Abstract

   Resveratrol is a polyphenol compound beneficial to human health, and
   its main source is grapes. In the present study, the molecular
   regulation of resveratrol biosynthesis in developing grape berries was
   investigated using weighted gene co-expression network analysis
   (WGCNA). At the same time, the reason for the resveratrol content
   difference between grape exocarp (skin) and mesocarp (flesh) was
   explored. Hub genes (CHS, STS, F3’5’H, PAL, HCT) related to resveratrol
   biosynthesis were screened with Cytoscape software. The expression
   level of hub genes in the exocarp was significantly higher than that in
   the mesocarp, and the expressions of the hub genes and the content of
   resveratrol in exocarp peaked at the maturity stage. While the
   expression levels of PAL, CHS and STS in the mesocarp, reached the
   maximum at the maturity stage, and F3′5′H and HCT decreased. These hub
   genes likely play a key role in resveratrol biosynthesis. Kyoto
   Encyclopedia of Genes and Genomes (KEGG) pathway analysis further
   indicated that resveratrol biosynthesis was related to flavonoid
   biosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis,
   and stilbene biosynthesis pathways. This study has theoretical
   significance for exploring genes related to resveratrol biosynthesis in
   the exocarp and mesocarp of grapes, and provides a theoretical basis
   for the subsequent function and regulatory mechanism of hub genes.

   Keywords: grapes, resveratrol biosynthesis, RNA-seq, WGCNA, hub genes

1. Introduction

   Resveratrol is the most important stilbene phytoalexin which exists
   naturally in plants and is conveyed as part of its defense mechanism
   [[44]1]. It mainly exists in the form of trans in plants. The
   trans-formed resveratrol is more stable, and its physiological activity
   is stronger than that of cis-resveratrol [[45]2]. Resveratrol is a
   non-flavonoid phenolic compound with antioxidant activity,
   anti-inflammatory, prevention and treatment of cardiovascular disease,
   antibacterial, antiviral, and other pharmacological effects
   [[46]3,[47]4,[48]5,[49]6,[50]7,[51]8,[52]9]. In vitro studies showed
   that resveratrol has a potential antiviral effect against COVID-19
   [[53]10,[54]11]. It has a medical effect and has great potential. The
   more resveratrol to be used in larger-scale clinical trials, the more
   resveratrol is needed. Grapes have the highest amount of resveratrol in
   any known plant. Grapes and their derivatives, including fruit juices
   and wine, are the most important natural sources of resveratrol
   [[55]12].

   The content of stilbene and its morphology in plants that produce
   stilbene vary strongly due to various environmental factors [[56]13].
   The varieties and their developmental stages are the main internal
   factors affecting the synthesis of resveratrol in grapes [[57]14].
   ‘Summer black’ as a triploid, seedless, dark purple variety, is a
   popular table grape in China [[58]15]. Divided into three distinct
   stages based on chemical and morphological characteristics, the initial
   stage of berry growth includes rapid growth and cell division,
   accumulation of organic acids (mainly malic and tartaric acid) in
   vacuoles, and synthesis of tannins and hydroxycinnamic acids. During
   the transition phase, known to viticulturists as veraison, growth
   declines and the berries begin to soften. There is reduced production
   of organic acids and synthesis of volatile secondary metabolites that
   contribute to the typical aroma and flavor of the wine at the ripening
   stage [[59]16]. Resveratrol can be transported to different tissues to
   adapt mechanisms responsive to the environment [[60]17]. Grapes have
   three clear parts: the exocarp, the mesocarp, and the seeds. The
   exocarp and mesocarp together constitute the development and maturation
   of the exocarp [[61]18]. During the veraison, berries experience a
   burst of reactive oxygen species (ROS), as well as a surge in the
   expression of genes that code for enzymes that produce antioxidants
   [[62]19]. Grape exocarp and mesocarp have the same heart-protective
   effects and have comparable antioxidant potential [[63]20,[64]21].
   Flavor-related characteristics, such as sugar and acid content, depend
   primarily on mesocarp [[65]22]. As the fruit ripens, large amounts of
   sugar in the mesocarp inhibit fungal growth [[66]23].

   Resveratrol in grapes mainly exists in leaves and fruits, and grape
   exocarp is an important source of resveratrol content [[67]24]. Its
   content is affected by quite a few factors, and varies greatly between
   different varieties, different times, and different tissue parts of the
   same plant [[68]25,[69]26,[70]27,[71]28,[72]29]. Resistance genes and
   pathogenesis-related (PR) genes are dynamically regulated during fruit
   development, and the transcriptional level of PR-1 in ‘Norton’ exocarp
   is significantly increased during ripening. Phenylalanine pathway genes
   are up-regulated during ‘Norton’ fruit development, and the
   transcription level of stilbene synthase genes is steadily increased
   [[73]30].

   Resveratrol is synthesized across the phenylalanine metabolic pathway.
   Phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H),
   4-coumarate: CoA ligase (4CL), chalcone synthase (CHS), stilbene
   synthase (STS), resveratrol synthase (ST), which are the key enzymes
   involved in phenylalanine metabolic pathways. Phenylpropane metabolism
   is based on phenylalanine or tyrosine as the substrate, under the
   catalysis of phenylalanine ammonia-lyase to produce trans cinnamic
   acid, cinnamic acid under the action of C4H to produce coumaric acid
   [[74]31,[75]32,[76]33]. STS is the key enzyme leading to the
   biosynthesis of resveratrol and stilbene. The expression of the STS
   family in different tissues and fruit development stages in different
   tissues and fruit development stages is of great significance for
   studying the content of resveratrol in fruits [[77]34]. STS and CHS
   belong to the polyketide synthase superfamily, which are the key
   enzymes in the biosynthesis of flavonoids and stilbene phytoalexin,
   respectively. Resveratrol and chalcone synthases are related to
   plant-specific polyketide synthases [[78]35,[79]36,[80]37,[81]38]. Both
   CHS and STS use p-coumarate CoA as substrate and they are ubiquitous in
   plants [[82]39]. CHS and STS are plant-specific Polyketide synthase,
   but STS evolved independently from CHS [[83]40]. It is reported that
   Al4CL and AlCHS genes have potential applications in improving the
   nutritional composition and flavor of wine [[84]41].

   Weighted gene co-expression network analysis is a systemic biology
   approach to describe correlation patterns between genes in microarray
   samples and it can be used to find modules of highly correlated genes.
   A dendrogram was created that similarly expressed genes clustered into
   discrete branches with the most connected nodes or “centres” at the
   branch tips [[85]42]. Wang et al. identified four highly expressed hub
   genes in adrenocortical carcinoma using WGCNA, which were inversely
   correlated with overall survival [[86]43]. Yu et al. used WGCNA to
   reveal a set of hub genes related to chlorophyll metabolic processes in
   Chlorella vulgaris in response to androstenedione [[87]44]. Cytoscape
   is open-source software ([88]https://apps.cytoscape.org (accessed on 15
   July 2022)) for analyzing and visualizing biological networks. It is
   capable of importing networks from various sources, and it also allows
   users to import tabular node data and visualize it on the network
   [[89]45]. Hub genes are several genes that are highly linked in a
   co-expression module and are considered biologically important
   [[90]46]. CytoHubba is a Cytoscape Plug-in for hub object analysis in
   network biology. It can be used to explore important nodes in
   biological networks. In addition, CytoHubba will be able to be combined
   with other plug-ins to develop new profiling protocols to identify hub
   genes [[91]47].

   In this study, we conducted transcriptome sequencing on grape exocarp
   and mesocarp at different developmental stages and investigated
   resveratrol hub genes in summer black grape fruits using WGCNA and
   Cytoscape software.

2. Results

2.1. Change of Resveratrol Content in Grape Mesocarp and Exocarp

   The contents of resveratrol in grape mesocarp and exocarp were
   significantly different in different stages. However, there was no
   significant difference in the resveratrol content of the mesocarp in
   the first four stages ([92]Figure 1A). The content of resveratrol in
   the mesocarp of berry increased significantly in S5, which reached 0.39
   ug/g. The resveratrol content in the exocarp showed no significant
   difference in S1, S2, and S3. The content of resveratrol in the exocarp
   reached the maximum at S5 stage, which reached 6.41 ug/g. Under the
   given conditions, the retention time of resveratrol was about 0.61 min
   ([93]Figure 1B).

Figure 1.

   [94]Figure 1
   [95]Open in a new tab

   (A) UPLC heat map of trans-resveratrol content in exocarp and mesocarp
   of ‘Summer Black’ grape at different times of berry development, which
   were expressed as log10 fold change. The darker the heat map, the
   higher the resveratrol content. (B) Ultrahigh performance liquid
   chromatography retention times of mesocarp and exocarp at different
   stages of berry. Different line colors represent different stages.

   The Illumina HiSeq sequencing platform was used to perform
   double-terminal sequencing of cDNA libraries of 18 grape exocarp and
   mesocarp samples from three stages (S1, S3, S5) using second-generation
   sequencing technology. A total of 128.01 Gb clean data were obtained
   following quality assessment and data filtering, with more than 92.78%
   Q30 scores of clean bases, and the mapped ratios were between 81.48%
   and 91.17% showing that explicit data can be used for subsequent
   analysis ([96]Table S5).

2.2. Construction of Weighted Gene Co-Expression Network

   By obtaining the RNA expression data of S1, S3 and S5 in the mesocarp
   and exocarp of the ‘summer black’ grape, the co-expression network was
   constructed on the basis of the optimal soft threshold. The absolute
   median difference (MAD) method was used to filter the genes with low
   expressions or small changes between samples, and 21,558 genes were
   selected for WGCNA analysis. The genes were divided into different
   modules, and the gene clustering tree was drawn ([97]Figure 2A). The
   figure can be divided into three parts, from top to bottom. The first
   part is the phylogenetic clustering tree of genes. The second part is
   the module color display of corresponding genes. Each color represents
   a module in the gene co-expression network constructed by WGCNA. The
   third part shows the correlation between genes and their modules of
   each trait-related sample. The redder the color, the more positively
   correlated it is, whereas the opposite is true for blue. Based on the
   topological overlap matrix, a heat map of the correlation between genes
   was drawn, where the darker the color, the stronger the interaction
   between genes ([98]Figure 2B). As shown in the figure ([99]Figure 2C),
   ten modules (grey60, midnight blue, black, cyan, blue, brown, magenta,
   purple, light cyan, and red) were identified from WGCNA, each of which
   contained a different number of genes. Defined with different color
   codes, the genes in the modules are highly correlated with resveratrol
   behavior. By observing the correlation between the module and trait, it
   was found that three modules were significantly related to the
   resveratrol content, namely magenta (r = 0.77, p = 2 × 10^−4), cyan (r
   = 0.76, p = 2 × 10^−4), purple (r = 0.61, p = 7 × 10^−3).

Figure 2.

   [100]Figure 2
   [101]Open in a new tab

   (A) Phylogenetic tree heat map associated with trans-resveratrol
   (trans-res) content. (B) Gene co-expression network heat map: on the
   left and top of the figure are the results of symmetric systematic
   clustering trees and gene modules. The domain represents the
   dissimilarity between genes, and the smaller the value, the darker the
   color. Genes between modules of the same color are darker, and genes
   between modules are lighter. (C) Heat map of correlation between
   co-expressed gene modules and resveratrol traits. Each row represents a
   module, and the vertical column represents the content of the
   resveratrol. The numbers in the rectangular box represent the
   correlation coefficient between the module and trait, and the
   corresponding p value. Red represents the positive correlation between
   the module and the trait, and blue represents the negative correlation.

2.3. Functional and Pathway Enrichment Analysis

   KEGG enrichment analysis was performed on magenta, cyan, and purple
   modules to determine the metabolic pathways related to resveratrol
   synthesis ([102]Table S1). Among these pathways, flavonoid
   biosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis,
   and stilbene biosynthesis were the most significantly enriched
   ([103]Figure 3). It was found that a total of 45 unigenes ([104]Table
   S2) were significantly enriched in the flavonoid biosynthesis pathway,
   among which 25 unigenes encode CHS, and the remaining 20 unigenes
   encode F3’5’H (flavonoid 3′, 5′-hydroxylase), CYP73A (trans-cinnamate
   4-monooxygenase), CHI (chalcone isomerase), F3H (naringenin
   3-dioxygenase), PGT1 (phlorizin synthase), HCT (shikimate hydroxyl
   cinnamoyl transferase). A total of 25 unigenes were significantly
   enriched in the phenylpropanoid biosynthesis pathway, among which 12
   unigenes encode PAL, and the remaining 13 unigenes encode 4CL, COMT
   (caffeic acid 3-O-methyltransferase), peroxidase, F5H
   (ferulate-5-hydroxylase), beta-glucosidase, CCR (cinnamoyl-CoA
   reductase), HCT. It is interesting that a total of 12 unigenes were
   significantly enriched in the phenylalanine metabolism pathway, and all
   of them were encoded as PAL. In total, 11 unigenes were significantly
   enriched in the stilbene biosynthesis pathway. Eight of them encode
   STS, and three unigenes encode HCT, C4H.

Figure 3.

   [105]Figure 3
   [106]Open in a new tab

   KEGG classification scatter plot of the top 10 pathways with the most
   enriched genes in the three modules. (A) Magenta module. (B) Cyan
   module. (C) Purple module. The enrichment KEGG classification is shown
   on the vertical axis, and the enrichment fraction is shown on the
   horizontal axis.

2.4. Screening of Related Hub Genes

   Using CytoHubba to visualize the interaction network MCC algorithm, the
   top 10 genes most related to resveratrol content in the three modules
   were selected ([107]Figure 4A–C). Through homology comparison and gene
   annotation interaction, 12 hub genes related to resveratrol
   biosynthesis were obtained ([108]Table S3). Based on the pathway map
   analysis of hub genes ([109]Figure 5), among which 2 genes
   (VIT_16s0039g01300, VIT_16s0039g01240) encode to regulate the PAL
   enzyme, which plays a role in the first stage of resveratrol
   biosynthesis. 2 genes (VIT_16s0100g00900, VIT_16s0100g01190) encode to
   regulate the STS enzyme, which plays a role in the final step of
   resveratrol biosynthesis. In the flavonoid pathway, 3 genes
   (VIT_16s0100g00930, VIT_16s0100g00780, VIT_16s0100g01000) were
   annotated to the CHS enzyme. 4 genes (VIT_06s0009g02880,
   VIT_06s0009g02970, VIT_06s0009g02810, VIT_06s0009g02840) were annotated
   to the F3′5′H enzyme. 1 gene (VIT_14s0030g01950) was annotated to the
   HCT enzyme. The first step in the phenylpropanoid pathway is the
   deamination of phenylpropanoid acid to cinnamic acid by PAL. PAL had no
   significant change between mesocarp and exocarp from S1 to S3 stage,
   but increased significantly from S3 to S5 stage. STS catalyzes the
   biosynthesis of the stilbene backbone from three malonyl-CoA and a
   CoA-ester of a cinnamic acid derivatives in a single reaction. The
   contents of STS and PAL were the same, and S5 reached its maximum value
   at the exocarp and mesocarp, while the contents of S5 at the early
   stage were little or none. CHS is an important enzyme in flavonoid
   metabolism and a key point in regulating the biosynthesis of different
   flavonoid compounds. CHS reached its maximum value at the S5 stage in
   the exocarp with little accumulation and no significant change. CHS in
   mesocarp was almost nonexistent from S1 to S3 stage, but increased
   significantly in S5 stage. F3 ‘5’ H is synthesized by the flavonoid
   pathway, biosynthetic by catalyzing the hydroxylation of flavonoids at
   the 3 ‘, and 5’ positions. F3 ‘5’ H increased gradually in the exocarp,
   reached the maximum value in the S5 stage, and showed a decreasing
   trend in the mesocarp. In the phenylpropane pathway, HCT catalyzes the
   formation of p-coumadyl CoA into p-coumadyl shikimic acid, followed by
   the formation of caffeic shikimic acid. Further functionalization was
   catalyzed by HCT to produce caffeoyl CoA. HCT in exocarp and mesocarp
   had little change in previous periods, while S5 content increased.

Figure 4.

   [110]Figure 4
   [111]Open in a new tab

   Interaction analysis of hub gene networks in significantly enriched
   resveratrol modules. (A) magenta module, (B) cyan module, (C) purple
   module. The hub genes and non-hub genes are represented in red and blue
   circles, respectively. The size of the point represents the weighted
   degree, and the larger the weighted degree, the larger the point. (D)
   exocarp and mesocarp quantitative heat map. The expression pattern of 8
   selected genes identified by RNA-seq was verified by RT-qPCR.

Figure 5.

   [112]Figure 5
   [113]Open in a new tab

   Heat map of pathway hub genes. In the figure, from left to right,
   changes in the relative expression level of the hub gene in exocarp and
   mesocarp during S1, S3 and S5 are shown, and the changes are log10
   times. The pathway can be divided into four sections: phenylalanine
   metabolism, phenylpropanoid, stilbene and flavonoid pathways.

2.5. Real-Time Quantitative PCR Validation of the Identified Genes

   Eight genes were selected from the four pathways enriched by KEGG,
   among which 4 were hub genes and 4 were highly expressed genes. RT-qPCR
   was performed in the exocarp and mesocarp of 5 different stages
   ([114]Figure 4D). The results showed that the 8 genes expressed at the
   same level and pattern as the FPKM values of transcriptome sequencing,
   indicating the reliability of the RNA-Seq data. In addition, the gene
   expression in the fruit exocarp increased significantly during the
   ripening stage. The mesocarp changes slightly compared to the exocarp.

3. Discussion

   In this study, 10 gene co-expression modules were obtained by
   constructing WGCNA, and three co-expression modules magenta, cyan, and
   purple were identified as resveratrol-specific modules, the genes in
   these modules were involved in resveratrol biosynthesis during the
   grape growth process of grapes. The hub genes (CHS, STS, F3’5’H, PAL,
   HCT) of resveratrol biosynthesis in mesocarp and exocarp at different
   developmental stages were further screened by Cytoscape. It was found
   that flavonoid biosynthesis, phenylpropanoid biosynthesis,
   phenylalanine metabolism, and stilbene biosynthesis were the most
   significantly enriched pathways.

   Many compounds are derived from phenylalanine via the general
   phenylpropanoid pathway, and multiple downstream derivatives of the
   original phenylpropanoid scaffolds are ubiquitous in plants and are
   used to maintain their structural integrity, UV protection,
   reproduction, and growth. It plays an important developmental role in
   cell physiology and signaling. Hu et al. identified four key enzymes
   (ThPAL, ThC4H, Th4CL, and ThRS) involved in the RES biosynthesis
   pathway [[115]48]. PAL catalyzes the first reaction in the biosynthesis
   of various phenylpropanoid natural products from phenylalanine,
   including lignin, flavonoid pigments, and phytoantitoxins [[116]49].
   PAL activity in the exocarp is thought to be directly involved in the
   synthesis of phenolic substances during grapefruit ripening [[117]50].
   The flavonoid metabolism pathway is closely linked to phenylpropanoids.
   Cinnamyl CoA and 4-cinnamyl CoA coumarin are precursors for flavonoid
   synthesis. Their biosynthesis is subject to related regulatory enzymes
   such as PAL in the phenylpropanoid pathway. Subsequently, chalcone is
   synthesized from 4-chammaryl CoA via CHS. After this step, different
   flavonoid subsets are controlled by CHS, F3′5′H, HCT, and other enzymes
   through the production of a modified molecular backbone. Flavonoids and
   related stilbene all stem from polyketide extension and subsequent
   cyclization of general phenylpropanoid substrates by CHS or related
   plant polyketide synthases [[118]51]. Zhu et al. found that MYB30 and
   MYB14 form an inhibitory activation module with WRKY8 in the flavonoid
   pathway for stilbene biosynthesis in grapes [[119]52]. According to
   reports, STS has developed from CHS several times in its evolution
   [[120]40]. There is a coregulation between the STS and CHS genes during
   grape development, which is consistent with previous studies [[121]53].
   CHS plays an important role in the accumulation of phenolic substances
   and total flavonoids in grapefruits [[122]54]. Although STSs have been
   isolated and identified in many species, the gene regulation mechanism
   of stilbene biosynthesis remains largely unknown [[123]55]. In our
   study, the contents of STS and CHS were significantly up-regulated at
   the maturity stage. This was confirmed by previous studies that the
   up-regulation of STSs and CHSs may also up-regulate the content of
   resveratrol, and that enhanced STS expression can produce more
   resveratrol [[124]35,[125]56,[126]57]. Gatto et al. analyzed the
   expression profiles of STS and PAL and found that their concentrations
   increased from variety to maturity, which was consistent with our
   findings [[127]58]. Ageorges et al. showed that the expression of
   F3′5’H structural genes of the flavonoid pathway, was investigated
   throughout ripening by real-time RT-PCR [[128]59]. There is evidence
   that the HCT gene relates to shikimic acid-mediated regulation of plant
   phenol metabolism [[129]60]. Yang, Min et al. showed that 31 unigenes
   encoded 15 key enzymes, mainly related to flavonoid biosynthesis, and
   HCT was one of them [[130]61]. Fan S et al. found that the CtHCT gene
   appeared to be associated with abiotic stress response through
   expression profiling of different flowering stages under light and MeJA
   treatment [[131]62]. Jim et al. found that PtoHCT9 and PtoHCT10 are
   active in winter and play a role in plant development and response to
   cold stress [[132]63]. Hoffmann et al. found that HCT genes participate
   in phenylpropanoid biosynthesis and influence the content of various
   substances, including flavonoids, phenolic acids, stilbenes, and
   coumarins [[133]64]. Therefore, different interplay mechanisms of HCT
   and F3′5’H might occur in berry mesocarp and exocarp.

   In addition, according to RNA-seq and RT-qPCR results, we found that
   the expression profiles of CHS, STS, PAL, HCT, and F3′5’H were
   different in exocarp and mesocarp at different stages. Abiotic stress
   increased the expression of genes encoding various enzymes of the
   phenolic biosynthetic pathway [[134]65]. Resveratrol is known as a
   plant phytoalexin. Activation of pathogen defense in the exocarp of
   nearly ripe berries appears to be a feature of grape ripening. The
   exocarp, which is exposed to many external stresses such as fungal
   infections and ultraviolet radiation, may require more resveratrol
   protection than the mesocarp. The expression level of hub genes in the
   exocarp was much higher than that in the mesocarp. The exocarp also
   acts as an interface to the external environment, protecting internal
   tissues from pathogens and abiotic stressors [[135]66].
   Phenylpropanoids-related transcripts with significant differences
   between grape exocarp and mesocarp throughout the ripening process. The
   expression of macromolecule transport-related genes remained highly
   active in the skin during the whole maturation process. Lijavetzky D et
   al. found that exocarp ripening can be considered a more complex
   process due to the wide variety of functions active during dermal
   maturation [[136]67]. This higher complexity, at least in terms of gene
   expression, is supported by the identification of more specific exocarp
   activation processes such as stilbene biosynthesis.

   The numbers of up-regulated and down-regulated genes across different
   stages in mesocarp and exocarp are presented in [137]Table S6. During
   the S1 stage, a total of 2523 different expressed genes were identified
   between the mesocarp and exocarp. During the S3 stage, a total of 3139
   different expressed genes were identified between the mesocarp and
   exocarp. During the S5 stage, a total of 2743 different expressed genes
   were identified between the mesocarp and exocarp. This indicated that
   exocarp gene expression was more active.

   The content of resveratrol in the exocarp was much higher than that in
   the mesocarp. The exocarp of grape berries acts as a physical and
   biochemical barrier to protect the ripe berries from pathogens. Studies
   have shown that the exocarp becomes more resistant to pathogens to
   protect the ripe grape berries before they ripen [[138]68,[139]69].
   Similarly, the expression level of hub genes in the exocarp was much
   higher than that in the mesocarp. It indicates that these hub genes
   directly or indirectly affect resveratrol levels.

4. Materials and Methods

4.1. Sample Collection

   The experimental base is located in Haidi Grape Orchard, Xiamen City,
   Fujian Province, China. The grape variety “Summer Black” of the same
   age (6 years) is planted in a facility sheltered from the rain and
   covered with a transparent plastic polyethylene film. Samples were
   harvested from November 11th to December 20th, 2021. The fruit was
   collected from five different developmental stages ([140]Figure 6)
   according to the BBCH scheme [[141]70]: S1, green fruit stage, day 15
   after flowering, begin of berry touch; S2, immature green, berry touch
   complete; S3, red-appeared, berries begin to brighten in color; S4,
   full-red, softening of berries; and S5, purple-black, berries ripe for
   harvest. Three clusters per vine, and 6 vines per stage were randomly
   picked. Mixed berries selected at random from the top, middle and
   bottom of each cluster were used for analysis. There was no evidence of
   stress symptoms or disease in each sample. All samples at the same
   ripening stage with no mechanical damage were harvested. The mesocarp
   and exocarp were frozen in liquid nitrogen immediately after separation
   and stored at −80 °C. Three biological replicates were used for all
   experiments in each stage.

Figure 6.

   [142]Figure 6
   [143]Open in a new tab

   ‘Summer black’ grapes at different stages.

4.2. Extraction and Determination of Resveratrol

   Resveratrol extraction was based on a previously published method, with
   slight modifications [[144]71]. The samples used were randomly selected
   from each grape lot that had been stored in a −80 °C refrigerator.
   Exocarp or mesocarp samples (1 g) were ground in liquid nitrogen and
   then 20 mL of ethanol was added, followed by centrifugation at 10,000
   rpm for 10 min. The supernatants were evaporated to dryness by rotary
   vacuum evaporation at 50 °C. Dried residues were then dissolved in 5 mL
   ethanol and stored at −40 °C before analysis by UPLC (Ultra Performance
   Liquid Chromatography). The mixture was filtered with a 0.22 µm syringe
   filter (Biosharp, Anhui, China). The extracted resveratrol solution was
   analyzed and quantified by UPLC-chromatography-diode array detector
   (Waters H-Class TUV QDa (Waters Corp, Milford, MA, USA)), respectively.
   The column temperature was 30 °C, and the detection wave was 306 nm.
   Elution was performed using a mobile phase made up of 0.1% (v/v) formic
   acid aqueous solution-acetonitrile (35:65) at a flow rate of 0.4
   mL·min^−1. The injection volume was 1 μL. The isocratic gradient run
   time was 2 min. For ultraviolet spectrophotometer detection, each
   sample was repeated 3 times, the scanning range was 240~600 nm, the
   maximum absorption wavelength of resveratrol is 306 nm.
   Trans-resveratrol standard was purchased from Yuanye, Shanghai, China.
   Samples were extracted in the dark. Each sample was repeated three
   times.

4.3. RNA Sequencing (RNA-Seq)

   Using the Illumina HiSeq sequencing platform from the Biomarker
   Biotechnology Corporation (Beijing, China), the cDNA library of 18
   samples of ‘Summer Black’ grape exocarp and mesocarp in three stages
   (S1, S3, S5) was sequenced by second-generation sequencing technology.
   After the sample test is qualified, the library is constructed.
   Eukaryotic mRNA was enriched with magnetic beads with Oligo (dT), and
   mRNA was randomly interrupted by the Fragmentation Buffer (YEASEN,
   Shanghai, China). Using mRNA as a template, the first cDNA strand was
   synthesized using six-base random hexamers. A second cDNA strand was
   then synthesized by adding buffer, dNTPs, RNase H, and DNA polymerase
   I, and the cDNA was purified using AMPure XP beads (YEASEN, Shanghai,
   China). The purified double-stranded cDNA was then end-repaired, A tail
   was added, and sequencing connectors were connected. AMPure XP beads
   were used for segment size selection. Finally, the cDNA library was
   enriched by PCR. After the construction of the library, the Q-PCR
   method was used to accurately quantify the effective concentration of
   the library (effective concentration of the library > 2 nM) to ensure
   the quality of the library. After a qualified library check, different
   libraries are pooled according to the target on-machine data volume,
   and sequenced by the Illumina platform. Clean Data was obtained by
   filtering the dismounted data, and sequence alignment was performed
   with the specified reference genome. The Mapped Data obtained is used
   for library quality assessment such as inserted fragment length test,
   randomness test, etc.

4.4. Weighted Gene Co-Expression Network Analysis and Gene Functional
Annotation and Expression Analysis

   After obtaining the read counts of genes, the correlation and gene
   significance of gene expression profiles and intra-module connections
   were analyzed by the weighted gene co-expression network analysis
   (WGCNA) software tool in BMKCloud ([145]https://www.biocloud.net/,
   accessed on 10 July 2022). Firstly, data filtering is carried out to
   detect and eliminate outliers. Secondly, a scale-free network was
   obtained by clustering the gene expression level of each sample. The
   soft threshold power was determined by calculating the correlation
   value between each gene pair. The minimum number of genes per module is
   set at 50 genes. Finally, a weighted gene co-expression network was
   constructed based on the correlation of gene expression levels. The
   correlation between modules and resveratrol was determined by
   estimating the module-trait relationship. The Topological overlap
   measure (TOM) was used to calculate WGCNA to calculate the degree of
   correlation between genes. The module with the highest weighted
   correlation coefficient is selected as the module of interest. Compared
   with KEGG, functional annotation of pathways and related metabolic gene
   information were obtained. The role of selected genes was determined by
   functional and pathway enrichment analysis to determine the link
   between these genes and resveratrol.

4.5. Screening of Hub Genes

   Based on the analysis of transcriptome results, the reliability of
   transcriptome results verified by real-time quantitative RT-qPCR, and
   the CytoHubba Visual Interaction Network MCC algorithm of Cytoscape,
   the expression changes of the top 10 hub genes related to resveratrol
   biosynthesis in the exocarp and mesocarp of grapes in five different
   periods were analyzed, and Gephi ([146]https://gephi.org/) (accessed on
   21 August 2022) was used to visualize the module network.

4.6. Real-Time Quantitative Reverse Transcription PCR Validation

   Total RNAs of exocarp and mesocarp were extracted using RNAprep Pure
   Plant Plus Kit (TIANGEN, Beijing, China) with three biological
   replicates. Reactions were set up in Hieff qPCR SYBR Green Master Mix
   (Yeasen, Shanghai, China) according to the manufacturer’s instructions,
   with gene-specific primers (0.4 μM) in a final volume of 20 μL. RNA
   integrity was verified by RNase-free agarose gel electrophoresis. The
   RNA quantity and concentration were checked using the Quawell Q5000
   spectrophotometer (Quawell, Sunnyvale, CA, USA). Thermal cycling
   conditions involved an initial 95 °C melt (5 min), followed by 40
   cycles of 95 °C (10 s) and 60 °C (30 s). Assays were conducted with a
   C1000 Thermal Cycler fitted with a CFX96 Real-time PCR detection system
   (BioRad, Hercules, CA, USA), and analyzed using the CFX Manager
   software (BioRad). The gene primers were designed using Premier 5.0
   software. Primers used in this study are listed in [147]Table S4, using
   VvGAPDH as an internal reference. The data were analyzed by the
   2^−ΔΔCt(−delta delta CT) method.

4.7. Statistics Analysis

   The results were expressed as the mean ± SD of three biological
   replicates. One-way ANOVA was used to analyze the significance of
   different samples in different stages, followed by SPSS 26.0
   statistical software Tukey multiple comparison tests (p < 0.05). The
   gene expression level was shown by the log10 fold change value. Origin
   2021 and Gephi were applied for the construction of the figures.

5. Conclusions

   Resveratrol-specific modules were obtained by constructing WGCNA, and
   the genes in these modules were involved in the biosynthesis of
   resveratrol during grape growth. The key genes of resveratrol
   biosynthesis in mesocarp and exocarp at different developmental stages
   were screened out with Cytoscape software. Hub genes such as CHS, STS,
   PAL, F3 ‘5’ H and HCT were identified in the exocarp and mesocarp of
   grape at different developmental stages, showing that they might have
   related with biosynthesis of resveratrol. The expression level of hub
   gene in exocarp was significantly higher than that in mesocarp. The
   exocarp needs to produce more resveratrol to defend against the
   environment. These results provide valuable insights into the
   biosynthesis and molecular biological functions of resveratrol.

Acknowledgments