Unraveling the complexity of transcriptomic, metabolomic and quality environmental response of tomato fruit

Abstract

Background: The environment has a profound influence on the organoleptic quality of tomato (Solanum lycopersicum) fruit, the extent of which depends on a well-regulated and dynamic interplay among genes, metabolites and sensorial attributes. We used a systems biology approach to elucidate the complex interacting mechanisms regulating the plasticity of sensorial traits. To investigate environmentally challenged transcriptomic and metabolomic remodeling and evaluate the organoleptic consequences of such variations we grown three tomato varieties, Heinz 1706, whose genome was sequenced as reference and two "local" ones, San Marzano and Vesuviano in two different locations of Campania region (Italy).

Results: Responses to environment were more pronounced in the two "local" genotypes, rather than in the Heinz 1706. The overall genetic composition of each genotype, acting in trans, modulated the specific response to environment. Duplicated genes and transcription factors, establishing different number of network connections by gaining or losing links, play a dominant role in shaping organoleptic profile. The fundamental role of cell wall metabolism in tuning all the quality attributes, including the sensorial perception, was also highlighted.

Conclusions: Although similar fruit-related quality processes are activated in the same environment, different tomato genotypes follow distinct transcriptomic, metabolomic and sensorial trajectories depending on their own genetic makeup.

Keywords: Environment; Fruit quality; Metabolome; Network; Plasticity; Sensorial attributes; Solanum lycopersicum; Transcriptome.

Fig. 1

Changes in gene expression profiles. a Letters in figure legends should be in uppercase Number of up-regulated genes identified in the two locations (Ac and Sa) for the three genotypes analyzed (H, SM and RSV). b, c and d List of top 10 up-regulated genes in both locations in H, SM and RSV, respectively. ACS: 1-aminocyclopropane-1-carboxylate synthase, PAL: Phenylalanine ammonia-lyase, MLP: Major latex-like protein, LOX: Lipoxygenase, MSP: Male sterility 5 family protein PPase: Pyrophosphate-energized proton pump, GASA2: Gibberellin-regulated protein 2, LHC: Chlorophyll a/b binding protein, ERF9: Ethylene-responsive transcription factor 9, EXO: Exocyst complex protein EXO70, PUB: U-box domain-containing protein, MORC: MORC family CW-type zinc finger 3, Ole e 1: Pollen Ole e 1 allergen and extensin, XPR1: Xenotropic and polytropic retrovirus receptor, PUB15: U-box domain-containing protein 15. Asterisks indicate genes absent in one location. To avoid an infinite fold-change of transcripts that did not express in one location, transcripts were augmented with small fragments per million of mapped reads (FPKM, 0,0001) prior to binary logarithmic transformation add a point at end od each legend

Fig. 2

Gene ontology enrichment analysis. a Scheme for classifying over-represented gene classes. For each genotype Acerra-specific (Ac) and Sarno-specific (Sa) enriched GO terms were identified. Enriched GO terms common to both environments (G) in each genotype (H, SM and RSV) were also identified. By crossing enriched GO terms in Acerra from all three genotypes, Acerra-specific and Acerra × Genotype interactions were identified. The same scheme was used to identify Sarno-specific enriched GO terms as well as Sarno × Genotype interactions. b Environment-specific enriched GO categories. Left) Acerra-specific enriched GO terms. Right) Sarno-specific enriched GO terms. c San Marzano GO Enrichment Analysis. The Venn diagram shows common and specific enriched GO terms. Bar plots reflect the percentage of genes in the enriched categories of the San Marzano Acerra (left), Sarno (right) and common (below), as well as the percentage of genes belonging to the same categories in tomato genome. Common enriched GO categories are reported for both environments because some categories, although enriched in both conditions, have a different percentage of genes. m.p. = metabolic process, b.p. = biological process, c.p. = catabolic process

Fig. 3

Outliers gene detection. Frequency distribution of fold change (FC) classes between locations in each enriched GO category in SM Acerra (a) and Sarno (b). Right: heat map of FPKM (Fragments per million of mapped reads) values for outlier genes in SM Acerra and SM Sarno. Green, yellow and blue indicate medium, low and high FPKM levels, respectively

Fig. 4

Molecular regulation of gene expression in SM. a DEGs mapped to the transcriptional regulation process (left). SM DE Transcription factor classification (right). b DEGs mapped to post-translational regulation process (left). SM DEGs mapped to ubiquitin dependent degradation process. c Number of up-regulated isoforms identified in the three genotypes in both locations. d DEI assigned to fruit quality metabolic pathways in each genotype

Fig. 5

Changes in metabolic profiles. a Separation of metabolic profiles for each genotype between the two environments. b Total number of varied metabolites between the two environments for each genotype and distribution of abundant metabolites for each genotype in the two locations. c Number of common varied metabolites in Acerra (Ac) and Sarno (Sa) as well genotypic specific varied metabolites in each localities. d Principal Component Analysis on changed metabolites between the two locations for each genotype (H on the left, SM in the middle, RSV on the right)

Fig. 6

Schematic representation of the changes in metabolic content between Acerra and Sarno in SM fruits. Red = increased level in Acerra. Green = increased level in Sarno. Gray = not changed. Blue = only present in Acerra. Orange = only present in Sarno. White = not measured. Similar representations for H and RSV are shown in Figs S9 and S10

Fig. 7

Changes in sensorial attributes. Principal component analysis (PCA) showing dimension parameters (Dim) 1 and 2 for all fruit quality attributes with projection of sensory descriptors for each genotype

Fig. 8

Network analysis of E effects on SM. a Xyloglucan endotransglucosylase/hydrolase 9 (Solyc03g093130) sub-network. b Xyloglucan endotransglycosylase family network

Fig. 9

Sensory attribute-specific network analysis of SM. Flavor and aroma sub-network

Fig. 10

Quantitative real-time RT-PCR (qPCR) analysis. San Marzano variety (SM) responsive genes involved in fruit quality pathways. The expression level of each gene is normalized by using a reference gene, Elongation Factor and then calculated as relative level in Sarno to in Acerra (control). qPCR data are presented as means ± SD for three biological replicates