Transcriptomics integrated with metabolomics reveals the effect of regulated deficit irrigation on anthocyanin biosynthesis in Cabernet Sauvignon grape berries

Journal Pre-proofs Transcriptomics Integrated with Metabolomics Reveals the Effect of Regulated Deficit Irrigation on Anthocyanin Biosynthesis in Cabernet Sauvignon Grape Berries Bohan Yang, Shuang He, Yuan Liu, Buchun Liu, Yanlun Ju, Dengzhao Kang, Xiangyu Sun, Yulin Fang PII: DOI: Reference:

S0308-8146(20)30015-7 https://doi.org/10.1016/j.foodchem.2020.126170 FOCH 126170

To appear in:

Food Chemistry

Received Date: Revised Date: Accepted Date:

11 August 2019 27 December 2019 6 January 2020

Please cite this article as: Yang, B., He, S., Liu, Y., Liu, B., Ju, Y., Kang, D., Sun, X., Fang, Y., Transcriptomics Integrated with Metabolomics Reveals the Effect of Regulated Deficit Irrigation on Anthocyanin Biosynthesis in Cabernet Sauvignon Grape Berries, Food Chemistry (2020), doi: https://doi.org/10.1016/j.foodchem.2020.126170

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Transcriptomics Integrated with Metabolomics Reveals the Effect of Regulated Deficit Irrigation on Anthocyanin Biosynthesis in Cabernet Sauvignon Grape Berries Bohan Yang,1, # Shuang He,1, # Yuan Liu,2 Buchun Liu,2 Yanlun Ju,1 Dengzhao Kang,1,3 Xiangyu Sun,1, * and Yulin Fang1, ** 1 College

of Enology, College of Food Science and Engineering, Viti-viniculture Engineering

Technology Center of State Forestry and Grassland Administration, Shaanxi Engineering Research Center for Viti-Viniculture, Heyang Viti-viniculture Station, Northwest A&F University, Yangling, 712100, China 2

Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of

Agricultural Sciences, Beijing 100081, China 3 Xinjiang

Panyu winery co. LTD, Bohu, 841400, China

Correspondence to: *Xiangyu Sun, Tel/ Fax: +86-29-8709-2107. Email: [email protected] **Yulin Fang, Tel/ Fax: +86-29-8709-1874. Email: [email protected]

Running title: Revealing the Anthocyanin Synthesis of Grapes under RDI through Omics

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Abstract: Regulated deficit irrigation (RDI) is a new type of water-saving irrigation technology developed in recent years which was well suited to arid and semi-arid grape plant areas. The anthocyanin synthesis of grapes under RDI was revealed through omics in this study. RDI slightly decreased the hundred-grain weight and increased the soluble solid content, juice pH, reducing sugar content, and total anthocyanin content. Meanwhile, the total acid content decreased before ripening. Transcriptomics and metabolomics analyses revealed that large numbers of differentially expressed genes (DEGs) and significantly changed metabolites (SCMs) were filtered in the RDI groups. RDI1 with 30% ETc upregulated 7 related gene expression levels in the anthocyanin biosynthetic pathway and also increased some metabolites contents. Eventually, the contents of most monomeric anthocyanins in the RDI groups were increased, and the proportion of Mv increased in the ripe grapes of the RDI groups. In all, RDI is a useful water-saving irrigation method whcih could also increase anthocyanin content in grapes. Keywords: grape; anthocyanin biosynthesis; regulated deficit irrigation; transcriptomics; metabolomics Graphical abstract

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1. Introduction Anthocyanins are important water-soluble pigments to grapes that are primarily present in berries and cellular fluids, and they play a decisive role in the color of grape fruits (Boss & Davies, 2009). The evaluation of wine appearance is normally the first step in wine tasting, while the color determines the consumer’s first impression of it. Therefore, the wine color is an essential quality index, which is mostly affected by the anthocyanins. The differences in the anthocyanin type and content in grape berries not only affects the quality and style of the final wine but also leads to the quality potential of wine as well as its commodity value (Liang et al., 2008); what’s more, the anthocyanins were also an important nourishing compositions with high antioxidant ability and contributed greatly to the health function of wine (Oliveira, Perez-Gregório, de Freitas, Mateus, & Fernandes, 2019; Sun et al., 2020). The plant roots absorb nutrients to promote plant growth, the ability of which is affected by soil factors (Cheng, He, Yue, Wang, & Zhang, 2014). By managing irrigation systems, the soil status could be regulated to help nutrient uptake in the plant roots. Finding the optimal irrigation amount for different plants could not only further the control of the plant's absorption of nutrients but also improve the fruit quality (Ju, Liu, Zhao, Meng, & Fang, 2016), which is so important for food industry (Zhang et al., 2019a, 2019b). Regulated deficit irrigation (RDI) is a new type of water-saving irrigation technology developed in recent years (Edwards & Clingeleffer, 2013; Yang et al., 2020). The application of RDI could increase the economic coefficient of horticultural crops to a certain extent under the condition of reducing water consumption. At present, RDI is widely used in wine grape production, which could significantly improve the ecological and economic benefits in viticulture systems (Terry & Kurtural, 2011). At present, some researchers believe that a water deficit leads to changes in plant endogenous hormone levels that affect the plant’s metabolism. Water stress signals are 4

transmitted to leaves through abscisic acid produced by the plant roots, thus leading to changes in the stomatal pore aperture on the leaves, which ultimately reduces transpiration. With the aim of improving the water use efficiency and controlling reproductive growth, it has been shown that abscisic acid could induce and enhance the aquaporin activity in plant roots (Kaldenhoff, Ribas-carbo, Sans, Lovisolo, Heckwolf, & Uehlein, 2008; Romero, Pérez-Pérez, Del Amor, Martinez-Cutillas, Dodd, & Botía, 2014; Speirs, Binney, Collins, Edwards, & Loveys, 2013), or could play a role similar to aquaporin. Some researchers believe that abscisic acid itself could be used as a signaling molecule to regulate water management in plants (Faci, Medina, Martínez-Cob, & Alonso, 2014; Medrano et al., 2015). Internal factors and external factors combined effect the biosynthesis of anthocyanins. Internal factors include the varieties, hormone levels, sugar accumulation levels and so on. The genetic characteristics of grapes determine the great variation in the contents and species of anthocyanins among different varieties. Sugar is an important basis for secondary metabolites. The precursors of anthocyanin biosynthesis are derived from glycolysis. Most of the structural genes and regulatory genes of anthocyanin biosynthesis were regulated by sugar (Teng, Keurentjes, Bentsink, Koornneef, & Smeekens, 2005). Sugar in grape berries also plays an important role in anthocyanin biosynthesis (Hayes, Davies, & Dry, 2007; Pastenes, Villalobos, Ríos, Reyes, Turgeon, & Franck, 2014; Rolland, Baena-Gonzalez, & Sheen, 2006; Terrier et al., 2005; Vignault et al., 2005). External factors include the water, light, temperature, cultivation measures, soil composition and so on. Researchers have found that the anthocyanin content in grape fruits decreases after shading treatment. It had also been found that the proportions of delphinidin, delphinidin derivatives, and corresponding acylated anthocyanins in the total anthocyanins increased after grapes underwent shading treatment (Cheng, et al., 2014; Downey, Harvey, & Robinson, 2004; Ristic et al., 2007). High temperature during veraison would seriously affect the biosynthesis of anthocyanins, resulting in difficulties in 5

accumulating pigments for grapes, while low temperatures at night could promote anthocyanin biosynthesis (Mori, Goto-Yamamoto, Kitayama, & Hashizume, 2007). Cultural practice could not only control the grape growth and anthocyanin biosynthesis by altering the external environment (light, temperature, water, etc.), but also regulate anthocyanin biosynthesis by changing the internal environment (endogenous hormone content, sugar accumulation level, etc.) (Cortell, Halbleib, Gallagher, Righetti, & Kennedy, 2005; Greven, Bennett, & Neal, 2014; Prajitna, Dami, Steiner, Ferree, Scheerens, & Schwartz, 2007). Previous studies have shown that RDI could cause vine tendrils to fall off and new shoots to stop growing (Edwards & Clingeleffer, 2013). A moderate water deficit could increase the total anthocyanin content in grapes by 30-50% and improve the degree of methylation of anthocyanins as well as the proportion of methylated anthocyanins in the total anthocyanins (Ju et al., 2019). However, although there have been many studies on these biochemical indices, there is still a lack of systematic studies on the mechanism of anthocyanin production in Cabernet Sauvignon (Vitis vinifera L.) grapes thus far, which is very important to clarify the mechanism of the effect of RDI on the anthocyanins. Therefore, the aim of this study was to clarify the mechanism of the effect of RDI on anthocyanin biosynthesis and metabolism using biochemistry and transcriptomics integrated with metabolomics in Cabernet Sauvignon berries to provide more evidence to clarify the anthocyanin metabolic pathways after treatment with RDI. The hope is that the effect of RDI can be explained from an integrative omics perspective and provide theoretical basis and guidance for the growth of wine grapes. 2. Materials and methods 2.1 Field conditions and plant materials The experiment was conducted in 2018 at the Rixin Agricultural Park (34°53′N, 108°84′E), Jingyang, Shaanxi, China, with the soil details shown in Table S1, and the weather 6

conditions in Fig S1. The plants in the vineyard were 7-year-old Cabernet Sauvignon grape vines, of which the frame type was VSP. The plant spacing was 1.0 m×3.0 m with drip irrigation tape, and the pruning method was short-cutting. There were 6 rain shelters in the vineyard (3 rows of vines in each shelter, 5 blocks per row, totaling 75 individual vines per shelter). A total of 6 rows of vines in 2 shelters were randomly selected for the RDI treatment. Three treatment groups were set up for the experiment, which were the RDI1, RDI2 and CK groups. Each group was watered according to their estimated evapotranspiration (ETc), respectively, from the time the grape unearthed to 30 days before harvest (Song, Shellie, Wang, & Qian, 2012). The grapevines were watered with 30% ETc (RDI1), 50% ETc (RDI2) and 100% ETc (CK) (Egea, Nortes, González-Real, Baille, & Domingo, 2010). The amount of irrigation was controlled according to the time of drip irrigation, and the amount of irrigation during every phenological period was calculated by the method of previous study. The amount of irrigation was controlled by controlling the irrigation time, as the vines received water with two 2.4 L/h drippers per plant and the irrigation amount was calculated by ETc. Vine water status was monitored by measuring leaf water potential at midday (ψmd) using pressure chamber. ETc was calculated using the Pennman-Monteith model (Allen, Pereira, Raes, & Smith, 1998; Allen, Smith, Pereira, Raes, & Wright, 2000), with the details shown in Table S2. Five hundred berries were sampled for each replicate at 8, 10, 12, 14 and 16 weeks after florescence (WAF), and each treatment group had 3 replicates. Immediately, a sufficient number of berries were randomly selected to determine the hundred-berry weight, reducing sugar content, total acid content, soluble solid content and pH of the juice after sampling. All samples used for HPLC-MS, qRT-PCR, transcriptomics, and metabolomics were frozen in liquid nitrogen and then stored in -80℃ for further analysis. 2.2 Determination of physicochemical indices of berries The hundred-berry weight was measured after washing with distilled water and drying 7

using filter paper. The reducing sugar content and the total acids were determined by the method of OIV, which was published in 2012 (OIV, 2012). The soluble solid content was determined with a hand-held digital Atago PAL-1 meter (Atago Co. Ltd., Japan) and indicated by the degrees brix. The pH was measured with a Mettler Toledo FE20 Desktop pH Meter (Mettler Toledo Instruments Co. Ltd., Shanghai, China). The total anthocyanin content (TAC) in berries was estimated according to the pH differential method (Ma et al., 2017, 2019a, 2019b; Meng et al., 2012). 2.3 RNA extraction, illumine sequencing and transcriptome data analysis The grape berries at 10 WAF were used for transcriptomics and metabolomics analyses because the anthocyanin content accumulated faster during this period. The total RNA was extracted from 3 biological replicates of grape berries using Plant RNAout (TIANDZ, Beijing, China) according to the manufacturer’s instructions. The degradation and contamination were monitored on 1% agarose gels. The RNA purity was checked using the NanoPhotometer spectrophotometer (IMPLEN, CA, USA). A Qubit RNA Assay Kit in a Qubit 2.0 Flurometer (Life Technologies, CA, USA) was used to measure the RNA concentration. The RNA integrity was checked using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA). A total amount of 3 µg of RNA per sample was used to generate a library using NEBNext. Then, sequencing the libraries on an Illumina Hiseq platform,125 bp/150 bp paired-end reads were generated. Custom Perl scripts extracted sequence data were used, in which the base-pair qualities were Q ≥ 20. The filtered reads were mapped to the reference genome (https://www.ncbi.nlm.nih.gov/genome/401) using the HISAT2 software (Kim, Langmead, & Salzberg, 2015). Fragments per kilobase of transcript per million mapped reads (FPKM) was used as an indicator of the transcription or gene expression level. The DESeq2 was used to identify differentially expressed genes (DEGs) (Love, Huber, & Anders, 2014; Varet, Brillet-Guéguen, Coppée, & Dillies, 2016), and the 8

filter condition was |log2(fold change)| ≥ 1, while the false discovery rate (FDR) < 0.05. DEGs were subjected to Gene Ontology (GO) analysis using the GOSeq R package (corrected pvalues < 0.05). 2.4 Quantitative real-time polymerase chain reaction analysis The method of total RNA isolation was described in 2.3 section. The expression levels of 8 anthocyanin biosynthesis genes in the phenylalanine pathway were measured by qRT-PCR. The first-strand cDNA was synthesized using HiscriptIIQ RT SuperMix for qPCR (Vazyme # R223-01). An IQ5 System (Bio-Rad, Hercules, CA, USA) was used to perform qRT-PCR, which used ChamQTM SYBR qPCR Master Mix (Vazyme # Q311). The primers are shown in Table S3, and VvActin was the internal reference gene. The relative expression was calculated using the 2-△△CT method. The reaction mixture contained 7.2 µL of ddH2O, 0.8 µL of primers (10 µmol/L), 2 µL of cDNA, and 10 µL of 2 × ChamQTM SYBR qPCR Master Mix. The reaction was performed using the following conditions: 90℃ for 30 s, followed by 40 cycles of 95℃ for 10 s, and then 55℃ for 30 s. Each sample was analyzed in 3 technical replicates. 2.5 Metabolite extraction and profiling The freeze-dried samples (grape berries stored at -80℃) were crushed at 30 Hz for 15 min using a mixer mill (MM 400, Retsch) with a zirconia head. Then, 100 mg of powder was weighed and extracted overnight at 4℃ with 1.0 mL of 70% aqueous methanol. After centrifugation at 10,000 g for 10 mins, the supernatant was removed and filtered (SCAA-104, 0.22 µm pore size; ANPEL Shanghai, China, http://www.anpel.com.cn/) before LC-ESIMS/MS analysis. The sample extracts were analyzed using an LC-ESI-MS/MS system (HPLC: Shim-pack UFLC Shimadzu CBM30A system, www.shimadzu.com.cn/; MS: Applied Biosystems 6500 Q TRAP, www.appliedbiosystems.com.cn/). The 3 biological replicates of each treatment group were analyzed independently. The samples were analyzed under the 9

following HPLC conditions: column, Waters ACQUITY UPLC HSS T3 C18 (1.8 µm, 2.1 mm × 100 mm); solvent system, water (0.04% acetic acid):acetonitrile (0.04% acetic acid); gradient program, 100:0 V/V at 0.0 min, 5:95 V/V at 11.0 min, 5:95 V/V at 12.0 min, 95:5 V/V at 12.1 min, and 95:5 V/V at 15.0 min; flow rate, 0.40 mL/min; temperature, 40℃; injection volume: 2 µL. The effluent for analysis was alternatively connected to an ESI-triple quadrupole-linear ion trap (Q TRAP)-MS. 2.6 Qualitative and quantitative analysis of metabolites The two RDI groups and CK group underwent metabolomics analysis, with three biological replicates in each group. The quantitative detection of metabolites were performed using multiple reaction monitoring (MRM) by the MetWare Biotechnology Co., Ltd. (Wuhan, China) (Yang et al., 2019). Linear ion trap (LIT) and triple quadrupole (QQQ) scans were acquired on an API 6500 Q TRAP LC/MS/MS system, which was equipped an ESI Turbo IonSpray interface controlled by Analyst 1.6.3 software (AB Sciex) and operating in the positive ion mode. The operational parameters of ESI were as follows: ion source, turbo spray; source temperature, 500℃; and ion spray voltage (IS), 5500 V. Additionally, the ion source gas I (GSI), gas II (GSII), curtain gas (CUR) were set at 55, 60, and 25.0 psi, respectively, and the collision gas (CAD) was high. Polypropylene glycol solutions of 10 and 100 µmol/L in the QQQ and LIT modes were used to perform the instrument tuning and mass calibration, respectively. The QQQ scans were acquired from the MRM experiments with the collision gas (nitrogen) set to 5 psi. DP and CE, which used individual MRM transitions, were performed for further DP and CE optimization. A specific group of MRM transitions was monitored for every period according to the metabolites eluted within this period. Metabolites were identified by comparing the m/z values, retention time, and fragmentation patterns with the standards in a database compiled by MetWare Biotechnology Co., Ltd. (Wuhan, China). The filtering conditions for significantly changed metabolites 10

(SCMs) were as follows: |log2(fold change)| ≥ 1, p-values < 0.05. To study metabolite varietyspecific accumulation, the principal component analysis (PCA) of SCMs was performed by R (www.r-project.org/). 2.7 HPLC analysis of monomeric anthocyanins The HPLC analysis of monomeric anthocyanins was performed to further support the conclusion of metabolomics analysis using the method of Ju et al. (2016). The highperformance liquid chromatography system (HPLC, Shimadzu, Japan), which was fitted with a C18 column (250 × 4.6 mm; Japan), was used for analysis. The conditions of analysis were as follows: column temperature, 30℃; phase A, water/acetonitrile/formic acid 80:10:7 V/V/V; and phase B, water/acetonitrile/formic acid 40:50:7 V/V/V. Samples were eluted using the method reported by Wang et al. with slight modifications (Wang et al., 2008). Briefly, the method used a 1.0 mL/min flow rate and from 0 to 30% B in 15 min; 50% B in 25 min; and 35 min, 0% B with an injection amount of 20 µL. The monomeric anthocyanins were identified by comparing the retention time and UV-VIS spectra from 200-600 nm to known standards. The detection and quantification were performed at 535 nm. Malvidin-3-O-glucoside (Sigma, St. Louis, USA) was used as internal standard. 2.8 Statistical analysis All data were analyzed using SPSS 17.0 software, and data were expressed as the mean ± standard deviation (SD) of triplicates. The differences between the means were analyzed using Duncan's multiple range test (Yang et al., 2020), and a p-value < 0.05 was considered to be significant. 3. Results and Discussion 3.1 Effects of RDI on the physicochemical indices in grape berries The hundred-grain weight of grapes under different RDI treatments were shown in Fig. 1A. From Fig. 1A, the RDI1 group with 30% ETc could slow the growth of the fruit weight 11

and stop the growth earlier than the CK group. Significant differences occurred between the groups at 14 WAF. The fruit weights of the RDI1 (105.19 g) and RDI2 (113.73 g) groups were significantly lower than those of the CK group (127.49 g) due to severe water shortage when the grapes were ripe, which dropped 17.49% and 10.79%, respectively. [Figure 1 about here] Fig. 1B shows the effect of RDI on the reducing sugar content of grapes in 2018. Under the RDI treatment, the reducing sugar content in grape fruit showed a higher content than in the CK group since 10 WAF, and reached a highest difference level in WAF. Meanwhile, the reducing sugar content in the RDI1 group was 42.4% higher than in the CK group, and that of the RDI2 group was higher than that of the CK group by 30.6%. After the grape fruit matured, the difference gradually decreased, but the reducing sugar content in the RDI groups was still higher than that in the CK group at maturity. The reducing sugar content in the RDI1 treatment group was 17.1% higher than that in the CK group, reaching 215.85 g/L; the reducing sugar content in the RDI2 group was 16.3% higher than that in the CK group, reaching 214.34 g/L, but there was no significant difference between the two treatment groups. This was in consistent with precious report, which was mainly due to the genes associated sugar unloading were significantly upregulated by RDI (Yang et al., 2020). Fig. 1C shows the change in the total acid content in the grapes from veraison to ripening. The total acid contents of grapes in the RDI groups were significantly lower than that in the CK group during veraison (especially during 10-12 WAF). The difference reached a maximum at 12 WAF, the RDI1 group was lower than the CK group by 34.4% and the RDI2 group was 33.3% lower than the CK group. The total acid content of the RDI1 group was slightly lower than that of the CK group, while that of the RDI2 group was slightly higher than that of the CK group, but there were no significant differences during ripening. Total acid mainly consisted of tartaric acid, malic acid and citric acid in grapes. The decrease of total acid content 12

in RDI groups during veraison was due to the decrease of these 3 kinds of organic acid content (Yang et al., 2020). The soluble solid content is related to the contents of various substances in the grape fruit. It can be seen that the degrees brix continue to increase during the ripening process (Fig. 1D), and those of the RDI groups increase faster. At 10 WAF, the soluble solid contents of the RDI groups were significantly higher than that of the CK group; the value of the RDI1 group was 26.6% higher than that of the CK group at maturity, and the value of the RDI2 group was 18.2% higher than that of the CK group. The soluble solid content mainly depends on the reducing sugar content of grapes when the fruit is ripe, and the changes are basically the same when compared with Fig. 1B. The pH of the juice gradually increased as the fruit ripened (Fig. 1E). The pH depends largely on the acid content of grapes (Li, Wang, Yuan, & Wang, 2007). As mentioned above the RDI treatments reduced the contents of organic acid, thus the pH raised. At 10 and 12 WAF, the pH of each group was different, and the pH of the RDI1 group was the highest, while that of CK group was the lowest. The total anthocyanin content (TAC) is one of the key indicators of this experiment. As seen from Fig. 1F, at 8 WAF, the TAC of the RDI groups and the CK group were basically the same. At 10-16 WAF, the TAC in the RDI groups was significantly higher than that in the CK group, and each group showed a slight increase after increasing at first. The TAC in the RDI groups increased rapidly after 8 WAF and reached a maximum at 12 WAF. The TAC of the CK group gradually increased during veraison and then reached a maximum at 14 WAF. The TAC in the RDI1 group was 28.6% higher than that in the CK group, and the content in the RDI2 group was 2.87% higher than that in the CK group at ripening. Therefore, RDI treatment not only increased the TAC of the fruit but also made veraison end earlier. The expression of some structural genes associated anthocyanin biosynthesis up-regulated by RDI treatment 13

resulted in the TAC content increasing (Ju et al., 2019). The reason of these phenomenon we assumed was that the vegetative growth and reproductive growth were affected by irrigation amount Water deficit would limit the vegetative growth and accelerate the process of reproduction, and induce the grapes ripe earlier (Ussahatanonta, Jackson, & Rowe, 1996). RDI treatments resulted in a lower berry weight, yield and titratable acidity with higher total soluble solid and total anthocyanin contents (Fang, Sun, Wan, Xi, Liu, & Zhang, 2013; Ju et al., 2018a, 2018b, 2019). Our data are consistent with previous studies, from which it can be seen that appropriate RDI treatment has the effect of improving Cabernet Sauvignon grape quality under the condition of slightly reducing the fruit field. This improvement in fruit quality is particularly important for wine grapes, which is directly related to the fruit economic value and the quality of the final wine to a certain extent. RDI treatment effectively reduces the amount of irrigation water, and it is well adapted to the arid and semiarid regions of northwestern China (Fang et al., 2013; Ju et al., 2018a, 2018b, 2019). Vine growth is largely influenced by the soil moisture content. As reported by Fang et al. (2013), the incidence of grape side shoots was reduced and shoot growth was inhibited under the RDI conditions. One of the main functions of RDI is to improve the berry quality by changing the root-to-shoot ratio of the vine (Kang, Shi, & Zhang, 2000), as it can retard vegetative growth as well as improve reproductive growth. This type of irrigation treatment can cause changes in the tree organs of the vine, such as the leaf size, leaf shape and boundary layer thickness, which may change the microclimate of the vine, thus causing changes in the temperature, illumination intensity and illumination time of grape clusters that directly or indirectly affect the biosynthesis and accumulation of anthocyanins. Previous studies have also shown that the light transmission of the canopy is likely to alter the biosynthesis and accumulation of anthocyanins in grape berries, which provides another possible explanation for the conclusion in this study (Haselgrove et al., 2000; Terry & Kurtural, 2011). 14

3.2 DEGs and transcriptome analysis of grapes Massive RNA deep-sequencing represents an alternative technological platform for the investigation of transcriptional regulation, which enables the precise elucidation of transcripts present within a particular sample. Based on the absolute transcript abundance, the gene expression can be calculated. Previous studies have been conducted to analyze the transcriptome at four developmental stages of grape berries (Vitis vinifera cv. Shirza) (Sweetman, Wong, Ford, & Drew, 2012). Based on those studies, transcriptome analysis of Cabernet Sauvignon berries under RDI was performed. From the analysis of Fig. 1F, the 8-12 WAF was the veraison which anthocyanins accumulated rapidly. Therefore, the grape berries at 10 WAF were selected randomly from each treatment group for transcriptomic analysis. Fig. 2A shows the correlation between the treatment groups and biological replicates, and the correlation is better when the value is closer to 1.00. Thus, this figure could directly reflect the significant difference between the different treatment groups, and the grouping is clear. Fig. 2B shows that the DEGs overlap between different combinations of RDI and CK groups. There were 3,991 DEGs between the RDI1 and CK groups, and there were 1,198 DEGs between the RDI2 and CK groups, which contain 551 identical genes. [Figure 2 about here] The volcano maps were drawn to intuitively represent the differential gene distribution between each RDI treatment group and the CK group. As shown in Fig. 2C and Fig. 2D, the green dots indicate the downregulated expressed genes (fold change, Log2FC≤0.5), the red dots indicate the upregulated expressed genes (Log2FC ≥ 2), and the black dots indicate the nondifferentially expressed genes (0.5 < Log2FC < 2). The abscissa indicates the differential expression multiple, and the ordinate indicates the level of difference in the gene significance. According to the results of transcriptomic analysis, there were 3,991 DEGs between RDI1 and 15

CK, of which 1,687 were upregulated and 2,304 were downregulated. There were 1,198 DEGs between RDI2 and CK, including 403 upregulated genes and 795 downregulated genes. The results of transcriptomic analysis indicated that the RDI affected the expression of a large number of genes of Cabernet Sauvignon during veraison, and the number of DEGs increased with the deepening of the water deficit. The most of anthocyanin synthesis genes witch located downstream of flavonoid biosynthesis

pathway

were

screened

(https://www.kegg.jp/kegg-bin/show_p

athway?map00941). Then, the expression levels were normalized, and two DEG cluster heat maps of “CK vs RDI1” and “CK vs RDI2” were produced with three biological replicates per treatment in each heat map (Fig. 2E and Fig. 2F). In the two figures, the difference between the RDI1 and CK group was more significant. At 10 WAF, the Vv4CL and VvFAOMT genes were significantly downregulated, and the VvUFGT, VvGDH, VvF3’H, VvF3’5’H, VvC4H, VvLDOX and VvF3H showed significant upregulated expression in RDI1. In Fig. 2F, the difference between each repeat of the RDI2 and CK group cannot be directly determined, and this still requires further analysis. [Figure 3 about here] The differential genes in this experiment were classified into three groups, molecular function, cellular component and biological process, by GO classification and plotted as shown Fig. 3A and 3B. In the biological process, a total of 1,391 (34.85%) DEGs were associated with the metabolic process between RDI1 and CK, and 415 (34.64%) DEGs were associated with the metabolic process between RDI2 and CK. It can be seen that different degrees of RDI will greatly affect the number of DEGs involved in the metabolic process in grape cells, but the proportion of DEGs involved in metabolism is similar to that of the total DEGs. 3.3 Expression of anthocyanin biosynthesis genes To confirm the effect of RDI on anthocyanin biosynthesis in the veraison of Cabernet 16

Sauvignon, further examination of the transcriptomics analysis results was needed. The RTPCR was performed on the relative expression levels of 8 key genes in the anthocyanin biosynthetic pathway: VvPAL, VvC4H, VvCHS, VvF3’5’H, VvF3’H, VvDFR, VvLDOX and VvUFGT (Fig. 4). The expressions of VvPAL in the two RDI groups were significantly higher than that in the CK group from 8 to 14 WAF, and the difference reached a maximum at 14 WAF. The difference relative transcript level were 6.43 in “CK vs RDI1” and 3.29 in “CK vs RDI2”, respectively. However, during ripening (16 WAF), the expression levels of this gene in the two RDI groups were significantly lower than that in the CK. The expression of VvC4H reached a maximum at the beginning of veraison (8 WAF), while the difference multiple of “CK vs RDI1” was 3.59 and that of “CK vs RDI2” was 4.71. The expression of VvC4H gradually decreased with the ripening of the fruit. At the ripening stage (16 WAF), the expressions of VvC4H in the RDI groups were lower than that in the CK group. The expression of VvF3’5’H showed a large upregulation under the severe RDI treatment (RDI1) at 8 WAF, and the difference multiple of “CK vs RDI1” was 23.14. The expression of another gene, VvUFGT, also showed a large upregulation under severe RDI treatment, and the difference multiple of “CK vs RDI1” reached 17.04. At 8 WAF, the expressions of VvLDOX in the two RDI groups were significantly lower than that in the CK group. Then, at 10 WAF, this gene was significantly upregulated in the RDI1 group, which was a feedback at the genetic level to the RDI treatment and still need further analysis for the mechanism. [Figure 4 about here] When the grapes suffered from a water deficit, the 8 key genes in the anthocyanin biosynthetic pathway showed different degrees of expression changes in different periods. VvPAL, VvC4H, VvCHS and VvDFR were upregulated during veraison but were downregulated during ripening. The expression of VvLDOX was downregulated at the beginning of veraison and then gradually increased until the fruit ripened. Different genes 17

respond differently to a water deficit, and the phenological periods of grapes with the response were different. With the difference in the degree of deficit, the same gene in the same period will also have distinct expression. Previous studies have shown that other substances in grape berries also have an effect on anthocyanin structural genes, as the anthocyanin content in berries is normally positively associated with the sugar content. The increase of glucose and fructose promotes the expression of VvDFR, and thus, the VvDFR gene in the anthocyanin pathway exhibited upregulated expression after RDI1 treatment. This may be due not only to the regulation of the VvDFR gene directly by the water deficit but also to the upregulation of genes and enzymes involved in the biosynthesis and accumulation of glucose and fructose under the effect of RDI, which regulate VvDFR expression. Zheng et al. (2009) also pointed out that glucose analogs such as 2-deoxyglucose and mannose can also induce the accumulation of anthocyanins. Vignault and Hayes showed that the sugar unloading protein synthesis gene VvHT1 was capable of transporting galactose, xylose, glucose and 3-glucoside, and VvHT2 and VvHT3 expressions had strong time specificity, especially, VvHT3 would be upregulated during veraison, which also confirms that changes in the carbohydrate metabolism pathway after RDI treatment can possibly cause changes in the anthocyanins (Hayes, Davies, & Dry, 2007; Vignault et al., 2005). In addition to the structural genes in the anthocyanin biosynthetic pathway involved in this study, as regulator genes, MYB family transcription factors are the most important transcription factors that have a great influence on anthocyanin biosynthesis (Fournier-Level, Lacombe, Cunff, Boursiquot, & This, 2010). Meanwhile, due to the mutation of their MYB gene, there was no anthocyanin accumulation detected in some white grape varieties (Walker, Lee, Bogs, McDavid, Thomas, & Robinson, 2007). The researchers studied the transcription factors VvMYB5a and VvMYB5b and found that they mainly regulate the flavonoid metabolic 18

pathways in the early phase of fruit growth, which directly affects the metabolism of various polyphenols in grapes including anthocyanins, flavanols and lignins (Deluc et al., 2006, 2008). Therefore, among the many factors that caused changes in the accumulation of metabolites in this study, changes in transcription factors at the expression level is one of the possible reasons, which is not covered in this article and requires further investigation as well as proof. 3.4 Differential metabolites of grapes are enriched in the anthocyanin biosynthetic pathways during veraison Previous studies have shown that RDI can lead to an increase in the contents of various anthocyanins in ripe wine grapes (Ju et al., 2019; Santesteban, Miranda, & Royo, 2011), but the mechanism and specific details of the upregulation of anthocyanins are still unclear. Therefore, a variety of monomeric anthocyanins, flavonoids and flavonols in the berries of Cabernet Sauvignon during mid-veraison (10 WAF) were detected, and metabolomics analysis was performed in this part of the experiment. [Figure 5 about here] From the principal component analysis shown in Fig. 5A, the distinguishing metabolite grouping of different sample groups proved the next step of metabolomics analysis. In all group comparisons, the contents of the 65 metabolites appeared different, and a total of 18 metabolites showed significant differences in each combination (Fig. 5B). In further analysis (Fig. 5C and 5D), the number of differential metabolites (number of dot), the significance (ordinate) and the difference multiple (abscissa) of the RDI1 and RDI2 groups compared with the CK group could be confirmed. RDI1 had 37 upregulated (Log2FC ≥ 2), 1 downregulated (Log2FC ≤ 0.5) and 104 unclear change (0.5 < Log2FC < 2) metabolites. RDI2 had 30 upregulated, 2 downregulated and 100 unclear change metabolites. In summary, the amount of irrigation is closely related to the content of anthocyanin-related metabolites. The number of upregulated metabolites increases as the water deficit increases. 19

Two cluster heat maps of 34 monomeric anthocyanins and flavonoids (Fig. 5E and 5F) were produced. Compared with the CK group, the RDI1 showed significant upregulation of the contents of most anthocyanins, and the contents of some anthocyanin precursors such as p-coumaric acid, dihydroquercetin and dihydromyricetin showed a significant downregulation in three replicates. In the comparison between the RDI2 and CK groups, the contents of the above three precursors still showed significant downregulation, and the contents of flavonoids such as rutin were similarly downregulated. Ollé et al. (2011) investigated the effect of postveraison water deficit on anthocyanin accumulation in Shiraz grapes. The p-coumaroylated derivatives and malvidin content increased significantly due to the post-veraison water deficit, which conclusion was similar to our investigation. This indicates that the contents of numerous anthocyanins and flavonoids in the anthocyanin biosynthetic pathway showed a significant change during RDI treatment, especially in the RDI1 group with the most severe water deficit. 3.5 Effect of RDI treatment on the monomeric anthocyanins of grape skins To more accurately verify the results of metabolomics, the contents of five main monomeric anthocyanins in grape skins during the beginning of veraison (8 WAF) to ripening (16 WAF) were determined. These five monomeric anthocyanins are cyanidin-3-O-glucoside (Cy), delphindin-3-O-glucoside (Dp), peonidin-3-O-glucoside (Pn), petunidin-3-O-glucoside (Pt) and malvidin-3-O-glucoside (Fig. S2). The content of Cy gradually increased with the ripening of grapes in each treatment group and had a lower level at 8 WAF. Subsequently, the Cy content increased rapidly in the two RDI groups, with values of 1.32 mg/L in the RDI1 group, 1.14 mg/L in the RDI2 group and 0.43 mg/L in the CK group at 10 WAF. The difference in the Cy content at 14 WAF was the smallest, and the Cy contents in the RDI1, RDI2 and CK groups at the time of grape ripening were 2.81 mg/g, 2.62 mg/g and 2.34 mg/g, respectively. The content of Dp was significantly different from that of Cy. At 8 WAF, the content was 20

similar in each group. At 10 WAF, the Dp contents of the RDI1 and RDI2 groups increased rapidly, while that of the CK group increased slightly, and the contents in three groups were 3.05 mg/g, 2.91 mg/g and 1.51 mg/g, respectively. The Dp content of the RDI2 group was the highest and that of the CK group was the lowest during ripening. The Pn content showed a tendency to decrease slightly after increasing at first in each group, and the difference between the groups was not significant. When the grapes were ripe, the Pn contents of the RDI1, RDI2 and CK groups were 1.90 mg/g, 2.01 mg/g and 2.17 mg/g, respectively. The change trends of the Pt contents were significantly different between the RDI groups and CK group. In the RDI groups, the Pt contents increased rapidly from 8-10 WAF and then remained substantially stable. In the CK group, the Pt content gradually increased with time but decreased at 14-16 WAF. The Pt contents in the three treatment groups at the time of ripening were 2.63 mg/g, 2.31 mg/g and 2.15 mg/g, respectively. Mv is the monomeric anthocyanin that has the largest proportion of total anthocyanins in grapes. Therefore, the change in the Mv content largely affects the change of the TAC in grapes. The My contents of the three treatment groups increased with fruit development. In the grapes at 10 WAF that underwent metabolomics analysis, the Mv content of the CK group was 3.03 mg/g. The Mv content of the RDI1 group was 6.22 mg/g, which was 205.28% that of the CK group. The Mv content of the RDI2 group was 5.70 mg/g, which was 188.12% that of the CK group. The My content increased slightly in the RDI1 and RDI2 groups and remained basically unchanged in the CK group during 12-16 WAF. When the grapes were ripe, the Mv contents of the three treatment groups were 8.68 mg/g, 8.09 mg/g and 5.71 mg/g, respectively, accounting for 45.54%, 44.22% and 38.03% of the non-acylated anthocyanin content. Mv has the highest proportion in the RDI1 group. In the detection and analysis of anthocyanins, it can be found that a variety of monomeric 21

anthocyanin contents decreased rapidly in the early stage of fruit ripening (14-16 WAF). This phenomenon may be caused by the activation of downstream metabolic reactions. For example, monomeric anthocyanins undergo acylation under the action of various acyltransferases to form acylated anthocyanins (Rinaldo et al., 2015), or it is likely that downstream reactions decompose and transport accumulated anthocyanins. In the study of Ju et al., RDI effectively increased the content of acylated anthocyanins (Ju et al., 2019). The different types of monomeric anthocyanins are related to different accumulation ratios under water deficit conditions. Most of the monomeric anthocyanins accumulated faster in the case of RDI treatment, and the time for the anthocyanin content to reach a maximum is increased. A small number of monomeric anthocyanins (such as Pn) were not sensitive to RDI. Therefore, the overall accumulation rate and trend are similar to those of the normal irrigation group. It can be found that the monomeric anthocyanin contents and the results of metabolomics analysis had significant correlation, and the results of metabolomics testing can be specifically explained by the changes in the contents of anthocyanins in the grapes at 10 WAF. Hence, the Cabernet Sauvignon had not only an increased anthocyanin content during veraison under RDI treatment but the anthocyanin content was also still significantly higher than that in the normal irrigation group during ripening. 3.6 Effects of RDI treatment on the anthocyanin biosynthetic pathway [Figure 6 about here] Combining transcriptomics with metabolomics data, we clearly see the different effects of different degrees of RDI treatment on the entire anthocyanin biosynthetic pathway (Fig. 6). Upstream of the pathway, the content of L-phenylalanine did not change significantly in the two RDI groups compared with the CK group, and the content of cinnamic acid produced by the VvPAL gene showed a significant upregulation. Subsequently, naringenin is generated under the action of VvC4H, Vv4CL and VvCHS, which showed significant upregulation in the 22

RDI1 group during this process. In addition, the content of naringenin was slightly upregulated in both RDI groups, and the RDI1 group experienced greater upregulation. After that, naringenin produced eriodictyol and dihydrotricetin under the action of VvF3’5’H and VvF3’H. The content of eriodictyol also increased to different degrees in the two RDI groups, and the RDI1 group experienced greater upregulation. The DHK, DHQ and DHM, which were downstream products of the three flavonoids naringenin, eriodictyol and dihydrotricetin, were different from those of other substances. DHK did not change significantly in the RDI1 group and increased slightly in the RDI2 group. The content of DHQ decreased slightly in both RDI groups, and the DHM content showed a significant downregulation, while the expression of VvF3H, which affects this process, was upregulated in the two RDI groups. The above three dihydroflavonols sequentially produced a variety of anthocyanins under the action of three genes, VvDFR, VvLDOX and VvUFGT. Among them, VvLDOX showed significant upregulation in the RDI1 group, and the VvUFGT gene showed upregulation in both RDI groups. Analysis of the metabolic pathway shown in Fig. 6 revealed that the monomeric anthocyanin contents of MV, Pt and Dp, which are downstream products of the delphinidin metabolic pathway, were significantly increased in both RDI groups. As Mv accounts for the largest proportion of the total anthocyanins compared with other monomeric anthocyanins, it is speculated that the large increase in the TAC was derived from the sharp increase in the Mv content under a water deficit. However, as the upstream precursor of Mv, Pt and Dp, the content of DHM showed a significant downward trend in both RDI groups, which is seemingly a contradictory result, and this may be due to the lower content of the upstream metabolite dihydrotricetin or decomposition of the downstream metabolite flavonols, and thus, these are specific reasons as to why further studies are required. 4. Conclusions 23

On the basis of our data, the effects of RDI on anthocyanin biosynthesis in Cabernet Sauvignon grape berries has been revealed; RDI increased the soluble solid content, juice pH, reducing sugar content, and total anthocyanin content, but it slightly decreased the hundredgrain weight. The total acid content decreased before ripening. The difference between the RDI1 group and CK group was the most significant. Transcriptomics and metabolomics analyses revealed that a large number of DEGs and SCMs were filtered in the RDI groups, and the number increased as the water deficit increased. In the grapes with a 30% ETc irrigation amount (RDI1), the related expression levels of key genes in the anthocyanin biosynthetic pathway, such as VvPAL, VvC4H, Vv4CL, VvCHS, VvF3’5’H, VvLDOX and VvUFGT, were upregulated. Then, the contents of metabolites such as cinnamic acid, naringenin chalcone, naringenin and eriodictyol increased significantly in this pathway. The contents of most monomeric anthocyanins increased and the proportions changed. The proportion of Mv increased as the amount of irrigation decreased. Our analyses revealed the mechanism by which RDI affects anthocyanin biosynthesis. The results of this study lay the groundwork for further studies on the regulation of anthocyanin accumulation by water. Such studies will ultimately benefit the promotion of RDI measures, and our data might be useful for improving the quality of wine grapes. ACKNOWLEDGMENTS This study was supported by the National key research and development program (2019YFD1002502), the National Nature Science Foundation Project (31801560), the Shaanxi Key Research & Development Program (2018NY-096), the class General Financial Grant from the China Postdoctoral Science Foundation (2017M623255, 2017M623257), the Xinjiang collaborative innovation project (2018E02050), and the Fundamental Research Funds for the Central Universities (2452017224, 2452017227). 24

Reference Allen, R., Pereira, L., Raes, D., & Smith, M. (1998). Crop evapotranspiration guidelines for computing crop water requirements (FAO irrigation and drainage paper no. 56). Rome: Food and Agriculture Organization of the United Nations. Allen, R. G., Smith, M., Pereira, L. S., Raes, D., & Wright, J. L. (2000). Revised FAO procedures for calculating evaportranspiration: irrigation and drainage paper No. 56 with testing in Idaho. 1-10. Boss, P. K., & Davies, C. (2009). Molecular biology of anthocyanin accumulation in grape berries. Grapevine Molecular Physiology & Biotechnology, Second Edition, 263-292. Cheng, G., He, Y. N., Yue, T. X., Wang, J., & Zhang, Z. W. (2014). Effects of climatic conditions and soil properties on Cabernet Sauvignon berry growth and anthocyanin profiles. Molecules, 19(9), 13683-13703. Cortell, J. M., Halbleib, M., Gallagher, A. V., Righetti, T. L., & Kennedy, J. A. (2005). Influence of vine vigor on grape (Vitis vinifera L. cv. Pinot Noir) and wine proanthocyanidins. Journal of Agricultural & Food Chemistry, 53(14), 5798-5808. Deluc, L., Barrieu, F., Marchive, C., Lauvergeat, V., Decendit, A., Richard, T., Carde, J. P., Mérillon, J. M., & Hamdi, S. (2006). Characterization of a grapevine R2R3-MYB transcription factor that regulates the phenylpropanoid pathway. Plant Physiology, 140(2), 499-511. Deluc, L., Bogs, J., Walker, A. R., Ferrier, T., Decendit, A., Merillon J. M., Robinson, S. P., & Barrieu, F. (2008). The transcription factor VvMYB5b contributes to the regulation of anthocyanin and proanthocyanidin biosynthesis in developing grape berries. Plant Physiology, 147(4), 2041-2053.

25

Downey, M. O., Harvey, J. S., & Robinson, S. P. (2004). The effect of bunch shading on berry development and flavonoid accumulation in shiraz grapes. Australian Journal of Grape & Wine Research, 10(1), 55-73. Edwards, E. J., & Clingeleffer, P. R. (2013). Interseasonal effects of regulated deficit irrigation on growth, yield, water use, berry composition and wine attributes of Cabernet Sauvignon grapevines. Australian Journal of Grape & Wine Research, 19(2), 261-276. Egea, G., Nortes, P. A., González-Real, M. M., Baille, A., & Domingo, R. (2010). Agronomic response and water productivity of almond trees under contrasted deficit irrigation regimes. Agricultural Water Management, 97(1), 171-181. Faci, J. M., Medina, E. T., Martínez-Cob, A., & Alonso, J. M. (2014). Fruit yield and quality response of a late season peach orchard to different irrigation regimes in a semi-arid environment. Agricultural Water Management, 143, 102-112. Fang, Y. L., Sun, W., Wan, L., Xi, Z. M., Liu, X., Zhang, & Z. W. (2013). Effects of regulated deficit irrigation (RDI) on wine grape growth and fruit quality. Scientia Agricultura Sinica, 46(13), 2730-2738. Fournier-Level, A., Lacombe, T., Cunff, L. L., Boursiquot, J. M., & This, P. (2010). Evolution of the VvMybA gene family, the major determinant of berry colour in cultivated grapevine (Vitis vinifera L.). Heredity, 104, 351-362. Greven, M. M., Bennett, J. S., & Neal, S. M. (2014). Influence of retained node number on sauvignon blanc grapevine vegetative growth and yield. Australian Journal of Grape & Wine Research, 20(2), 263-271. Haselgrove, L., Botting, D., van Heeswijck, R., HøJ, P. B., Dry, P. R., Ford, C., & Iland, P. G.

26

(2000). Canopy microclimate and berry composition: The effect of bunch exposure on the phenolic composition of Vitis vinifera L cv. Shiraz grape berries. Australian Journal of Grape & Wine Research, 6(2), 141-149. Hayes, M. A., Davies, C., & Dry, I. B. (2007). Isolation, functional characterization, and expression analysis of grapevine (Vitis vinifera L.) hexose transporters: differential roles in sink and source tissues. Journal of Experimental Botany, 58(8), 1985-1997. Ju, Y. L., Liu, M., Tu, T. Y., Zhao, X. F., Yue, X. F., Zhang, J. X., Fang, Y. L., & Meng, J. F. (2018a). Effect of regulated deficit irrigation on fatty acids and their derived volatiles in ‘Cabernet Sauvignon’ grapes and wines of Ningxia, China. Food Chemistry, 245, 667-675. Ju, Y. L., Liu, M., Zhao, H., Meng, J. F., & Fang, Y. L. (2016). Effect of exogenous abscisic acid and methyl jasmonate on anthocyanin composition, fatty acids, and volatile compounds of Cabernet Sauvignon (Vitis vinifera L.) grape berries. Molecules, 21(10), 1354. Ju, Y. L., Xu, G. Q., Yue, X. F., Zhao, X. F., Tu, T. Y., Zhang, J. X., & Fang, Y. L. (2018b). Effects of regulated deficit irrigation on amino acid profiles and their derived volatile compounds in Cabernet Sauvignon (Vitis vinifera L.) grapes and wines. Molecules, 23(8), 1983. Ju, Y. L., Yang, B. H., He, S., Tu, T. Y., Min, Z., Fang, Y. L., & Sun, X. Y. (2019). Anthocyanins accumulation and biosynthesis are modulated by regulated deficit irrigation in Cabernet Sauvignon (Vitis vinifera L.) grapes and wines. Plant Physiology & Biochemistry, 135, 469-479. Kaldenhoff, R., Ribas-carbo, M., Sans, J. F., Lovisolo, C., Heckwolf, M., & Uehlein, N. (2008). Aquaporins and plant water balance. Plant Cell & Environment, 31(5), 658-666. Kang, S., Shi, W., & Zhang, J. (2000). An improved water-use efficiency for maize grown

27

under regulated deficit irrigation. Field Crops Research, 67(3), 207-214. Kim, K., Langmead, B., & Salzberg, S. L. (2015). HISAT: a fast spliced aligner with low memory requirements. Nature Methods, 12 (4), 357-360. Li, H., Wang, H., Yuan, C., & Wang, S. (2007). Wine Technology. Beijing: Science Press. Liang, Z. C., Wu, B. H., Fan, P. G., Yang, C. X., Duan, W., Zheng, X. B., Liu, C. Y., & Li, S. H. (2008). Anthocyanin composition and content in grape berry skin in Vitis germplasm. Food Chemistry, 111(4), 837-844. Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15, 550. Ma, T., Sun, X., Zhao, J., You, Y., Lei, Y., Gao, G., & Zhan, J. (2017). Nutrient compositions and antioxidant capacity of Kiwifruit (Actinidia) and their relationship with flesh color and commercial value. Food Chemistry, 218, 294-304. Ma, T., Lan, T., Geng, T., Ju, Y., Cheng, G., Que, Z., Gao, G., Fang, Y., & Sun, X. (2019a). Nutritional properties and biological activities of kiwifruit (Actinidia) and kiwifruit products under simulated gastrointestinal in vitro digestion. Food & Nutrition Research, 63, 1674. Ma, T., Lan, T., Ju, Y., Cheng, G., Que, Z., Geng, T., Fang, Y., Sun, X. (2019b). Comparison on the nutritional properties and biological activities of kiwifruit (Actinidia) and their different forms products: towards making kiwifruit more nutritious and functional. Food & Function, 10, 1317-1329. Meng, J. F., Fang, Y. L., Gao, J. S., Qiao, L. L., Zhang, A., Guo, Z. J., Qin, M. Y., Huang, J. Z., H, Y., & Zhuang, X. F. (2012). Phenolics composition and antioxidant activity of wine produced from spine grape (Vitis davidii Foex) and cherokee rose (Rosa laevigata Michx.)

28

fruits from south China. Journal of Food Science, 77(1), C8-C14. OIV.

(2012).

International

code

of

oenological

practices.

Available

online:

http://www.oiv.int/oiv/info/enpratiquesoenologiques Accessed on 1 January. Oliveira, H., Perez-Gregório, R., de Freitas, V., Mateus, N., & Fernandes, I. (2019). Comparison of the in vitro gastrointestinal bioavailability of acylated and non-acylated  anthocyanins: Purple-fleshed sweet potato vs red wine. Food Chemistry, 276, 410-418. Pastenes, C., Villalobos, L., Ríos, N., Reyes, F., Turgeon, R., & Franck, N. (2014). Carbon partitioning to berries in water stressed grapevines: the role of active transport in leaves and fruits. Environmental & Experimental Botany, 107, 154-166. Rinaldo, A. R., Cavallini, E., Jia, Y., Moss, S. M. A., McDavid, D. A. J., Hooper, L. C., Robinson, S. P., Tornielli, G. B., Zenoni, S., Ford, C. M., Boss, P. K., & Walker, A. R. (2015). A grapevine anthocyanin acyltransferase, transcriptionally regulated by VvMYBA, can produce most acylated anthocyanins present in grape skins. Plant Physiology, 169(3), 1897-1916. Ristic, R., Downey, M. O, Iland, P. G., Bindon, K., Francis, I. L., Herderich, M., & Robinson, S. P. (2007). Exclusion of sunlight from shiraz grapes alters wine colour, tannin and sensory properties. Australian Journal of Grape & Wine Research, 13(2), 53-65. Rolland, F., Baena-Gonzalez, E., & Sheen, J. (2006). Sugar sensing and signaling in plants: conserved and novel mechanisms. Annual Review of Plant Biology, 57(1), 675-709. Romero, P., Pérez-Pérez, J. G., Del Amor, F. M., Martinez-Cutillas, A., Dodd, I. C., & Botía, P. (2014). Partial root zone drying exerts different physiological responses on field-grown grapevine (Vitis vinifera cv. Monastrell) in comparison to regulated deficit irrigation. Functional Plant Biology, 41(11), 1087-1106.

29

Santesteban, L. G., Miranda, C., & Royo, J. B. (2011). Regulated deficit irrigation effects on growth, yield, grape quality and individual anthocyanin composition in Vitis vinifera L. cv. ‘Tempranillo’. Agricultural Water Management, 98(7), 1171-1179. Sun, X., Cheng, X., Zhang, J., Ju, Y., Que, Z., Liao, X., Lao, F., Fang, Y., & Ma, T. (2020). Letting wine polyphenols functional: Estimation of wine polyphenols bioaccessibility under different drinking amount and drinking patterns. Food Research International, 127, 108704. Song, J., Shellie, K. C., Wang, H., & Qian, M. C. (2012). Influence of deficit irrigation and kaolin particle film on grape composition and volatile compounds in Merlot grape (Vitis vinifera L.). Food Chemistry, 134(2), 841-850. Speirs, J., Binney, A., Collins, M., Edwards, E., & Loveys, B. (2013). Expression of ABA synthesis and metabolism genes under different irrigation strategies and atmospheric VPDs is associated with stomatal conductance in grapevine (Vitis vinifera L. cv Cabernet Sauvignon). Journal of Experimental Botany, 64(7), 1907-1916. Sweetman, C., Wong, D. C. J., Ford, C. M., & Drew, D. P. (2012). Transcriptome analysis at four developmental stages of grape berry (Vitis vinifera cv. Shiraz) provides insights into regulated and coordinated gene expression. BMC Genomics, 13(1), 691. Teng, S., Keurentjes, J., Bentsink, L., Koornneef, M., & Smeekens, S. (2005). Sucrose-specific induction of anthocyanin biosynthesis in arabidopsis requires the MYB75/PAP1 gene. Plant Physiology, 139(4), 1840-1852. Terry, D. B., & Kurtural, S. K. (2011). Achieving vine balance of syrah with mechanical canopy management and regulated deficit irrigation. American Journal of Enology & Viticulture, 62(4), 426-437.

30

Varet, H., Brillet-Guéguen, L., Coppée, J. Y., & Dillies, M. A. (2016). SARTools: a DESeq2and EdgeR-Based R pipeline for comprehensive differential analysis of RNA-Seq data. PLoS One, 11 (6), e0157022. Yang, B., Yao, H., Zhang, J., Li, Y., Ju, Y., Zhao, X., Sun, X., Fang, Y. (2020). Effect of regulated deficit irrigation on the content of soluble sugars, organic acids and endogenous hormones in Cabernet Sauvignon in the Ningxia region of China. Food Chemistry, 312, 126020. Yang, M., Yang, J., Su, L., Sun, K., Li, D., Liu, Y., Wang, H., Chen, Z., & Guo, T. 2019. Metabolic profile analysis and

identification of

key metabolites during rice seed 

germination under low-temperature stress. Plant Science, 289, 110282. Zhang, C., Zhang, Y., Zhao, Z., Liu, W., Chen, Y., Yang, G., ... & Cao, Y. (2019a). The application of slightly acidic electrolyzed water in pea sprout production to ensure food safety, biological and nutritional quality of the sprout. Food Control, 104, 83-90. Zhang, M., Ye, J., Fang, P., Zhang, Z., Wang, C., & Wu, G. (2019b). Facile electrochemical preparation of NaOH nanorods on glassy carbon electrode for ultrasensitive and simultaneous sensing of hydroquinone, catechol and resorcinol. Electrochimica Acta, 2019, 317, 618627.Zheng, Y. J., Tian, L., Liu, H. T., Pan, Q. H., Zhan, J. C., & Huang, W. D. (2009). Sugars induce anthocyanin accumulation and flavanone 3-hydroxylase expression in grape berries. Plant Growth Regulation, 58(3), 251-260.

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Figure Captions Figure 1. Physicochemical indices of grape berries. (A) Hundred-grain weight of grape berries. (B) Contents of reducing sugar. (C) Contents of total acid. (D) Contents of soluble solids. (E) The pH values of grape juice. (F) Contents of total anthocyanins. Values presented are the means ± SE (n ≥ 3). Different letters indicate significant differences among treatments in the same period using Duncan’s test (p < 0.05). Figure 2. Preliminary analysis of transcriptomics data. (A) Correlation heat map of different treatment groups. (B) Venn diagram of DEGs. (C) Volcano plots of DEGs between CK and RDI1. (D) Volcano plots of DEGs between CK and RDI2. (E) Cluster heat map of DEGs between CK and RDI1. (F) Cluster heat map of DEGs between CK and RDI2. Figure 3. GO classification of DEGs. (A) GO functional classification of DEGs between CK and RDI1. (B) GO functional classification of DEGs between CK and RDI2. Red arrows show the DEGs associated with metabolic processes. Figure 4. Expressions of the genes VvPAL, VvC4H, VvCHS, VvF3’5’H, VvF3’H, VvDFR, VvLDOX and VvUFGT, which are associated with anthocyanin biosynthesis in grape skins. Values presented are the means ± SE (n ≥ 3). CK was set as a reference group in each period, and the gene expression level was recorded as 1. The ordinate value is the multiple of the gene expression amount of each treatment group relative to the gene expression amount of the CK group, and the scale is logarithmic scale.. Figure 5. Preliminary analysis of metabolomics data. (A) PCA score plot metabolite profiles from different treatment groups. (B) Venn diagram of SCMs. (C) Volcano plots of SCMs between CK and RDI1. (D) Volcano plots of SCMs between CK and RDI2. (E) Cluster heat

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map of SCMs between CK and RDI1. (F) Cluster heat map of SCMs between CK and RDI2. Figure 6. Effect of RDI on the anthocyanin biosynthetic pathway. The left block below each gene/metabolite is the log2(fold change) of this gene/metabolite between CK and RDI1; the right block below each gene/metabolite is the log2(fold change) of this gene/metabolite between CK and RDI2.

33

A

B

C

D

E

F

Figure 1

34

A

B

C

D

E

F

CK vs RDI1

CK vs RDI2

Figure 2

35

A

CK vs RDI1

B

CK vs RDI2

Figure 3

36

A

B

C

D

E

F

G

H

Figure 4

37

A

B

C

D

CK vs RDI1

E

CK vs RDI2

F

CK vs RDI2

CK vs RDI1

Figure 5

38

Figure 6

39

Table S1 Physical and chemical indicators of the soil Depths (cm) pH Organic matter (g/kg) Soil bulk density (kg/m3) Water content (%)

0-20 8.92±0.23 13.57±1.36 1.69±0.07 15.43±0.04

40

20-40 8.84±0.21 9.43±1.28 1.75±0.09 16.82±0.03

40-60 8.91±0.25 7.54±1.41 1.78±0.08 17.67±0.03

Table S2 Scheme of regulated deficit irrigation (Unit: m3/ha) Treatment s RDI1 RDI2 CK

Unearth Buddin Flowering Setting Growing g 200 200 210 210 228 300 310 370 400 410 450 600 600 810 900

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Veraiso n 200 290 800

Tota l 1248 2080 4160

Table S3 List of primers for real-time PCR Gene name

Primer

Sequence (5’-3’)

VvActin

F

CTTGCATCCCTCAGCACCTT

R

TCCTGTGGACAATGGATGGA

F

CAACCAAGATGTGAACTCCTT

R

TTCTCCTCCAAATGCCTC

F

GGCAAGCACAAAGAGCACAGAT

R

TTCTTCTGGATGTGAGGGTGGTT

F

GTCTGAAGGAAGAGAAACTGAGAG

R

CCAGGATAAACAACACGCAT

F

AAACCGCTCAGACCAAAACC

R

ACTAAGCCACAGGAAACTAA

F

CAACAAGAGCTGGACGCAGT

R

AGCCGTTGATCTCACAGCTC

F

GGCCAAATCAAACTACCAGA

R

GAAACCTGTAGATGGCAGGA

F

AGGGAAGGGAAAACAAGTAG

R

ACTCTTTGGGGATTGACTGG

F

GGGATGGTAATGGCTGTGG

R

ACATGGGTGGAGAGTGAGTT

VvPAL VvC4H VvCHS VvF3’5’H VvF3’H VvDFR VvLDOX VvUFGT

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Figure S1. The weather conditions at the time of experiment including precipitation, the maximum, minimum and average temperature

43

A

B

C

D

E

Figure S2. Contents of monomeric anthocyanins Cy, Dp, Pn, Pt and Mv in grape skins. Values presented are the means ± SE (n ≥ 3). Cy: cyanidin-3-O-glucoside, Dp: delphinidin-3-Oglucoside, Pn: peonidin-3-O-glucoside, Pt: petunidin-3-O-glucoside, Mv: malvidin-3-Oglucoside.

Author contributions This study was designed by XY Sun, and YL Fang. Collection and identification of field material were performed by S He, and BH Yang. Sample preparation and analysis were performed by BH Yang, S He, Y Liu, BC Liu, and YL Ju. Data analysis was conducted by BH Yang, Y Liu, DZ Kang and BC Liu. Authors BH Yang, S He, DZ Kang, and XY Sun wrote the paper. YL Fang modified the language. All the authors read and approved the final manuscript. 44

Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Highlights 

Effects of RDI on anthocyanin biosynthesis in wine grapes was investigated.



RDI1 treatment increased anthocyanin content most effectively.



Revealing the changes of genes and substances under RDI by Omics.



Mapping the effects of anthocyanin biosynthetic pathway under RDI.

45