Abstract

   The currently accepted paradigm is that fruits and vegetables should be
   consumed fresh and that their quality deteriorates during storage;
   however, there are indications that some metabolic properties can, in
   fact, be improved. We examined the effects of low temperature and
   high-CO[2] conditions on table grapes, Vitis vinifera L. cv. ‘Superior
   Seedless’. Berries were sampled at harvest (T0) and after
   low-temperature storage for 6 weeks under either normal atmosphere
   conditions (TC) or under an O[2] level of 5 kPa and elevated CO[2]
   levels of 5, 10 or 15 kPa (T5, T10, T15). Accumulation of 10 stilbenes,
   including E-ε-viniferin, E-miyabenol C and piceatannol, significantly
   increased under TC treatment as compared to T0 or T15. Sensory analysis
   demonstrated that elevated CO[2] elicited dose-dependent off-flavor
   accumulation. These changes were accompanied by an accumulation of 12
   volatile metabolites, e.g., ethyl acetate and diacetyl, that imparted
   disagreeable flavors to fresh fruit. Transcriptome analysis revealed
   enrichment of genes involved in pyruvate metabolism and the
   phenylpropanoid pathway. One of the transcription factors induced at
   low temperature but not under high CO[2] was VvMYB14, which regulates
   stilbene biosynthesis. Our findings reveal the potential to alter the
   levels of targeted metabolites in stored produce through understanding
   the effects of postharvest treatments.

Introduction

   A large proportion of fresh produce is stored and transported from
   production sites to markets. This has been made possible by
   technological developments and intensive postharvest research that
   facilitate long-term storage with minimal losses and quality
   impairment^[38]1. The basic postharvest technology uses cold storage to
   reduce respiration rate and decay; freshness is preserved mainly by
   packaging to retain humidity around the produce. Another level of
   protection, termed modified atmosphere (MA), is achieved by packaging
   produce in bags designed to maintain higher CO[2] and lower O[2] levels
   during postharvest respiration. In a controlled atmosphere (CA), CO[2]
   and O[2] contents are set to optimal levels in a closed environment.
   These optimal levels are calculated to ensure maximal quality, minimal
   decay, and minimal off-flavors that may be generated by the anaerobic
   respiration that results from O[2] reduction and CO[2] enhancement.

   Grape (Vitis vinifera L.) berries are non-climacteric fruits; they have
   low respiration rates and display high tolerance to postharvest cold
   stress^[39]2. Commercial storage of table grapes is carried out at 0 °C
   in the presence of SO[2]-emitting sheets to effectively inhibit the
   development of fungi, especially Botrytis cinerea^[40]3. CA and MA are
   widely used in postharvest storage of various produce^[41]4 but in
   table grapes, these technologies have been explored only in recent
   years, as alternatives to prevailing practices^[42]5.

   Although it is assumed that changes in table grape composition during
   cold storage are minimal, little is known about the metabolic processes
   that occur in grapes during postharvest cold storage. There is evidence
   that short-term exposure of table grapes to high CO[2] levels (20 kPa)
   for 48 to 72 h affects antioxidant activity, trans-resveratrol levels
   in berry skin and expression of genes associated with the
   phenylpropanoid pathway^[43]6,[44]7. Prolonged or suboptimal
   applications of CA or MA may cause a shift to alcoholic fermentation
   and development of off-flavors, because of accumulation of volatile
   pyruvate-degradation products, such as ethanol, acetaldehyde, ethyl
   acetate and acetone^[45]8. Although off-flavors have been reported to
   develop following CA storage of grapes^[46]9, information is lacking on
   the types and levels of the specific metabolites involved.

   The objective of the present research was to examine the effects of
   long-term postharvest treatments on flavor and health-promoting
   properties of table grapes. The results demonstrate that cold storage
   induced the accumulation of specific compounds with recognized
   health-promoting properties in grapes, whereas storage under reduced
   O[2] and elevated CO[2] levels impaired this effect. We also identified
   a set of compounds and metabolic processes associated with the
   development of off-flavors under limited O[2] and elevated CO[2]
   levels. This research may, therefore, open the way to understanding how
   storage conditions modulate gene expression; from a practical
   standpoint, it may lead to better tools for monitoring postharvest
   storage of table grapes.

Results

Off-flavors developed under elevated CO[2] levels are associated with the
accumulation of volatile compounds related to glycolysis

   Clusters of ‘Superior Seedless’ grapes were sampled after harvest (T0),
   after storage at low temperature for 6 weeks (TC) or after storage at
   low temperature under a constant O[2] level of 5 kPa and CO[2] levels
   of 5, 10 or 15 kPa (T5, T10 and T15, respectively). Figure [47]1A shows
   the percentages of tasters that categorized the grape berries as having
   no off-flavor or three levels of off-flavor. Half of the tasters
   noticed low or medium off-flavor at 10 kPa CO[2]; all tasters noticed
   off-flavor at 15 kPa CO[2], half of them registering high off-flavor
   scores. Partial least square - discriminant analysis (PLS-DA) for
   correlation between volatile compounds and off-flavor levels showed
   separation into three clusters: T0 first; TC, T5 and T10 joint second;
   and T15 third (Supplementary Fig. [48]S1A). Component 1 (67.6%)
   separated T15 from the other four. Therefore, correlation coefficients
   were examined for volatile compounds that correlated with T15 (high
   off-flavors) more strongly than with T0, TC, T5 and T10 (Supplementary
   Fig. [49]S1B). Twelve volatile compounds that were associated with
   perceived off-flavors included: pyruvate-degradation metabolites such
   as ethyl acetate, acetone, acetaldehyde, acetate, acetoin; and volatile
   compounds derived from diacetyl or branch-chain amino acids, such as
   3-methyl-1-butanol (L-leucine) (Fig. [50]1B, Supplementary
   Table [51]S1).

Figure 1.

   [52]Figure 1
   [53]Open in a new tab

   Increased levels of volatile compounds under elevated CO[2] conditions
   are associated to off-flavor in table grapes. Grape berries of
   ‘Superior Seedless’ after harvest (T0), after storage for 6 weeks at
   low temperature (TC) or after storage at low temperature under constant
   O[2] level of 5 kPa and CO[2] levels of 5, 10 and 15 kPa (T5, T10 and
   T15, respectively). (A) Mosaic plot based on sensory analysis results
   of T0, TC, T5, T10 and T15. Data shows percent of tasters that
   identified the berries as having no, low, medium or high off-flavor (B)
   PLS-DA coefficient scores of volatile compounds associated to high
   off-flavor in T0, TC, T5, T10 and T15 (Supplementary Fig. [54]1) and
   (C) estimated odor active value (OAV) of two compounds associated with
   off-flavor after harvest or after storage under different conditions
   (Supplementary Table [55]2). Levels of metabolites were analyzed based
   on three biological replications for each treatment (n = 3).

   Odor active values (OAV) serve as an estimator for the potential of a
   metabolite to affect the flavor of a given sample; values greater than
   one indicate a higher potential and represent higher concentrations of
   a given compound than its known odor threshold. Ethyl acetate had an
   OAV of 10 and diacetyl one of 1.4 in T15 (Fig. [56]1C); thus they are
   likely to emit disagreeable odors reminiscent of nail polish or milky
   compounds, respectively (Supplementary Table [57]S2).

A shift towards up-regulation of genes under elevated CO[2] and
down-regulation of genes under cold stress

   To further explore mechanisms underlying off-flavor accumulation,
   RNAseq analysis was applied to the grapes under T0, TC, and T15
   conditions. Heat-map analysis revealed the reproducibility of the
   replicates and the significant differences among the treatments
   (Supplementary Fig. [58]S2): a total of 6600 genes changed under the
   three sets of experimental conditions and the two thresholds used —
   LogFC > 1.5 and FDR < 0.05). Under cold-stress conditions 359 genes
   were up-regulated and 550 down-regulated with respect to both TC and
   T0; conversely, under anaerobic stress 522 genes were up-regulated and
   168 down-regulated with respect to both TC and T0 (Supplementary
   Fig. [59]S3, Supplementary Tables [60]S3 and [61]S4). Gene ontology
   analysis that compared the up-regulation of the molecular function of
   genes under T15 conditions with that under either TC or T0 showed
   greater overall up-regulation of oxido-reductase activity, of
   transcription factors and of sequence-specific DNA binding elements
   (Supplementary Fig. [62]S4). Interestingly, in addition to the effect
   of the elevated CO[2] treatment on berry flavor and metabolism, global
   pathways enrichment analysis showed induction of the phenylpropanoid
   pathway for both in TC and T15 as compared to T0, suggesting that it is
   a cold-stress-related effect (Supplementary Tables [63]S5–[64]S14).

Effects of elevated CO[2] level on genes involved in off-flavor-related
metabolic processes

   Genes related to pyruvate metabolism that are up-regulated following
   exposure to high levels of CO[2] can be hypothesized to be involved in
   accumulation of off-flavor related metabolites (Fig. [65]1B). A
   pyruvate kinase (PK) ortholog encoding for the last enzyme in pyruvate
   biosynthesis, in which phosphoenolpyruvate is converted to pyruvate,
   was up-regulated in T15 as compared to either TC or T0 (Fig. [66]2,
   Supplementary Table [67]S15), as also were two additional genes that
   may be of importance for accumulation of pyruvate. Phosphoenolpyruvate
   carboxykinase (PEPCK), encoding for an enzyme responsible for
   conversion of oxaloacetate to phosphoenolpyruvate; and an ortholog of
   NADP-dependent malic enzyme gene that encodes for an enzyme that
   catabolizes malate to pyruvate were both significantly up-regulated in
   T15 than in TC.

Figure 2.

   [68]Figure 2
   [69]Open in a new tab

   Upregulation of genes putatively involved in metabolism of pyruvate,
   amino and fatty acid may result in accumulation of volatile compounds
   associated to off-flavor. Volatile compounds derived from degradation
   of (A) pyruvate, (B) branch-chain amino acids or (C) fatty acid
   degradation were examined after harvest (T0), after storage for 6 weeks
   at low temperature (TC) or after storage at low temperature under O[2]
   level of 5 kPa and CO[2] levels of 15 kPa (T15). Genes are presented in
   the heat-map analysis if in at least one of the treatments (T0, Tc or
   T15), genes were down- or upregulated with LogFC > (1.5) and
   FDR < 0.05. Heat-map was performed based on normalized read counts for
   the significantly regulated genes: red box indicates upregulated and
   green downregulated expression. In the heat-maps and in the bar graphs,
   samples are arranged, from left to right, as T0, TC and T15.
   Metabolites in graph bars marked in red are associated to off-flavor
   while grey bars are not associated to off-flavor. PEPCK,
   phosphoenolpyruvate carboxykinase; PK, pyruvate kinase; PDH, pyruvate
   dehydrogenase; PDC, pyruvate decarboxylase; ALDH, aldehyde
   dehydrogenase; ADH, alcohol dehydrogenase; BCKDHA, branched-chain
   alpha-keto acid dehydrogenase; LOX, lipoxygenase; HPL, hydroperoxide
   lyase; OPR, 12-oxophytodienoate reductase. Dashed lines represent
   multi-step or unknown metabolic process while full line represents a
   single known enzymatic step. Units for volatile metabolites are in ng/g
   FW while values for leucine, isoleucine and jasmonic acid are in peak
   abundance (Abun.). Levels of metabolites and expression of genes were
   analyzed based on three biological replications for each treatment
   (n = 3). Statistical analysis of metabolites is presented in
   Supplementary Tables [70]1 and [71]22.

   Three gene families are normally involved in conversion of pyruvate to
   volatile metabolites: pyruvate decarboxylase (PDC) converts pyruvate to
   acetaldehyde, pyruvate dehydrogenase (PDH) converts pyruvate to
   acetyl-CoA, and acetolactate synthase (ALS) converts pyruvate to
   acetolactate. Interestingly, and despite the increase in the
   metabolites produced by these enzymes, no up-regulation was observed
   for PDH, PDC or ALS in any of the three treatments, and all gene
   families had members that were constitutively expressed (Supplementary
   Table [72]S15).

   Downstream along the pathway, two gene families are involved in the
   metabolism of aldehydes: alcohol dehydrogenase (ADH) and aldehyde
   dehydrogenase (ALDH). A grapevine ADH ortholog with multiple isoforms
   had higher expression in T15 than in T0 or TC (Supplementary
   Table [73]S15). The ALDH family, which encodes for an enzyme that
   catalyzes the conversion of acetaldehyde to acetate, had two gene
   members with significantly greater up-regulation in T15 than in TC but
   not greater than in T0.

   Acetyl Coenzyme A (Ac-CoA) is a key metabolic intermediate that may
   lead to production of acetone and ethyl acetone (2-pentanone).
   Alternative pathways to the production of Ac-CoA by PDH are degradation
   of branch-chain amino acids, and β-oxidation of fatty acids. Two
   putative genes involved in the formation of Ac-CoA from leucine and
   isoleucine were up-regulated: aminotransferase and branched-chain
   alpha-keto acid dehydrogenase (BCKDHA) (Fig. [74]2, Supplementary
   Table [75]S15). With regard to degradation of linoleic and linolenic
   acids, several members of the LOX, HPL and ADH gene families were
   up-regulated in T15 as compared to T0 or TC (Fig. [76]2, Supplementary
   Table [77]S15); they encode for enzymes involved in the production of
   C[6] alcohols. Although hexanol and (E)-2-hexenol increased in T15,
   they were less likely to contribute to off-flavor in grape berries.
   Interestingly, jasmonate, another product of this pathway was also
   found at a higher level in T15 than in T0 or TC, concomitantly with the
   up-regulation of putative 12-oxo-phytodienoic acid reductase (OPR)
   gene, which is known to be involved in jasmonate biosynthesis
   (Fig. [78]2, Supplementary Table [79]S15).

Major shifts in regulation of gene expression under elevated CO[2] levels and
low temperature

   Expression of 412 putative and characterized transcription factors was
   examined among the three treatments (Supplementary
   Tables [80]S16–[81]S19). The ethylene response factors (ERFs) consist
   of a subfamily termed “Hypoxia-Response Elements” (HREs), which are
   active under anaerobic stress. Analysis of ERFs related to anaerobic
   stress was focused on the three members of the HRE family characterized
   in Arabidopsis^[82]10: HRE1 (At1g72360), HRE2 (At2g47520), and RAP2.12
   (At1g53910). Four putative ERFs, two of which are similar to AtRARP2.12
   and two to HRE1 were significantly up-regulated in T15 compared to TC
   or T0 (Fig. [83]3, Supplementary Table [84]S16). Another five ERFs were
   reported elsewhere to be induced following 3 days of exposure to high
   CO[2] in V. vinifera ‘Cardinal’ berries^[85]11 but none of them was
   up-regulated in T15 as compared to TC or T0. A gene with high
   similarity to one of the five known ERFs from V. vinifera —
   VvERF6L7-c-like gene — displayed significantly higher expression in T15
   and in TC than in T0 (Supplementary Table [86]S16). The Arabidopsis
   hemoglobin-like gene AtHB1 ([87]NP_179204.1 was up-regulated under
   anaerobic conditions. Among the several V. vinifera orthologous HB1
   genes, one gene — VIT_203s0063g01960.1 — was up-regulated in T15 as
   compared to TC or T0 (Supplementary Table [88]S20). C-repeat binding
   factors (CBFs), transcription factors^[89]12, and their inducers
   (ICEs)^[90]13 were shown to be involved in cold-stress response and
   freezing tolerance in V. vinifera. However, we did not observe
   increased expression of any of the VvCBFs in T15 or TC as compared to
   T0. VvICE1, an inducer of CBF expression was up-regulated in T15 and TC
   as compared to T0 (Supplementary Table [91]S19). The CBFs are also
   called dehydration responsive element-binding (DREB)^[92]14. Out of the
   38 partially characterized VvDREBs, four were significantly changed:
   VvDREB05 and VvDREB08 were down-regulated by cold stress, VvDREB12 also
   was down-regulated under cold stress but with stronger preference for
   anaerobic conditions, whereas VvDREB25 was up-regulated in T15 as
   compared to TC but not as compared to T0 (Supplementary Table [93]S19).
   VvDHN1a, which is a structural gene encoding dehydrin 1a that is
   associated with the cold-stress response was up-regulated in TC and T15
   as compared to T0 (Supplementary Table [94]S21).

Figure 3.

   [95]Figure 3
   [96]Open in a new tab

   Suspected hypoxia-response elements (HRE) upregulated under elevated
   CO[2] levels. Grape berries of ‘Superior Seedless’ after harvest (T0),
   after storage for 6 weeks at low temperature (TC) or after storage at
   low temperature under O[2] level of 5 kPa and CO[2] levels of 15 kPa
   (T15). The Y-axis refer to LogFC values. Comparison is between pairs of
   treatments at the top and bottom of each panel. Grey surface between
   LogFC < (1.5) represent comparison that did not change significantly.
   Red balloons represent conditions of genes that were upregulated in T15
   as compared to T0 and TC and therefore are related to anaerobic stress.
   Blue balloons represent conditions of genes that were upregulated in TC
   and in T15 as compared to T0, but not between T15 to TC and therefore
   are related to cold stress. Squares indicate the mean Log(FC): black
   squares indicate FDR < 0.05; green squares indicate FDR > 0.05.
   Expression of genes were analyzed based on three biological
   replications for each treatment (n = 3).

Metabolic changes in phenylpropanoid levels under low temperature and
elevated CO[2] levels

   Metabolites of four branches of the phenylpropanoid pathway changed
   among the treatments, including 14 stilbenes, 13 flavonols, three
   dihydroflavonols, five flavan-3-ols, and eight of their derivative
   proanthocyanidins. Of the 47 metabolites detected, 30 had higher level
   in TC and T15 than in T0 (Fig. [97]4, Supplementary Table [98]S22). The
   levels of 22 metabolites were higher in either TC, T15, or both than in
   T0. The metabolites were detected mainly in their glycosylated forms,
   such as kaempferol-3-O-galactoside. The levels of the amino acid
   L-phenylalanine, the entry-point metabolite of the phenylpropanoid
   pathway, was significantly lower in both TC and T15 than in T0
   (Fig. [99]4, Supplementary Table [100]S22).

Figure 4.

   [101]Figure 4
   [102]Open in a new tab

   Upregulation of the phenylpropanoid pathway resulted in the
   accumulation of metabolites from different sub-branches under cold
   stress and elevated CO[2] levels. Grape berries of ‘Superior Seedless’
   after harvest (T0), after storage for 6 weeks at low temperature (TC)
   or after storage at low temperature under O[2] level of 5 kPa and CO[2]
   levels of 15 kPa (T15). Graphs are colored according to the following
   key: flavonols (black), dihydroflavonols (green), flavan-3-ols and
   their derivative proanthocyanidins (red), stilbenoids (purple). Gene
   are presented in the heat-map analysis if in at least one of the
   treatments (T0, Tc or T15), genes were down- or upregulated with
   LogFC > (1.5) and FDR < 0.05. Heat-map was performed based on
   normalized read counts for the significantly regulated genes: red boxes
   indicate upregulated and green downregulated expression. Bar graphs
   describe changes in metabolite accumulation (Y-axis: relative
   abundance). In the heat-maps and in the bar graphs, samples are
   arranged, from left to right, as T0, TC and T15. PAL, phenylalanine
   ammonia lyase; C4H, cinnamate 4-hydroxylase; 4CL, 4-coumarate-CoA
   ligase; STS, stilbene synthase; CHS, chalcone synthase; CHI, chalcone
   isomerase; F3H, flavanone 3-hydroxylase; F3′H, flavonoid
   3′-hydroxylase; FLS, flavonol synthase; F3′5′H, flavonoid
   3′,5′-hydroxylase; DFR, dihydroflavonol 4-reductase; ANS, anthocyanidin
   synthase; ANR, anthocyanidin reductase; LAR, leucoanthocyanidin
   reductase. PBS3 and EPS1 two putative regulatory genes those are
   associated to salicylate biosynthesis. Dashed lines represent
   multi-step or unknown metabolic process while full line represents a
   single known enzymatic step. Levels of metabolites and expression of
   genes were analyzed based on three biological replications for each
   treatment (n = 3). Statistical analysis is presented in Supplementary
   Table [103]22. Units for metabolite levels are in peak abundance
   (Abun.).

Accumulation of stilbenes under cold stress

   One of the important junctions in the phenylpropanoid pathway is the
   conversion of p-coumaroyl-CoA and three molecules of malonyl-CoA to
   either the stilbene trans-resveratrol, or the flavonol naringenin
   chalcone. The stilbenes detected in the present study included
   piceatannol, a hydroxylated form of resveratrol, piceids that are
   glycosylated forms of resveratrol and viniferins that are
   oligostilbenes.

   Only two viniferins — palidol and δ-viniferin — were detected in T0.
   Six viniferins — (E)-miyabenol C, (E)- and (Z)-ε-viniferin, caraphenol,
   (Z)-ω-viniferin and an unidentified resveratrol dimer — were detected
   in TC and T15, and (Z)-miyabenol C was detected only in TC
   (Fig. [104]4, Supplementary Table [105]S22). Of the eight resveratrol
   oligomers present, seven were more abundant in TC than in T0 or T15;
   Only δ-viniferin was found at similar levels in TC and T15, both higher
   than in T0 (Fig. [106]4, Supplementary Table [107]S22).

   The two glycosides of piceatannol (E)- and (Z)-astringin, did not show
   any significant difference between the treatments. No significant
   changes were detected for cis- or trans-piceid isomers among T0, TC and
   T15 (Fig. [108]4, Supplementary Table [109]S22). Interestingly, in all
   treatments, cis-piceid was 40-fold more abundant than the trans isomer.
   BLAST of hsaCYP1B1 (Genbank [110]NP_000095.2), a cytochrome P450 (CYP)
   gene encoding trans-resveratrol hydroxylase, identified a predicted CYP
   that was upregulated in TC compared to T15 (Supplementary
   Table [111]S23).

Accumulation of flavonoids under elevated CO[2] levels

   The flavonol subgroup was represented by 13 metabolites in ‘Superior
   Seedless’ grape berries. Two kaempferol-derived compounds —
   kaempferol-3-O-galactoside and kaempferol-3-O-glucoside — were more
   abundant in T15 than in T0 or TC, as also were quercetin and
   tamarixetin. Additional quercetin derivatives, such as
   quercetin-3-O-galactoside and quercetin-3-O-glucoside, were more
   abundant in T15 and TC than in T0. The three flavonols derived from
   myricetin showed the opposite trend: laricitrin-3-O-glucoside content
   was higher in T0 than in TC or T15, and myricetin-3-O-glucoside and
   syringetin-3-O-glucoside were more abundant in T0 than in TC, but not
   more than in T15 (Fig. [112]4, Supplementary Table [113]S22).

   Dihydroflavonols did not show a consistent pattern of accumulation
   among treatments: dihydrokaempferol-3-O-rhamnoside levels did not
   differ significantly among the treatments; the
   dihydroquercetin-3-O-rhamnoside level was higher in T0; and
   dihydroquercetin-3-O-hexoside was more abundant in TC and T15 than in
   T0.

   Thirteen flavan-3-ols and their polymerized derivatives —
   proanthocyanidins — were detected in the berries. We identified four
   flavan-3-ols: (−)-epicatechin, (−)-epigallocatechin, (+)-catechin, and
   (−)-epicatechin gallate, but only (−)-epicatechin was affected by the
   treatments; it was more abundant in T15 and TC than in T0 while
   taxifolin-pentoside showed the opposite trend. Proanthocyanidins
   displayed a different pattern from that observed for stilbenes or
   flavonols: isomer 1 of procyanidin T2/T3/T4/C1 was not affected by the
   treatments, whereas isomer 2 accumulation was higher in T0 than in TC
   or T15, and isomer 3 accumulation was higher in TC and T15 than in T0
   (Fig. [114]4, Supplementary Table [115]S22).

Induction of phenylpropanoid pathway genes under low temperature and elevated
CO[2] levels

   Analysis of the expression levels of genes encoding for the 16
   enzymatic steps of the phenylpropanoid pathway demonstrated that 7
   steps displayed significant changes in T15 or TC compared to T0
   (Fig. [116]4, Supplementary Table [117]S24). The initial reaction of
   the phenylpropanoid pathway involves three key steps: phenylalanine
   ammonia lyase (PAL), cinnamate-4-hydroxylase (C4H) and 4-coumarate-CoA
   ligase (4CL) with, respectively, 13, 2 and 1 gene(s) that were
   significantly up-regulated in TC and T15 as compared to T0. Downstream,
   the pathway splits into two branches, stilbenes and flavonols, that are
   catalyzed by stilbene synthase (STS) and chalcone synthase (CHS) gene
   products, respectively. Both STS and CHS encode for enzymes that
   utilize the same substrates — p-coumaroyl-CoA and three molecules of
   malonyl-CoA — to produce resveratrol or naringenin chalcone,
   respectively, and the genes share many features^[118]15. STS had six
   homologous genes that were significantly up-regulated in TC and T15 as
   compared to T0, whereas no up-regulation was observed for CHS
   (Fig. [119]4). Peroxidase activity was associated with the biosynthesis
   of viniferins^[120]16. Of the 73 putative genes encoding for
   peroxidases (EC 1.11.1.7), only two were up-regulated in TC as compared
   to T0 or T15 (Supplementary Table [121]S25). Peroxidase 16
   (VIT_211s0052g00650.1) had logFC of 3.14 as compared with T0, and logFC
   of 4.07 as compared with T15.

   Downstream in the flavonoid branch there were significant changes in
   expression of members of dihydroflavonol 4-reductase (DFR),
   anthocyanidin reductase (ANR) and leucoanthocyanidin reductase (LAR)
   among the treatments but without conclusive correlation to the
   respective metabolite levels. Five putative flavonoid
   glycosyltransferase orthologues encoding enzymes that add sugar
   moieties to flavonoids were upregulated in T15 compared to TC and T0
   (Fig. [122]4, Supplementary Table [123]S24).

Regulation of the phenylpropanoid pathway

   MYB transcription factors are known to play key roles in regulating the
   phenylpropanoid pathway^[124]17–[125]20. Recent studies^[126]21,[127]22
   extended the list of MYBs and WRKYs that are presumably involved in
   stilbene biosynthesis, and improved their annotation; 21 MYBs showed
   significant up- or down-regulation under the experimental setup
   (Supplementary Table [128]S18). Two MYBs were up-regulated in TC as
   compared to T15 or T0: the stilbene regulator VvMYB14^[129]20, and
   MYB-related protein 3r-1-like (Fig. [130]5A, Supplementary
   Table [131]S18). VvMYB15, another stilbene regulator^[132]20 was
   up-regulated in T15 as compared to T0 but not with respect to TC
   (Supplementary Table [133]S18). Three MYBs were up-regulated under cold
   and anaerobic conditions (Fig. [134]5B, Supplementary Table [135]S18)
   and another three MYBs were up-regulated under cold stress without
   association with higher CO[2] levels (Fig. [136]5C, Supplementary
   Table [137]S18). Conversely, five MYBs were down-regulated under
   cold-stress conditions (Fig. [138]5D, Supplementary Table [139]S18).
   The family of WRKY transcription factors was also implied to regulate
   the phenylpropanoid pathway^[140]22 and 20 WRKYs changed in T15 or TC
   as compared to T0. VvWRKY24 was highly up-regulated under cold stress
   whereas VvWRKY44 underwent significant changes in expression among the
   treatments (Supplementary Tables [141]S17). PBS3 and EPS1 are two
   regulators of the salicylate pathway and putative homologs of these
   genes were up-regulated in T15 and TC than in T0 (Fig. [142]4,
   Supplementary Table [143]S26).

Figure 5.

   [144]Figure 5
   [145]Open in a new tab

   MYB transcription factors significantly affected by cold stress and
   elevated CO[2] levels. Results appear as comparisons between two
   treatments. Grape berries of ‘Superior Seedless’ after harvest (T0),
   after storage for 6 weeks at low temperature (TC) or after storage at
   low temperature under O[2] level of 5 kPa and CO[2] levels of 15 kPa
   (T15). Comparison is between pairs of treatments at the top and bottom
   of each panel. The Y-axis refer to LogFC values. Grey surface between
   LogFC < (1.5) represent comparison that did not change significantly.
   Red balloons represent upregulation of genes at T15 as compared to T0
   and TC (anaerobic stress). Blue balloons represent upregulation of
   genes at TC and T15 as compared to T0, but not between T15 to TC (cold
   stress). Green balloons represent upregulation of genes at TC as
   compared to T0 or T15 (cold stress under aerobic conditions). Squares
   indicate the mean Log(FC): black squares indicate FDR < 0.05; green
   squares indicate FDR > 0.05. Expression of genes were analyzed based on
   three biological replications for each treatment (n = 3).

Discussion

   Berry flavor was examined in five storage treatments, including low
   temperature and elevated CO[2] levels. The treatment with the highest
   CO[2] level of 15 kPa (and 5 kPa O[2]) resulted in a significant
   negative effect on berry flavor during 6 weeks of storage. The 12
   metabolites that increased in T15 (elevated CO[2] levels, i.e.,
   anaerobic conditions) were derived mainly from pyruvate degradation
   with two representatives from branch-chain amino acids. Of the 12
   compounds that had increased levels during storage under elevated CO[2]
   levels, two volatile compounds — diacetyl and ethyl acetate — showed
   OAV scores >1, a threshold value that indicates the potential to
   contribute to grape flavor. Ethyl acetate has been associated with
   off-flavors in fruits, including strawberries and
   mandarins^[146]23,[147]24 but not in grapes. Diacetyl was associated
   with PDC activity^[148]25,[149]26 in various fruits and was reported as
   a potential metabolite that contributed to off-flavors as a result of
   microbial activity^[150]27,[151]28. Although the contributions of
   individual volatile compounds to off-flavor are well established, the
   combined effect of the mixture cannot be ignored^[152]29. For example,
   diacetyl and acetoin share a similar ‘milky’ odor character that could
   be enhanced by the presence of both compounds in the medium and under
   elevated ethanol levels (i.e., in berry fermentation). Our present
   results associate the accumulation of suspected off-flavor volatile
   compounds in grapes with up-regulation of genes such as PK, PEPPCK, and
   malic enzyme, from various upstream branches involved in the production
   of pyruvate. These results indicate that increased pyruvate flux is a
   more likely lead to up-regulation of pyruvate degradation, because no
   up-regulation was recorded for PDC, PDH or ALS.

   The sub-branch of pyruvate degradation by the ALS gene family encoding
   enzymes that convert pyruvate to acetolactate has only one member
   characterized in Arabidopsis^[153]30. The ALS activity is followed by a
   still unknown enzymatic activity or by a spontaneous step that leads to
   accumulation of diacetyl, its conversion to acetoin and, in turn, to
   the conversion of acetoin to 2,3-butanedienol by dehydrogenases that
   have not so far been identified in plants. Acetoin, diacetyl, and
   2,3-butanedienol increased in various wine grape cultivars undergoing
   carbonic maceration, but their accumulation patterns varied
   substantially among varieties and the accumulation was attributed to
   microbial rather than endogenous activity^[154]31. One of the largest
   families of genes in plants, the ADHs, also is associated with
   off-flavors in numerous fruits; ADH enzyme activity was associated with
   off-flavors in mandarins, grapefruits^[155]32 and strawberries^[156]33.
   Moreover, ADHs genes and their isoforms have varied substrate
   specificity^[157]34; in grapes six VvADHs were characterized either by
   sequence identity^[158]35 or by functional expression^[159]36.
   Moreover, VvADH enzyme activity was shown to be affected by the hypoxic
   conditions in grape cell culture^[160]37; in contrast to our present
   experimental conditions, stress duration was relatively short and
   ambient temperature (20 °C) was used. Except for the six characterized
   VvADHs genes, additional putative members of the ADH family were found
   by sequence identity but their functions or activities in grape berries
   were not described^[161]35. Grapevine leaves showed higher levels of
   glycosylated volatile alcohols from various metabolic pathways, e.g.,
   monoterpenols or C[6] alcohols in transgenic grapevine overexpressing
   VvADH2^[162]38. So far a major part of the study of VvADH in grapes was
   focused on grapevine and berry development^[163]39. Our present results
   suggest that members of the VvADH gene family that are constitutively
   expressed or, possibly, that up-regulation of a specific VvADH —
   VIT_214s0068g01760.1 and its isoforms — might be involved in the
   production of multiple volatile compounds under anaerobic conditions
   (T15) that can associated with off-flavors; such compounds include:
   ethanol, acetaldehyde, ethyl acetate, 2-methylbutanol and
   3-methylbutanol^[164]23,[165]24,[166]31. Conversely, ADH enzyme also
   involved in the last step of biosynthesis of hexanol or (E)-2-hexenal,
   which are not associated with off-flavor in table grapes^[167]40.
   Except for the ADH gene family, the LOX-HPL genes were also shown to be
   important for the diversification of C[6] volatiles in the
   berries^[168]41. Characterization of the LOX gene family in Vitis
   vinifera identified 18 putative genes that were partially characterized
   for 13-LOX activity^[169]42. The HPL gene family is part of the
   cytochrome P450s superfamily and may hold a substrate specificity to
   either 13-HPL or 9-HPL or to both; so far, two HPLs were characterized
   in Vitis vinifera^[170]43. The up-regulation of expression of ADH and
   HPL genes is consistent with the increase in the C[6] volatile, and
   up-regulation of the LOX can be associated with the increase in
   jasmonate under anaerobic conditions.

   The increased expression of genes involved in fermentative respiration
   under anaerobic conditions is mediated by specific transcription
   factors, some of which have been identified in model systems and in
   table grapes^[171]10,[172]44,[173]45. A unique and characterized group
   of ERFs — HREs^[174]10 — was shown to be involved in the transition to
   fermentative respiration in Arabidopsis. HRE genes belong to the group
   of VII ERFs and respond to low-oxygen conditions^[175]10. The
   superfamily of ERF genes was characterized in grapevine and was shown
   by sequence identity to include over 100 genes^[176]46,[177]47. The
   HRE2 protein is stabilized under hypoxic conditions by a conserved
   motif that starts with Met-Cys in its N-terminus^[178]48,[179]49.

   Under our experimental conditions, the expression of five grape
   orthologs to HREs increased under elevated CO[2] conditions, making
   them also plausible candidates for regulation of hypoxia responses.
   Conversely, five VvERFs that were previously shown to be up-regulated
   in grape berries under elevated CO[2] levels, were not up-regulated
   under T15 as compared to TC and genes (Fig. 3). V viERF2-c and
   VviERF11-c, were upregulated following cold stress conditions
   (upregulation in TC and in T15 as compared to T0) . One of the major
   differences between our present conditions and that work^[180]11 was
   the time factor: the grape berries were exposed to the elevated CO[2]
   for only 3 days as compared to 6 weeks in our experiment. Six ERFs in
   addition to the five HRE orthologous genes were induced under our
   long-term exposure to elevated CO[2] conditions; their putative
   functions and responsiveness to anaerobic stress should be evaluated
   under different conditions^[181]50,[182]51. Up-regulation of ADH and
   HB1 (hemoglobin) was previously suggested as a hallmark of anaerobic
   conditions^[183]10 and our present findings support this notion for HB1
   and one of the VvADH family members. AtHB1 encodes a non-symbiotic
   hemoglobin-like protein that increases in Arabidopsis under anaerobic
   conditions. The non-symbiotic hemoglobin class 1 proteins are
   up-regulated under hypoxic conditions and possess high affinity to
   O[2], whereas hemoglobin class 2 proteins possess low affinity to O[2]
   and are up-regulated under cold stress^[184]52. HB1 was hypothesized to
   act as a plant sensor for hypoxic conditions^[185]53 and it may be an
   important marker also for the development of anaerobic stress during
   cold storage of grapes.

   Transcription factors that were shown to be up-regulated under cold
   stress included several ERF gene family members, MYBs and WRKYs that
   were shown to be up-regulated after short exposure to cold
   stress^[186]49,[187]54. We did not detect up-regulation of any of the
   previously characterized VvCBF genes that previously were associated
   with cold stress^[188]55,[189]56; in contrast, the putative CBF
   inducer, VvICE1, was up-regulated under cold stress. In grapes, the
   VvCBFs and VvICEs were examined for their effects on plant growth but
   their expression was not examined at the fruit level^[190]55,[191]56;
   future studies should examine the response of VvCBFs to short- and
   long-term low temperature at the berry level. It should also be pointed
   out that VvCBF1 ([192]AY390372) was not identified in the V. vinifera
   genome and that functional analysis of the VvCBFs and VvICEs is
   desirable. Apart from the relatively well characterized function of
   DREB1-4^[193]57–[194]59, there has been no good characterization of
   additional gene family members. Two VvDREB genes — VvDREB05 and
   VvDREB08 — that showed down-regulation under cold stress behaved in
   accordance with short-term down-regulation^[195]14 but their role in
   the cold-resistance mechanism is not well understood.

   The phenylpropanoid pathway is responsible for the synthesis of
   important compounds involved in various stress responses in
   plants^[196]60, including acclimation to cold stress^[197]61; in grape
   berries, this pathway has a central role in the biosynthesis of
   compounds that impart important quality characteristics, such as
   antimicrobial activity, color, flavor, antioxidant capacity and
   astringency. Reduced levels of L-phenylalanine in treatments TC and
   T15, along with up-regulation of PAL, suggest that more L-phenylalanine
   entered the pathway and subsequently was metabolized to downstream
   metabolites. This finding is consistent with the increased levels of
   most phenylpropanoids detected in the berries indicating on the
   importance of inducing the initial stage of the phenylpropanoid pathway
   to produce various metabolites downstream along the pathway and its
   branches. Previous studies demonstrated specific metabolic and
   transcriptomic changes in the phenylpropanoid pathway following
   exposure of ‘Cardinal’ grape berries to cold stress under aerobic or
   short-term anaerobic conditions^[198]6,[199]7,[200]11. In general, our
   present findings are in agreement with these studies with respect to
   the up-regulation of PAL and STS, but offer a perspective on how
   prolonged cold stress or elevated CO[2] levels might affect gene
   expression and accumulation of phenylpropanoid pathway metabolites
   during storage.

   One main branch of the phenylpropanoid pathway is that of the flavonols
   such as quercetin, kaempferol and myricetin, and their glycoside
   derivatives, which exhibit antioxidant and anti-inflammatory
   activities^[201]62 and were repeatedly reported to be present in grape
   berries. Our results show that after long exposures to elevated CO[2]
   levels, the levels of kaempferol and quercetin glycosides increased
   significantly. This effect was not demonstrated previously; it may be
   attributed to a shunting effect that could result from inhibition of
   stilbene synthesis under elevated CO[2] levels.

   Stilbenes are another important branch of the phenylpropanoid pathway
   that is involved in the production of resveratrol and its derivatives;
   resveratrol derivatives with health-promoting properties for humans
   include viniferins^[202]63,[203]64, which were shown to strongly
   suppress proliferation of various cancerous cell lines and to be
   involved in apoptosis^[204]65,[205]66. Seven out of the nine viniferins
   identified in the present study appeared only in TC, and the other two
   viniferins increased in TC as compared to T15 and T0. Trans-resveratrol
   can be converted to δ-viniferin by horseradish peroxidase enzyme
   extracts^[206]16; we detected increases in four peroxidase-like gene
   homologs concurrently with the accumulation of δ-viniferin, which
   raised the hypothesis that grape peroxidases might be involved in the
   biosynthesis of δ-viniferin. The hydroxylated analog of
   trans-resveratrol — piceatannol — was 10 times as abundant in TC as in
   T0 or T15. The conversion of trans-resveratrol to piceatannol occurs in
   humans via the action of CYP1B1^[207]67 but, to the best of our
   knowledge, neither this enzymatic step nor the gene encoding a putative
   enzyme catalyzing this reaction was characterized in plants. We
   identified an orthologous gene of the hsaCYP1B1 that potentially could
   be involved in the hydroxylation of trans-resveratrol to piceatannol in
   grape berries. The up-regulation in STS does not account for the
   increased levels of piceatannol and viniferins; piceids did not
   accumulate to a greater extent in TC than in T0 or T15. Alternatively,
   increased expression of peroxidases, as demonstrated in the present
   study, and of hydroxylases might account for the greater accumulation
   of the stilbenes in TC than in T0 or T15. Previous findings revealed an
   increase in resveratrol induced by low-temperature stress before
   harvest^[208]68 and a decrease after exposure to cold stress^[209]6.
   One explanation for these findings is the conversion of
   trans-resveratrol to piceatannol or viniferins during prolonged cold
   stress in our experiments, or the fact that ‘Cardinal’, a red grape
   berry cultivar, is not blocked in anthocyanin synthesis.

   The regulation of biosynthesis of stilbenes in plants, and especially
   in grapes, has attracted much attention, with a focus on the role of
   MYB genes, because many of the MYBs regulate various branches of the
   phenylpropanoid pathway^[210]19,[211]69. Specifically: two MYBs were
   characterized as STS gene regulators (VvMYB14-15) and a third also was
   hypothesized to be an STS regulator, in light of its co-expression
   pattern (VvMYB13). MYBS13-15 were shown to be induced by biotic and
   abiotic stress conditions and the three regulatory genes form a
   co-expression network with seven STS genes^[212]69. Under our present
   experimental conditions, we did not find significant expression of
   VvMYB13 and the up-regulation of VvMYB15 at T15 with respect to T0
   could not be associated with stilbene accumulation pattern in the
   berries. Conversely, our findings show that up-regulation of VvMYB14
   following cold stress (TC) was concomitant with the viniferins
   accumulation pattern. Thus, our results suggest that VvMYB14 is
   involved in the regulation of viniferins or piceatannol in grape
   berries during postharvest storage. Recently, the role of WRKY
   transcription factors in regulation of stilbene biosynthesis was
   highlighted^[213]22; of special interest was the possible interaction
   of VvWRKY24 with VvMyb14 at the promoter level. VvWRKY24 was also shown
   to interact with the promoter of VvSTS29. The Arabidopsis homolog of
   VvWRKY24 (AtWRKY33) was shown to be involved in salicylate signaling,
   redox homeostasis, and jasmonate/ethylene-mediated defense
   responses^[214]70. Further analysis and characterization are required
   for the additional 12 MYB and 10 WRKY genes that showed differential
   expression between aerobic and anaerobic conditions under cold stress.
   One of the hypotheses for the induction of stilbenes at low temperature
   corresponds to their known protective role as stress-induced
   phytoalexins^[215]68,[216]71, but they also mitigate cold–induced ROS
   damage^[217]72. Conversely high CO[2] may inhibit accumulation of
   resveratrol and its derivative(s) by interfering with ion transport and
   associated redox processes^[218]71,[219]73.

   Salicylate is a plant hormone known to be involved in the response to
   abiotic-stress conditions^[220]74. The biosynthesis of salicylate was
   ascribed to two pathways. The first is from chorisimate to
   isochorismate and then to salicylate via two steps involving
   isochorismate synthase (ICS) and isochorismate pyruvate lyase (IPL).
   However, in plants only the ICS gene was identified so far in
   Arabidopsis. The second pathway is from trans-cinnamate to salicylate
   via an as yet unknown number of steps^[221]75. Two key regulatory genes
   — PBS3 and EPS1 — were identified as important for biosynthesis of
   salicylate; under our experimental conditions both were up-regulated in
   T15 and TC as compared to T0, and in accordance with the accumulation
   of salicylate. Exogenous application of salicylate resulted in
   induction of PAL, which catalyzed the conversion of L-phenylalanine to
   trans-cinnamate^[222]76. Therefore, as suggested by the data in
   Fig. [223]4, it is hypothesized that salicylate also may induce PAL in
   grape berries exposed to cold and anaerobic stresses. Interestingly,
   VvWRKY3, which was up-regulated as a result of anaerobic stress under
   our experimental conditions, also was shown to be up-regulated by
   salicylate and jasmonate in leaves of Vitis pseudoreticulata^[224]77.

   Jasmonate is another plant hormone that can be activated by either
   biotic or abiotic stress conditions^[225]78. Jasmonate biosynthesis is
   initiated in the plastid by LOX^[226]79 and subsequently the
   intermediate cis-12-oxo-phytodienoic acid is transported to the
   peroxisome by an ATP-binding cassette (ABC) transporter and undergoes
   reduction by OPR and a β-oxidation process^[227]80. OPR is the third
   enzyme in the biosynthesis of jasmonate and it was characterized in
   different plant species, e.g. Zea mays^[228]81, and putative VvOPRs
   also were described^[229]82. Application of jasmonate treatments to the
   berries had resulted in increased LOX enzyme activity and enhanced
   levels of several C[6] volatiles, including the two alcohols hexanol
   and (E)-2-hexenol, in agreement with our present results^[230]83.

   The induction of putative LOX and OPR genes under anaerobic conditions
   (Fig. [231]2, Supplementary Table [232]S15) was consistent with the
   increase in jasmonate levels, especially under anaerobic conditions.
   Interestingly, jasmonate was shown to be involved in the induction of
   various ‘specialized’ metabolites in plants^[233]84 and in particular
   PAL expression and stilbene accumulation including in grape
   berries^[234]85. A possible explanation for the increased levels of
   both salicylate and jasmonate under elevated CO[2] levels is the higher
   flux of the upstream metabolites, phenylalanine and linolenic acid.

   In conclusion: postharvest storage research has focused mainly on
   developing methodologies to control and minimize detrimental changes in
   fruits and vegetables during storage. During storage fruits and
   vegetables exhibit active respiration to meet the energy demands of the
   cells and, most importantly, they can respond to environmental cues.
   Our findings shed light on the specific metabolic shifts occurring in
   table grapes under elevated CO[2] levels and in cold storage. In the
   present paper we describe some of the specific genes that may be
   involved in responding to these conditions and regulating the
   responses; we also describe specific metabolic shifts and the resulting
   metabolites that accumulate under cold stress or combined cold and
   anaerobic stresses. The volatile metabolites that accumulate under
   anaerobic stress may be useful as off-flavor markers that facilitate
   improved control of alternative storage conditions. Our results
   indicate that the levels of stilbenes, normally associated with
   beneficial health-promoting effects, are more than 60 times as high
   after storage as before storage. Thus, we demonstrated that storage may
   have beneficial effects in creating new opportunities to actively
   enhance specific metabolites after harvest.

Materials and Methods

Plant material, experimental setup and storage conditions

   Table grapes (Vitis vinifera L.) cv. ‘Superior Seedless’ were obtained
   from a commercial vineyard in Lachish, Israel (lat. 31°33′, long.
   34°51′). The vines were supported by a Y-shaped trellis with planting
   spaces of 3 × 1 m; the shoots were trained to eight canes, with 15 buds
   per cane. Gibberellin was applied at fruit set at a rate of 15 mg/l
   directly to the grape clusters. Leaf removal was performed at veraison.

   Grape clusters were randomly distributed into storage boxes, each
   containing approximately eight clusters with a total weight of
   approximately 5 kg. The boxes were placed in 400-l storage chambers.
   The atmosphere composition was controlled by an ICA6000 system (ICA
   Group, Cardiff, UK). The treatments were as follows: T0 (not stored) –
   grapes sampled on day of harvest; TC – grapes kept under 20 kPa O[2]
   and 0 kPa CO[2], designed to simulate atmospheric conditions; T5, T10
   and T15 – grapes kept at air compositions of 5 kPa O[2] and 5, 10 and
   15 kPa CO[2], respectively. Storage conditions for all treatments
   (except T0) were: 0.0 ± 0.5 °C with RH of 90–95%. Storage duration was
   6 weeks followed by shelf life at 20 °C for 2 days. Postharvest
   analysis was performed only on berries that did not show any sign of
   external or internal decay.

Berry weight, firmness, and sugar and acid contents

   Berry weight was measured by random sampling of 30 berries in each of
   three replications. Berry firmness and diameter were measured on 20
   berries from each replication with a Firmtech II small fruit firmness
   analyzer (BioWorks, Wamego, KS, USA). Juice for measurement of total
   soluble solids (TSS) and TA (titratable acidity) was prepared by
   maceration of the berries in a T398 juice blender (Grandix, Cheres,
   France) and filtration through four layers of cheesecloth. The TSS (°
   Brix) and TA (%), respectively, were determined with a digital
   refractometer (Atago, Tokyo, Japan) and an autotitrator (Metrohm,
   Herisau, Switzerland). The latter measurement used 0.1 N NaOH to adjust
   to pH 8.2. Maturity indices and berry conditions are presented in
   Supplementary Table [235]S27.

Grape sampling for sensory analysis, volatile and non-volatile compounds, and
RNA extraction

   For each treatment, 20 berries were sampled from five clusters in each
   of the three biological replications. For sensory analysis, 50 berries
   were taken from each replicate and were mixed to create a pool of 150
   berries for each treatment. Twenty-five berries from each replication
   were used for volatile-compound analysis for all treatments. Only
   treatments T0, TC, and T15 were analyzed for the presence of
   non-volatile compounds and were used for transcriptomic analyses. The
   berries were cut into quarters from the stem end to the stylar end,
   frozen in liquid nitrogen and kept at −80 °C pending processing, but
   not for more than 6 months. Prior to analysis, 10 quarter-berries were
   homogenized in an A11 grinder (IKA, Staufen, Germany) under liquid
   nitrogen for 20 s and the frozen powder was divided into subsets of 2
   and 5 g, and of 1.2 g for the volatile and non-volatile analyses and
   RNA extraction, respectively.

Sensory analysis

   Grape tastings were conducted in two sessions: at harvest and after 6
   weeks of storage followed by 48 h of shelf life at 20 °C. Each tasting
   panel of 11 trained panelists tasted five randomly selected berries
   from each treatment. Panelists were asked to evaluate the intensity
   score of the off-flavor in each sample by indicating: none = 0,
   low = 1, medium = 2, or high = 3.

Volatile compound analysis

   Crushed tissue powder (2 g) was immediately transferred to 20-ml amber
   vials (LaPhaPack, Langerwehe, Germany) that contained 1 g of NaCl
   (Merck, Darmstadt, Germany) and 2 ml of 20% (w/v) NaCl solution. A
   50-µl aliquot containing internal standard 2-octanol (Sigma-Aldrich,
   St. Louis, MO, USA) at 10 mg/l was added to the vials, which then were
   sealed with magnetic screw caps fitted with pre-cut silicone
   white/polytetrafluoroethylene red LaPhaPack septa (Thermo Fisher
   Scientific, Waltham, MA, USA). GC/MS analysis was performed as
   previously described^[236]86.

Analysis of non-volatiles

   Each 5-g sample was lyophilized and maintained at 4 °C under dry
   nitrogen pending analysis. Before analysis, the sample was solubilized
   with 5 ml of H[2]O/CH[2]OH 50:50 (v/v) solution, and 100 µl of
   4′,5′,7′-trihydroxy flavanone at 52 mg/l was added as an internal
   standard (Sigma-Aldrich, Milan, Italy). The samples were homogenized
   with an Ultra-Turrax (IKA) at 10,000 rpm for 30 s and then extracted in
   an orbital shaker at 200 rpm for 15 min at room temperature. After
   centrifugation at 7000 × g for 15 min the supernatant was filtered
   through a GHP 0.2-µm Acrodisc syringe filter (Pall, MI, USA) and
   collected in a vial for further chromatographic analysis.

   LC/MS analyses were performed as previously described^[237]87 in an
   UHPLC 1290 Infinity apparatus (Agilent Technologies, Santa Clara, CA
   USA) coupled to a Model 1290 Infinity Autosampler (G4226A) (Agilent)
   and a Model 6540 accurate-mass Q-TOF mass spectrometer (Agilent) with a
   jet stream ionization source. For each sample, two analytical
   repetitions in negative ionization mode and full-scan acquisition were
   performed. A blank was run between successive samples to avoid
   cross-contamination. We used Agilent’s MassHunter data-acquisition
   software, version B.04.00 (B4033.2). We performed chromatography with a
   Zorbax reverse-phase column (RRHD SB-C18; 3 × 150 mm, 1.8 μm). The
   mobile phase comprised 0.1% (v/v) aqueous formic acid (A) and 0.1%
   formic acid in acetonitrile (B). The elution gradient program was as
   follows: 5% B isocratic for 8 min; from 5% to 45% B over 10 min; from
   45% to 65% B over 5 min; from 65% to 90% B over 4 min; 90% B isocratic
   for 10 min. The flow rate was adjusted to 0.4 ml/min, column
   temperature was 35 °C, and injected sample volume was 5 μl. The Q-TOF
   conditions were: sheath gas nitrogen 10 l/min at 400 °C; drying gas
   nitrogen 8 l/min at 350 °C; nebulizer pressure 60 psi; nozzle voltage
   0 kV; capillary voltage 3.5 kV. Signals in the m/z range of 100–1700,
   were recorded. Negative mass calibration was performed with a
   G1969–85000 standard mass mix (Supelco Inc., Bellefonte, PA, USA) and
   had a residual error for the expected masses of ±0.2 ppm. Lock masses
   were: TFA (trifluoroacetic acid) anion at m/z 112.9856 and HP-0921
   (+formate) at m/z 966.0007 in negative-ion mode. MS/MS conditions were:
   collision energies between 20 and 60 eV to fragment the parent ions in
   the m/z range of 100–1700; acquisition rate – 2 spectra/s. Data
   processing was performed with Agilent’s MassHunter qualitative analysis
   software version B.05.00 (5.0.519.0). Confidence of compound
   identification based on accurate mass and isotope pattern was expressed
   as the “overall identification score”, computed as a weighted average
   of the isotopic pattern signals of the compound, such as exact masses,
   relative abundances, and m/z distances (spacing). The weights of these
   parameters were: W[mass] = 100, W[abundance] = 60, W[spacing] = 50,
   mass expected data variation 2.0 mDa + 5.6 ppm, mass isotope abundance
   7.5%, mass isotope grouping peak spacing tolerance 0.0025 m/z + 7.0
   ppm. Target identification of compounds was performed with the
   home-made database of grape and wine metabolites called
   GrapeMetabolomics^[238]88.

RNA extraction and analysis

   Total RNA was extracted from 1.2 g of frozen berry powder^[239]89.
   200 µl of extracted RNA was added 12 µl of DNAse buffer and 8 µl of
   5-U/µl DNase TaKaRa DNase I kit (Cat#, 2270 A; TaKaRa, Japan). The
   mixture was incubated for 15 min at 37 °C. Two-hundred microliters of
   24:1 (v/v) chloroform:isoamyl alcohol mixture was added to the samples
   and vortexed for 5 s. The mixture was then centrifuged at 20,000 × g
   for 5 min at 4 °C. The supernatant was precipitated in 1/3 volume of
   10 M ammonium acetate and 10 volumes of 100% cold EtOH (−20 °C). The
   mixture was then incubated for 3 h at −80 °C and then centrifuged as
   described above for 30 min. The pellet was washed with 100 µl of 70%
   cold EtOH (−20 °C), which then was centrifuged as described above for
   5 min. The EtOH was discarded and the pellet was left on the bench to
   dry for 15 min. The pellet was then placed in 30 µl of DEPC water and
   mixed by pipetting. The RNA was purified with an RNA Clean and
   Concentrator Kit (Zymo Research, Irvine, CA, USA).

Bioinformatics analysis of RNA sequences

   RNA was sequenced by the Technion Genome Center (Haifa, Israel)
   following integrity analysis with the TapeStation (Agilent), and
   sequencing libraries were generated with the TrueSeq RNA Sample Prep
   Kit v2 (Illumina) according to the manufacturer’s protocol. RNA
   sequencing was conducted with the Hiseq2500 (Illumina) applied to
   60-bases-long single-end reads; we used V4 reagents (Illumina) that
   yielded 20–25 M pair reads per sample. The raw reads of nine libraries
   — three biological replications for each of the three treatments, T0,
   TC and T15 — were subjected to quality trimming and filtering and
   adapter removal by trimmomatic software^[240]90. Cleaned sequences were
   mapped to the latest reference genome version V2.1 of V. vinifera
   downloaded from the Cribi database^[241]91. The Bowtie software
   alignment protocol^[242]92 was used to align clean reads to the
   reference genome. Abundances were estimated for each V. vinifera
   transcript with the RSEM software package^[243]93. Bioconductor
   EdgeR^[244]94 of the Bioconductor R packages^[245]95 was used to
   identify differentially expressed transcripts for each biological
   replicate, based on the count estimates for each transcript.
   Transcripts were regarded as differentially expressed if they reached
   the threshold of FDR < 0.05 and the log of the proportional change was
   smaller than −1.5 or greater than 1.5. Transcript expression was
   normalized by using trimmed mean of M-values (TMM)^[246]96. All data
   analyzed in this manuscript were deposited in GenBank under bioproject
   accession number PRJNA386228, and the Raw Data SRA accession no. is
   SRP107049. Reproducibility of the replicates can be visualized by
   heat-map analysis (Supplementary Fig. [247]S2). Grape gene orthologs
   related to specific metabolic stages were annotated based on
   MetGenMap^[248]97, Blast2Go^[249]98, Cribi^[250]91 data base
   ([251]http://genomes.cribi.unipd.it) and on orthologous genes from
   tomato or Arabidopsis. STS, WRKY and MYB genes were annotated based on
   recent publication of the grape
   genome^[252]18,[253]21,[254]22,[255]69,[256]99,[257]100. The GO
   term-enrichment analysis was performed based on the free web-based
   PANTHER system on Aug. 31, 2018^[258]101.

Statistical analysis

   Metabolite results were subjected to one-way ANOVA with Tukey’s honest
   significant difference (HSD) test for the non-volatiles or the
   nonparametric comparison with controls by using Dunn’s method for joint
   ranking for the volatiles on a JMP 13.0 platform (SAS Institute, Cary,
   NC, USA). Mosaic plot, PLS-DA and correlation coefficient for volatile
   compound analysis were based on the web-based MetaboAnalyst, version
   3.0 ([259]http://www.metaboanalyst.ca, accessed 26 Jan 2018)^[260]102.
   For the genes’ heat-map (Figs [261]2 and [262]4), genes TMM reads were
   centered by mean and normalized, and then subjected to gene cluster
   (centroid linkage) by Cluster 3.0^[263]103. Heat-maps were visualized
   based on and Java Treeview ([264]http://jtreeview.sourceforge.net/).
   The Venn diagram was visualized based on online Venny V.2.1^[265]104.
   Molecular function visualization was performed on agriGO
   V.1.2^[266]105.

Supplementary information

   [267]Supplementary Figures 1-4^ (484.5KB, docx)
   [268]Supplemetary Tables 1-27^ (467.5KB, xlsx)

Acknowledgements