Integrative analysis of metabolome and transcriptome profiles to highlight aroma determinants in Aglianico and Falanghina grape berries

Abstract

Background: The biochemical makeup of grape berries at harvest is essential for wine quality and depends on a fine transcriptional regulation occurring during berry development. In this study, we conducted a comprehensive survey of transcriptomic and metabolomic changes occurring in different berry tissues and developmental stages of the ancient grapes Aglianico and Falanghina to establish the patterns of the secondary metabolites contributing to their wine aroma and investigate the underlying transcriptional regulation.

Results: Over two hundred genes related to aroma were found, of which 107 were differentially expressed in Aglianico and 99 in Falanghina. Similarly, 68 volatiles and 34 precursors were profiled in the same samples. Our results showed a large extent of transcriptomic and metabolomic changes at the level of isoprenoids (terpenes, norisoprenoids), green leaf volatiles (GLVs), and amino acid pathways, although the terpenoid metabolism was the most distinctive for Aglianico, and GLVs for Falanghina. Co-expression analysis that integrated metabolome and transcriptome data pinpointed 25 hub genes as points of biological interest in defining the metabolic patterns observed. Among them, three hub genes encoding for terpenes synthases (VvTPS26, VvTPS54, VvTPS68) in Aglianico and one for a GDP-L-galactose phosphorylase (VvGFP) in Falanghina were selected as potential active player underlying the aroma typicity of the two grapes.

Conclusion: Our data improve the understanding of the regulation of aroma-related biosynthetic pathways of Aglianico and Falanghina and provide valuable metabolomic and transcriptomic resources for future studies in these varieties.

Keywords: Amino acids; Green leaf volatiles; Norisoprenoids; RNASeq; Terpenoids; WGCNA.

Fig. 1

Biosynthetic pathway of terpenes in Aglianico and Falanghina. The expression levels of DEGs are reported in boxes with a yellow-green scale, while the accumulation of DAMs is in boxes with a blue-red scale. Per each transcript/metabolite, the abundance levels are represented by heatmaps, in which the blocks shown from left to right represent the four comparisons Skin_VvsPV, Skin_RvsPV, Pulp_VvsPV and Pulp_RvsPV in Aglianico and Falanghina, shorten as SV, SR, PV and PR, respectively. DEGs missing data are in grey, while DAMs missing data in orange

Fig. 2

Biosynthetic pathway of carotenoids/apocarotenoids in Aglianico and Falanghina. The expression levels of DEGs are reported in boxes with a yellow-green scale, while the accumulation of DAMs is in boxes with a blue-red scale. Per each transcript/metabolite, the abundance levels are represented by heatmaps, in which the blocks shown from left to right represent the four comparisons Skin_VvsPV, Skin_RvsPV, Pulp_VvsPV, and Pulp_RvsPV in Aglianico and Falanghina, shorten as SV, SR, PV and PR, respectively. DEGs missing data are in grey, while DAMs missing data in orange

Fig. 3

Biosynthetic pathway of GLVs in Aglianico and Falanghina. The expression levels of DEGs are reported in boxes with a yellow-green scale, while the accumulation of DAMs is in boxes with a blue-red scale. Per each transcript/metabolite, the abundance levels are represented by heatmaps, in which the blocks shown from left to right represent the four comparisons Skin_VvsPV, Skin_RvsPV, Pulp_VvsPV, and Pulp_RvsPV in Aglianico and Falanghina, shorten as SV, SR, PV and PR, respectively. DEGs missing data are in grey, while DAMs missing data in orange

Fig. 4

Correlation of the identified modules with the content of volatile metabolites and their precursors in Aglianico (A) and Falanghina (B). Red and green color notes positive and negative correlations with gene expression, respectively