitamin E) decreased and increased, respectively, in _pd_ and _hp-2/Aff_atv_; similarly, phylloquinone (vitamin K) was characterized by higher and lower levels in _hp-2_ and _pd_, respectively, whereas ubiquinone-9 and 10 (coenzyme Q9 and Q10, respectively) were higher in _hp-2/Aff_atv_ and lower in _hp-1_ (the former) and increased in _pd_ (the latter). Finally, ascorbic acid (vitamin C) was found to be more abundant in _hp-2_ and _Af_atv_ and reduced in _hp-1_ (Figure S1). To investigate the relationships between the different metabolic classes analyzed in the four mutated lines, we used correlation-based network analysis in which the nodes represent compounds and the edges between them the significant [PERSON]'s correlation coefficients (\(\rho\); Figure S2 and Table S5). The obtained geometry allowed the realization of specific topologies according to the distribution of the significant interactions existing between P, NP, and VOC metabolites; in particular, several areas with interesting inter  
Figure 5: Schematic representation of the PP pathway in tomato genotypes: metabolites showing significant changes in at least one comparison with the WT are represented by heatmaps in different shades of red (over-accumulated) and blue (down-accumulated) for _hp-1_, _hp-2_, _pd_, and _Aff_atv_ (from left to right). *, **, and *** indicate variations from the WT significant at \(p\leq\) 0.05, 0.01, and 0.001, respectively, after Student’s _t_-test. In white, data showing no alteration in metabolite accumulation; in gray, undetectable metabolites. actions were observed, with both direct (PHEs, CARs and CARs with QUIs and TOCs) and inverse (CARs and volatile Cs) relationships. Moreover, nodes with high density of negative correlations, known as negative hubs, were highlighted: 3-methyl butanoic acid, methanethiol, 2-methyl-butenal, and phytoene. For a better elucidation of the strongest correlations, MCODE was used to evidence the regions with the highest number of statistically significant (thus powerful) interactions (Figure 6a-e). It was thus possible to identify several interesting subnetworks which were not clearly visible using the global network view; indeed, a large extent of positive interactions was observed between CARs (lutein and \(\alpha\)-carotene) and PHEs (quercetin and quercetin glucosides) but also QUIs (phylloquinone and plastoquinones), and TOCs (\(\alpha\)-tocopherol; Figure 6b). Another interesting subnetwork was characterized by the inverse correlation between SAPs and PHEs (Figure 6c). On the contrary, and unexpectedly, a series of negative correlations was observed, such as the one between phytoene and PHEs (Figure 6d). To explore the mutual relationships between analyzed compounds belonging to different metabolic classes in the four mutated lines, we calculated [PERSON]'s correlation coefficients for the fold change of all metabolite pairs. Significant correlations emerged from the matrix of this analysis (Figure S3). Among NP compounds, almost all CARs (phytoene, phytofluene, \(\zeta\)-carotene, lycopene, \(\alpha\)-carotene, lutein, \(\gamma\)-carotene, \(\beta\)-carotene,  
Figure 6: Subnetworks related to _hp-1_, _hp-2_, _pd_, and _Af_atv_ and generated from the global network present in Figure S2. Each subnetwork (**a–e**) highlights the high densely connected regions present in the global network. Each node represents a P (triangle), NP (diamond), or a VOC (circle) metabolite. Lines joining the nodes represent correlations; direct correlations are shown in red, while inverse correlations are in blue. Node sizes are proportional to the respective node strengths (Table S5). The color of the node depends on the metabolic class membership as reported on the top. The number of nodes (n) is shown on top of each network. Only correlations with \(\mid\rho\mid>0.95\) are shown (\(p\)-value \(\leq 0.05\)).