Flavonoid deficiency disrupts redox homeostasis and terpenoid biosynthesis in glandular trichomes of tomato.

Glandular trichomes (GTs) are epidermal structures that provide the first line of chemical defense against arthropod herbivores and other biotic threats. The most conspicuous structure on leaves of cultivated tomato (Solanum lycopersicum) is the type-VI GT (tVI-GT), which accumulates both flavonoids and volatile terpenoids. Although these classes of specialized metabolites are derived from distinct metabolic pathways, previous studies with a chalcone isomerase 1 (CHI1)-deficient mutant called anthocyanin free (af) showed that flavonoids are required for terpenoid accumulation in tVI-GTs. Here, we combined global transcriptomic and proteomic analyses of isolated trichomes as a starting point to show that the lack of CHI1 is associated with reduced levels of terpenoid biosynthetic transcripts and enzymes. The flavonoid deficiency in af trichomes also resulted in the upregulation of abiotic stress-responsive genes associated with DNA damage and repair. Several lines of biochemical and genetic evidence indicate that the terpenoid defect in af mutants is specific for the tVI-GT and is associated with the absence of bulk flavonoids rather than loss of CHI1 per se. A newly developed genome-scale model of metabolism in tomato tVI-GTs helped identify metabolic imbalances caused by the loss of flavonoid production. We provide evidence that flavonoid deficiency in this cell type leads to increased production of reactive oxygen species (ROS), which may impair terpenoid biosynthesis. Collectively, our findings support a role for flavonoids as ROS-scavenging antioxidants in GTs.

Variability in drought gene expression datasets highlight the need for community standardization.

Physiologically relevant drought stress is difficult to apply consistently, and the heterogeneity in experimental design, growth conditions, and sampling schemes make it challenging to compare water deficit studies in plants. Here, we re-analyzed hundreds of drought gene expression experiments across diverse model and crop species and quantified the variability across studies. We found that drought studies are surprisingly uncomparable, even when accounting for differences in genotype, environment, drought severity, and method of drying. Many studies, including most Arabidopsis work, lack high-quality phenotypic and physiological datasets to accompany gene expression, making it impossible to assess the severity or in some cases the occurrence of water deficit stress events. From these datasets, we developed supervised learning classifiers that can accurately predict if RNA-seq samples have experienced a physiologically relevant drought stress, and suggest this can be used as a quality control for future studies. Together, our analyses highlight the need for more community standardization, and the importance of paired physiology data to quantify stress severity for reproducibility and future data analyses.