Effects of Darkness On Fruit Ripening In Grape And Tomato By RNA-Seq

doi:10.21203/rs.3.rs-819604/v1

Light is an important external environment factor which influences all aspects of plant growth and development, including fruit ripening. Transcription regulation of light will provide insights into effect of light for fruit ripening. In this study, we treat grape and tomato fruit with dark or light, and by the RNA-seq method, compare transcriptional level between dark-treated and light-treated fruits. Additionally, we analyzed the metabolome of freshly cut fruit samples in two-treated conditions. In this study, transcriptomic and metabonomic analyses were used to evaluate the effects of shading on the ripening of different climacteric types of fruits (tomato and grape). we showed that shading treatment could inhibited fruit development by down-regulating factors related to fruit ripening-related growth and development. The differentially expressed genes (DEGs) from treated or non-treated samples with dark were mainly enriched in sugar metabolism and signal transduction, plant hormone biosynthesis and secondary metabolism. At the same time, we used metabonomics to detect different secondary metabolites in tomato and grape. Based on the above data, we established a possible model of shading treatment regulating fruit quality of tomato and grape. We found that the expression of DEGs in sugar metabolism and signal transduction, plant hormone biosynthesis and secondary metabolism differ between tomato and grape after shading treatment, which helps to clarify the possible mechanism of how the response to light in climacteric and non-climacteric fruit.

Plant Molecular Biology and Genetics

Plant Physiology and Morphology

Light

Fruit maturity

RNA-seq

Tomato

Grape

We established a possible model of shading treatment regulating fruit quality of tomato and grape.

Light is one of the important external environment factors affecting the growth and development of plants (Botton et al., 2008). Evidences indicated that light may regulate genes of coloration at transcriptionally level as well as post-translationally level to affect the accumulation of anthocyanin(Xu et al., 2018). Fruit quality assessments taken in pear showed that the ripeness of fruit is accompanied by an increase in soluble solids and a decrease in titratable acidity. And the increase of light penetration level will accelerate this process(Zhang et al., 2016).

Tomato (Solanum Lycopersicum L.) is widely grown around the world as edible fruits and commercial vegetables. Tomato is popular among consumers because the fruits are rich in vitamins, carbohydrates, lycopene and carotenoids (Watzl et al., 1999). Grape (Vitis vinifera) is a popular fruit with high economic value whose cultivation area ranks the second in the world. The fruits of grape are rich in nutrition which can be make to fruit juice, wine besides consumed as table grape (Hongyan et al., 2018). The various physiological and biochemical changes that occur during fruit development and ripening are a complex process. These changes include changes in exterior color and internal taste of the fruit, which are carried out in a manner coordinated with environmental and genetic regulation. Fruits are divided into climacteric and non-climacteric due to different development processes especially respiration and ethylene production (Anna et al., 2005, Giovannoni et al., 2001). Previous studies on the ripening mechanism of typical menopausal fruits, such as tomato, showed that ethylene synthesis and respiration rate increased along with fruit ripening (Giovannoni et al., 2001, Giovannoni and James, 2004, Lucille and Don).In addition, compared with climacteric fruits, the ripening mechanism of non-climacteric fruits remains unsystematic. As a non-climacteric fruit, previous studies have shown that abscisic acid is closely related to the ripening process of grapes, and some studies have pointed out that there are some similar physiological and biochemical changes during the ripening process of climacteric and non-climacteric fruits(Barry CS, 2007).

Transcriptomics and metabolomics can be used to identify the genes and metabolic pathways involved in plant’s responses to different environmental stresses (Pezet et al., 2010). As a novel NGS technique, RNA-seq is widely used to acquire transcriptomic profiling which can describe complex response pathways, interactions, physiological and biochemical changes in plants(Haider et al., 2017, G. et al., 2002). Metabolomics analyses part of all or most of the metabolites in the sample and measures the molecular weight of the entire set of metabolites based on their metabolites. Non-target analysis and identification of the entire metabolome within an organism or system could be performed using metabolomics under given conditions (Jaehoo et al., 2014) .

Previous studies mainly focused on the respiratory changes and maturation mechanisms of different climacteric plants, but few have studied their biosynthetic pathways under abiotic stress. In this study, transcriptome libraries of tomato and grape under two different treatments were constructed via RNA-SEQ. At the same time, metabolites in tomato and grape fruits were identified via UHPLC-QTOF-MS. Based on the above transcriptome and metabolome information, differences in related metabolites and corresponding gene changes in enzymes related to maturation mechanism were observed. Comprehensive analysis to understand the different light response mechanisms of climacteric and non-climacteric.

Effects of shading treatment on fruit quality

In the tomato fruit, Shading treatment inhibited coloration compared to the control, which was supported by carotene, lycopene and Xanthophyll contents (Fig. 1A, B C). However, Shading treatment increased the chlorophyll content (Fig. 1D) and the total acid content (Fig. 1H). The treatment also affected the fruit firmness which is reflected in the slowing of the fruit softening (Fig. 1G). All of the above indicated that shading treatment retarded the tomato fruit ripening process. Similar to tomato, shading treatment reduced the contents of anthocyanins (Fig. 2A) and UDP-glucose: flavonoid 3-O-glucosyltransferase (UFGT) (Fig. 2G), which resulted in suppressed coloring of grape fruits. At the same time, shading treatment also increased chlorophyll content (Fig. 2B) and the total acid (Fig. 2C).

Common differences were found in sugar metabolism at tomato and grape fruits, shading treatment increased the starch content compared to the control fruit. The difference of sucrose content in fruits was the result of the synergistic effect of various enzymes in sucrose metabolism. The contents of acid invertase (AI) (Fig. 1K, 2J), neutral invertase (NI) (Fig. 1L, 2K) and sucrose phosphate synthase (SPS) (Fig. 1I, 2H) decreased, while the content of sucrose synthase (SS) (Fig. 1J, 2K) increased. These changes inhibit the synthesis and transformation of sucrose (Fig. 1G), thus delaying the accumulation of fructose and glucose (Fig. 2E, F). In summary, shading delayed the ripening process of different fruit types, tomato and grape may respond to darkness stress through some similar pathways.

Transcriptome profiling in response to darkness

Transcriptome sequencing of tomato fruit (TW) and control group (TR), grape pulp (PulpD) and control group (PulpL), and grape skin (SkinD) and control group (SkinL) were performed after dark treatment. The three replicates for RNA-seq in TW group yielded 6.59, 6.66, and 5.98G clean reads after quality control and raw read filtering per sample and the TR group obtained 6.55, 6.19, 6.56 G clean reads, respectively. The Q30 of all samples were greater than 94%, and the lowest reads sequence is 67.85% which fits for comparison with reference genome. In addition, we performed transcriptional profiling of the pulp and skin of grapes from treatments described above, three replicates per library in four cDNA libraries were constructed. After removing impurities and linker sequence, approximately 6.4 G-7.2 G clean reads of these libraries were obtained. Most of the reads (> 93.5%) were highly matched with grape genome sequences indicating that the clean reads were good enough for subsequent analysis.

DEGS analysis

All of the treatments were divided into three comparison groups named TW vs TR, SkinD vs SkinL, PulpD vs PulpL. The construction of cluster analysis clearly showed the expression content of DEGs in different samples (Fig. 3A), and the quantitative relationship of DEGs in different control groups was statistically analyzed by histogram (Fig. 3B). In addition, we compared the relationship between the number of up-regulated and down-regulated gene DEGs in the treatment group and the control group by drawing volcanic maps (Fig. 3C).

The GO and KEGG analysis of DEGs

As the largest comprehensive database in the world, the Gene Ontology (GO) knowledge base is widely used for annotation analysis of gene or protein function. We used the Gene Ontology (GO) knowledge base to predict and analyze the function of gene expression in the dark processing group, and selected the most significant 30 notes for DEGS rich in biological processes, cellular components, and molecular functions (Fig. 4).

In the TW vs TR group, GO analysis indicated that Shading treatment affected multiple metabolic pathways including 10 cellular components GO terms,10 biological process terms, and 10 molecular function terms.

In the SkinD vs SkinL group, GO analysis indicated that shading treatment affected multiple metabolic pathways including 13 cellular components GO terms, with cytoplasm being the most enriched terms; 9 biological process terms, with organonitrogen compound biosynthetic process being the most enriched; and 9 molecular function terms, with transporter activity being the most enrich.

In the PulpD vs PulpL group, GO analysis indicated that Shading treatment affected multiple metabolic pathways including 10 cellular components GO terms, with membrane protein complex being the most enriched terms. Then, we used KEGG pathway data base to examine the DEGs-associated pathways, KEGG pathway enrichment analysis showed that shading treatment was involved in photosynthesis and the biosynthesis of secondary metabolites (Fig. 5). These terms are more important to fruit quality.

Metabolome analysis

In order to study the metabolic response of different climacteric plants to dark stress, the metabolites of the treatment and the control group were compared and analyzed. Between TW-TR groups, 538 metabolites were identified across broad chemical classes from the spectra after quality validation when 201 metabolites were significantly upregulated and 300 were significantly down-regulated. And between SkinD vs SkinL, 298 metabolites were identified across broad chemical classes from the spectra when 161 metabolites were significantly up-regulated and 137 were significantly down-regulated. In PulpD vs PulpL group, 180 metabolites were found, 106 of which were up-regulated and 74 down-regulated. We conducted principal component analysis (PCA) of the metabolic differences between samples within each group and the differences between samples within the group (Fig. 6). P-value is the symbol of the result of significance test and p-value < 0.05 was defined as differentially expressed metabolites. The biological repetition of the three groups (TW-TR, SkinD-SkinL and Pulp-Pulp) met the requirements when there were significant differences between the treatment and the control group. Meanwhile, it was found that the expression of metabolites was mostly down-regulated in tomato, while the expression was mostly up-regulated in grape. The effects of dark stress on fruits of different climacteric were different.

Correlation analysis between transcriptome and metabolome

The KEGG pathway enrichment of the metabolome and DEGs in different climacteric fruits were integrated to evaluate the complementary analysis of transcriptomic and metabolomic data (Fig. 7). The results showed that the metabolic pathways related to Photosynthesis, hormone signal transduction, Starch and sucrose metabolism were more abundant in different species. At the same time, there are abundant pathways related to fruit coloring, such as Carotenoid biosynthesis and flavonoid biosynthesis-related pathways.

Shading treatment affects chlorophyll metabolism pathway

A significant enrichment degree of commonality in all comparison combinations has been observed in “Porphyrin and chlorophyll metabolism” according to KEGG pathway enrichment results. When berries underwent shading treatment, a series of enzyme activities all reduced related to chlorophyll biosynthesis in the tomato and grape. such as delta-aminolevulinic acid dehydratase (HEMB), uroporphyrinogen-III synthase (HEMC), uroporphyrinogen decarboxylase (HEME), coproporphyrinogen-III oxidase 1 (HEMF), protoporphyrinogen oxidase (HEMY), ChlH (encoding magnesium-chelatase subunit H), ChlI (ending magnesium-chelatase subunit I), CHLD (encoding magnesium chelatase subunits D) and protochlorophyllide reductase (POR2) were highly inhibited, therefore affecting the biosynthesis of chlorophyll. Comparative transcriptome analysis of the two contrasting species allows us to identify some candidate genes involved in chlorophyll degradation for example senescence -inducible chloroplast stay-green protein (SGR1), encoding protein stay-green 1 gene and ending red chlorophyll catabolite reductase gene transcript are inhibited in tomato and grape respectively (Table S1). Chlorophyll biosynthesis is a complex regulatory process, which is not only affected by external environmental factors, but also the enzymes involved in chlorophyll biosynthesis are regulated by genes(Nagata et al., 2005). Shading treatment inhibited the expression of several chlorophyll biosynthesis genes and the differential expression of genes encoding chlorophyll degrading enzymes in the two contrasting species, revealed that tomato and grape berries experience similar physiological mechanisms and parallel programs of cytological change following abiotic stress. Finally, it reflects the increase of chlorophyll content. The influence of light intensity on chlorophyll content showed a distinct performance in various types of plants. Previous studies have pointed out that in dark conditions, in case to ensure the normal growth of plants and promote net photosynthesis, Lilium auratum would capture light energy by synthesizing large amounts of chlorophyll (Zhang et al., 2015). Evidence indicates similar regulatory mechanisms for chlorophyll within both ripening physiologies, suggesting common regulators of climacteric and non-climacteric ripening physiology.

Shading treatment affects Sugar metabolism and signal transduction

In TW vs TR, RMATS software was used to compare the results for AS classification and differential AS analysis. In total, 4,026 AS events were identified in the transcriptome datasets including 223 Mutually exclusive exon (MXE) events and 3,803 Skipped exon (SE) events. Among them, 2 MXE events and 8 SE events were significantly enriched. In the MXE event, a sugar transporter (SUT,Solyc08g048290.3) was found (Table S2). Data suggests that INT1-transported myo-inosito not only plays a crucial role in the regulation of cell elongation in a sucrose dependent manner, but also participates in the regulation of sucrose and other carbohydrate intermediates as a metabolic signal (Strobl et al., 2018). In Arabidopsis, SUT belongs to the monosaccharide transporter (MST) -like gene family. The MST(-like) family includes 53 genes with significant homology to known monosaccharide transporters (Buttner, 2007).

Sugar, as photosynthetic products, plays an important role in nutrition supplement and signal molecules throughout the life cycle of higher plants (Zhang et al., 2020a). MSTs are important sugar transporters that were functioned in carbohydrate flux for maintaining the balance between source and sink tissues(Zheng et al., 2014). The number and proportion of different subtypes of SUT were significantly different from those before shading treatment, and the expression of SUT was decreased. In view of that plant sugar transporters play an important regulatory role in the transport balance of sucrose which was one of the important photosynthetic products. We speculate that AS of SlSUT after dark treatment, inhibited the transport and accumulation of sugar, which affected the fruit quality.

As previously reported, the accumulation and transport of sugar in grape berries has been well understood. Carbohydrates produced during leaf photosynthesis are transported as sucrose to the phloem, where they will be transported to the berry cluster. In fruits ripeness and senescence course, a series of sugar transporters guide the transport of sugars through different organelles (Conde et al., 2006, Swanson and El-Shishiny). Following berries ripening, sugars accumulate in vacuoles in the form of glucose and fructose and the polysaccharides are broken down by enzymes. Then these sugars will be transported through different organelles in the direct of monosaccharide. The three encoding sucrose phosphate synthase (VIT_218s0089g00410, VIT_211s0118g00200, VIT_205s0029g01140) and the gene encoding sucrose phosphatase (VIT_208s0032g00840) were significantly down-regulated in shading fruits (Table S3). At the same time, a decrease in sucrose content was detected in the metabolites (Table S4). In grape berries, sucrose is either degraded by sucrose synthase into uridine 5 '-diphosphate (UDP) glucose and fructose or cleaved by invertase into glucose and fructose for subsequent metabolism and biosynthesis (Stitt, 1993, Koch and K., 1996).

Plant hormone biosynthesis

In climacteric fruits like tomato, ripening and senescence are generally controlled by ethylene. While in the ripening process of grape, a non-climacteric fruit, may be facilitated by the accumulation of ABA. However, numerous studies implicating ABA has a hand in in the ripening of climacteric fruits (Chernys and Zeevaart, 2000, Leclercq et al., 2002). The cleavage of 9-cisviolaxanthin to xanthoxin (C15) and C25-epoxy-apo-aldehyde is necessary for ABA biosynthesis, which is catalyzed by 9-cis-epoxycarotenoid dioxygenase (NCED). When grape was shading stressed, a rise in ABA biosynthesis via expression of NCED (VIT_219s0093g00550, VIT_210s0003g03750), and strong ABA degradation correlated with a higher decrease of abscisic acid 8'-hydroxylase 4 (Hyd1)(VIT_218s0001g10500). However, in tomato, it was observed that ABA biosynthesis and degradation correlated with up-regulation of NCED1 (solyc07g056570.1) and abscisic acid 8'-hydroxylase (CYP707A1) (Solyc08g005610.3, Solyc04g078900.3) separately. Furthermore, the metabolomics data showed that accumulation of ABA was repressed and induced respectively in tomato and grape processing group. During maturation, environmental factors such as dark stress accelerated the induced expression of these genes to different levels., under illumination deficit. This characteristic pattern of expression is shared with many Chlorophyll metabolism pathway genes. These observations regarding correlation of expression present a common regulatory mechanism in both climacteric (tomato) and the non-climacteric (grape) throughout the ripening process.

In the GA-biosynthesis pathway, the activity of GA20- oxidase is considered to be one of the main regulatory points. It has been proved in spinach, Arabidopsis and potato that the expression of GA 20-oxidase was regulated by photoperiod with significantly higher levels of GA 20-oxidase in long-compared with short-day conditions (Wu et al., 1996, Xu et al., 1995, Carrera et al., 1999). The GA biosynthetic key enzyme GA20ox1 in StSUT4-RNAi plants was reduced indicating that SUT4 can promote GA biosynthesis(Kuehn, 2011). Ethylene stimulates phytochrome-mediated shade avoidance responses to shade treatment by enhancing GA action (Pierik et al., 2004).

In higher plants, methionine is a biosynthetic precursor of ethylene, 1-aminocyclopropane-1-carboxylic Acid Synthases (ACS) process S-adenosine l-methionine (SAM) to 1-aminocypropane-1-carboxylic Acid (ACC), Finally, ACC is oxidized to produce ethylene. (Yang, 1979). The two most important steps in this biosynthesis process are the catalytic processes of ACS and ACO.(Yang and Hoffman, 2003). The transcripts encoding ACS6 (Solyc08g008087.1), ACS2 (Solyc01g095080.3), ACO5 (Solyc07g026650.3) and ACO4 (Solyc07g049550.3) were promoted under shading stress. At the same time, in grape, a gene encoding 1-aminocyclopane-1-carboxylate synthase (VIT_202s0025g00360) and ACO1 (VIT_200s2086g00010) was inhibited (Table S5).

Effects of light deficit on carotenoid metabolism in tomato berries

At the transcriptional level, change of genes that associated with the carotenoid biosynthesis were firstly observed. The prominent gene enriched in up-regulated treatment-responsive transcripts was Lycopene cyclase protein (Lcy) (Solyc12g008980.2). Suppression of LCYe increased enhanced the accumulation of β-carotene both in transgenic and sweet potato (Diretto et al., 2006, Kim et al., 2013). In the pericarp of SlLCYe-RNAi fruit, transcript level of SlPSY1 was elevated, indicating that there was a negative regulatory feedback loop (Wang et al., 2020). In addition, the unigene of Squalene/phytoene synthase (PSY) (Solyc03g031860.3) was up-regulated and flavin containing amine oxidoreductase (Solyc03g123760.3) known as 15-cis-phytoene desaturase (PDS) was down-regulated (Table S6). The results showed that the content of lycopene and total carotenoids was positively correlated with the expression of PSY and PDS during the ripening of tomato fruits (Fraser et al., 2002). At the same time, the increase of geranylgeranyl pyrophosphate (GGPP) which known as precursor of carotenoid content was detected in the metabolites.

The up-regulation of PSY increased the synthesis of phytoene, while the decrease of PDS was the rate-limiting step of lycopene biosynthesis. LCYe was a key regulatory step for lycopene cyclization to β-carotene. The downregulation of LCYe gene expression inhibited the biological process of lycopene conversion into beta-carotene, which directly affected the ripening and color transformation of tomato fruits.

Effects of light deficit on flavonoid metabolism in grape berries

The GO and KEGG analysis results indicated that DEGs involved in flavonoid biosynthesis-related pathway consist of anthocyanins and Flavone difference between SkinD and SkinL. Therefore, we further studied DEGs participate in flavonoid biosynthesis in detail and established a predicted flavonoid biosynthesis pathway (Fig. 8). Nine DEGs were identified in flavonoid biosynthesis pathway. Interestingly, most them were down-regulated in SkinD vs SkinL, except PAL (VIT_216s0039g01110). These down regulated genes include, structural genes 4CL (VIT_216s0039g02040), CHS (VIT_214s0068g00920, VIT_205s0136g00260), CHI (VIT_213s0067g03820, VIT_213s0067g02870), and F3'H (VIT_217s0000g07200, VIT_217s0000g07210), F3H (VIT_204s0023g03370); DFR (VIT_218s0001g12800) and LDOX (VIT_202s0025g04720). Simultaneously, two metabolites (Laricitrin, Syringetin) showed significant down-regulated expression differences between SkinD and SkinL (Table S4,7). In our study, flavonols content was positively correlated with the transcripts of genes involved in the flavonoid biosynthesis pathway and their corresponding enzymatic activities. The down-regulation of these key genes, including the downstream genes for anthocyanin synthesis (DFR, UFGT), affects proanthocyanidin biosynthesis (cyanidin, pelargonidin, delpinidin), which largely explains the low accumulation of anthocyanins in SkinD.

Shading treatment affects the pathway of α-linolenic acid metabolism in grape berries

Compared with the control group, lipoxygenase (LOXO; VIT_209s0002g01080 LOXA; VIT_206s0004g01510) was significantly upregulated in berries of Shading treatment group. Whereas, fatty acid hydroperoxide lyase (HPL1; VIT_212s0059g01060) were dramatically reduced in Shading treatment group. The expression levels of alcohol dehydrogenase (ADH; VIT_204s0044g01110, VIT_218s0001g15450) were significantly higher than the control group (Fig. 9, Table S8).

DEGs for RNA-seq results verifified by qRT-PCR analysis

To verify the accuracy and repeatability of RNA-Seq data in this study, we analyzed the expression levels of related genes in tomato and grape berries by qPCR after dark treatment.We selected 13 DEGS as qPCR genes, which are involved in different biological pathways. These include ‘flavonoid metabolism’, ‘carotenoid metabolism’, ‘Plant Hormone biosynthesis’, ‘Sugar metabolism’, ‘Chlorophyll metabolism’. According to the qPCR results, we found that the expression levels of most genes were similar to the transcriptome data results (Fig. 10).

The color of the tomato fruit is determined by the accumulation of carotenoids and the degradation of chlorophyll (Manoharan et al., 2017). During grape ripening, accumulation of anthocyanin pigments for berry color and total chlorophyll decrease was sharp and continuous (Giovanelli et al., 2007). In this study, light shading inhibited the degradation of chlorophyll in tomato and grape fruits. And light, as an important environmental factor for plant growth and development, was involved in the different coloration mechanisms of tomato and grape. The changes in pigment contents are different in response to light stress among various plants which points out that the further studies are required to determine the specific mechanism underlying these changes.

The transport, metabolism and storage of sugar in fruit affect the total sugar content in fruit(Katz et al., 2007). Sugar produced by photosynthesis, principally sucrose, is moved from source leaves to support growth of, and carbon storage by, non-photosynthetic tissues through sugar transport pathway. The first plant sucrose transporter SoSUT1 was functionally identified from spinach (Spinacea oleracea) (Riesmeier et al., 1992). And nine sucrose transporter genes (SUTs or SUCs) were described in Arabidopsis (Arabidopsis Genome, 2000). SUT1 is essential for phloem loading into sieve elements in solanaceous plants (Burkle and L., 1998). Tuber starch content and tuber yield were most likely regulated by SUT2 alleles (Laurence Barker, 2000).

In plants, ABA is mainly involved in sugar metabolism, fruit softening and color development during fruit development. Studies have shown that ABA is involved in the positive regulation of grape fruits, and the content of ABA increases with fruit development (Jia et al., 2016). In tomato, ABA content reached the highest level about one to two weeks after flowering, followed by a slow decline in ABA levels during subsequent ripening (Buta and Spaulding, 1994), ABA plays important roles in plant development and tolerance to abiotic stresses. The berries underwent shading treatment ripened very slow compared to non-treated berries and some genes related to ABA synthesis and degradation were activated to the increase fruit maturation period. Interestingly, the metabolomics data showed that the content of ABA in grape and tomato increased and decreased respectively. These findings add to our understanding of the molecular mechanisms of the shading-delayed maturing response in tomato and grape. In addition, typically, climacteric fruits produce significant levels of ethylene during ripening, while non-climacteric fruits have lower levels (Qian et al., 2016). Ming Zhou et al. reported that in non-climacteric watermelon fruits, some physiological activities during fruit ripening are regulated by ethylene, and ethylene production may play a positive role in flesh softening (Zhou et al., 2016). During the mature stage of grape fruit, endogenous levels of ethylene, ABA and BRs increased as ripening proceeded (Ziliotto et al., 2012). A small but significant increase in endogenous ethylene synthesis, which was consistent with findings in some other non-climacteric fruits (D\ufcring et al., 1978). The metabolic pathways of ethylene and ABA in tomato and grape responded to abiotic stress such as shading stress by different regulatory mechanisms (Jia et al., 2011, Karppinen et al., 2013, Koyama et al., 2010). These findings add to our understanding of the molecular mechanisms of the shading-delayed maturing response in tomato and grape. It is helpful to further reveal the mechanism of fruit development so that the physiological and biochemical effects of ethylene and ABA on fruit ripening and senescence could be explained.

Some flavonoid compounds such as anthocyanins, chlorophylls, and carotenoids are synthesized by branching pathways from flavonoids. According to the transcriptome analysis of tomato, the expression of PSY, 15 CIS phytoene desaturase (PDS) and LCYrelated genes in carotenoid biosynthesis pathway jointly regulate tomato color. In addition, comparative transcriptome analysis of two contrasting grape. The transcripts of VvNCED which act as catalyticase of ABA biosynthesis were suppressed dramatically during shading grape development. Sugar can act as a carbon source as well as a signal molecule mediating the transcription of genes involved in the early steps of the anthocyanin biosynthetic pathway (CHS, CHI, F3H, F3’ H and FLS) that leads to the production of colorless dihydroflavonol compounds. Meanwhile, the transcription of downstream genes (DFR, UFGT) involved in anthocyanin synthesis is also regulated by sugar signals and hormones to affect anthocyanin production and color pigmentation in fruits.

Volatile organic compounds (VOCs) are the main determinants of wine flavor and organoleptic in grape berries (L. et al., 2016). Fatty acid metabolism pathway is one of the metabolic pathways related to VOCs synthesis in plants. Linear fatty alcohols, aldehydes and ketones are the main aromatic compounds or conjugated compounds in fruits, which are synthesized by fatty acids through a series of metabolic pathways(Lei et al., 2018). The main precursors to fatty acid metabolism are linolenic acid and linoleic acid in fatty acids. The regulation of aroma synthesis during fatty acid metabolism is regulated by LOX and ADH gene families (Mohamed et al., 2013). Studies showed that under different shade treatments, light affected the transcription level of the genes involved in volatile organic compounds synthesis, and thus had an impact on the species and content of VOC in berries (Friedel et al., 2016). Studies have shown that the LOX gene family actively participates in the synthesis of VOCs in the fatty acid metabolic pathway (Ma et al., 2020). HPL genes are involved in the regulation of precursors of fatty acid metabolism, including linoleic and linolenic acids (Granell and Rambla, 2013). After shading treatment, the expression of HPL1 (VIT_12s0059g01060) was inhibited, which may lead to the decrease of alcohol and ester contents in grape fruits. The transcriptional expression of ADHs genes can promote the transformation of aldehydes in the process of fatty acid metabolism, which has been proved in apple. The upregulation of ADH (VIT_204s0044g01110, VIT_218s0001g15450) could promote the synthesis of alcohols. In addition, the upregulation of LOXO and ADH could promote the accumulation of 2-heptanol, trans-2-hexenal, and cis-7-decenal in berries under complete shading conditions (Ma et al., 2020).

The shading treatment of tomato and grape activated the light-regulated feedback mechanism and affected the metabolism of chlorophyll. The sugar transporter SUT is linked to a phytochromes (Phys) dependent signal, Photochromes are not hormones, but dimer photoreceptors. phytochrome play an important role in the whole process of plant growth and development. There is a complex interaction between the phytochrome system and the hormone metabolism system, endogenous circadian rhythm and systemic stomatal responses (Devireddy et al., 2020). When plants are subjected to light stress, phytochrome induce transcription changes of genes by absorbing far-red and red light. In tomato, on the one hand, the inhibition of sugar transport in sources leaves leads to the decrease of sugar content in non-photosynthetic tissues. On the other hand, the decrease of ABA content resulted in the inhibition of fruit growth and fruit size through the interaction with GA signal. At the same time, ABA regulated the carotenoid content in fruit. The levels of two key enzymes involved in carotenoid biosynthesis, PSY1 and PDS, also rely on ethylene. Therefore, the lycopene biosynthesis pathway was first inhibited. The increased expression of Lcy could not make up for the lack of carotenoid synthesis materials, thus impeding the color turning of fruits. In grape, Phys was act as a photoreceptor that is not directly involved in photosynthesis or photorespiration, but was involved in regulating light-induced transport and accumulation of sucrose. All of the above were reflected in the decrease of glucose and fructose content after shading treatment. By activating SUT connecting Phys dependent and phytohormone signaling pathway, fruit ripening and color turning were delayed after shading treatment as well as the reduced of fruit size, thus affecting fruit yield and quality.

Fruit ripening is a complex genetic programmed involving physiological and biochemical responses. The effect of light conditions on grape and tomato fruit maturity, quality and physiology was investigated in this study. Light has its greatest impact on pigmentation, the regulation of pigmentation during ripening is due to ripening-related and phytohormone-inducible gene expression in tomato and grape. Our study demonstrated that light and phytohormones have some crosstalk mechanisms regulating gene transcription levels in fruit development. And a complex network of more than one phytohormones especially ABA and ethylene is involved in controlling all aspects of fruit ripening. After shading, different hormone levels on grape and tomato suggested the different molecular basis and ripening regulatory networks of climacteric and non-climacteric ripening physiology. The shading treatment also activated the light-regulated feedback mechanism of tomato and grape to affect the yield and quality of fruit. Through comprehensive analysis of physiological data, transcriptome and metabolome, the signal transduction, material metabolism and ripening regulatory networks of fruit ripening under light stress were sorted out. Then, we established a possible model of shading treatment regulating fruit quality of tomato and grape (Fig. 11). Greater impact is likely to result following more complete view into common regulatory mechanisms among climacteric and non-climacteric ripening. Tantalizing observations regarding the role of light in fruit ripening may lead to opportunities for addressing problems in fruit production and quality. Further studies will shed light on how the response to light that mediated through some key regulator in climacteric and non-climacteric fruit.

Plant material

The grapevine fruits of cultivar ‘Kyoho’ (Vitis labrusca L. × V. vinifera) and the tomato plants (Lycopersicon esculentum cv. Ailsa Craig) of cultivar ‘Lichun’ were collected from the Baima Experiment Field of Nanjing Agricultural University (located at 31 ^oN Lat. and 119 ^oE Long.) Nanjing, China. The grape fruits of growth for one week before ripe were wrapped of black bags for dark treatment. Similarly, in the BIG (big immature green, 29 days after flowering) stage, the tomato fruit was wrapped using black bags. The fruits of light- and dark-grown were collected until the fruits under light grew to mature stage with a completely red coloration. The receptacles (pulp) were cut into small sections, and then stored at –80 °C after immediately frozen in liquid nitrogen. Fifteen uniformly sized fruits were sampled for one replicate.

Determination of soluble sugar, organic acid, anthocyanins

On the basis of the method described by Ma et al. (Ma et al., 2015) with minor changes, the contents of soluble sugar and organic acid were measured by the high-performance liquid chromatography (HPLC). The samples of grape and tomato flesh from each replicate were ground into powder in liquid nitrogen. 5 grams of power was extracted with 25 mL redistilled water, then the residue was washed with 80% methanol twice after ultrasonically extract and centrifugate to collected the mixed supernatant for freeze-dried using Freezing Drier (Labconco FreeZone 4.5L). The samples of soluble sugar and organic acid were dissolved with distilled water and filtered with 0.45 μm Millipore membrane filters before testing.

The separation of soluble sugar was performed by a Sugar Pak TM I column (300 mm × 6.5 mm) (Waters, USA). The column temperature was 80 ℃ with the injection volume of 20 µL and the elution solvent was redistilled water, whose flow rate was 0.4 mL/min(Ma et al., 2015). According to the method described by Liu et al.(Liu et al., 2013), The separation of organic acid was performed by an IC PAK TM ION Exclusion column (300 mm × 7.8 mm) (Waters, USA), whose temperature was set at 40 °C. And the mobile phase was 0.01 mM sulfuric acid in redistilled water, whose flow rate was 0.5 mL/min. Soluble sugar and organic acid were expressed as mg/g fw. The measurement of anthocyanins were described as by Francis(Fuleki and Francis, 1968). The whole process was repeated three times.

RNA-seq

Transcriptome sequencing

After grinding into powder in liquid nitrogen, total RNA was extracted from each pulp sample using Hexadecyl trimethyl ammonium Bromide (CTAB) (Liao et al., 2004).

Nanodrop™ 2000 spectrophotometer (Thermo Fisher Scientific, USA) was used to detected the RNA purity and integrity within Agilent 2100 (Agilent Technologies, CA, USA). Further mRNA purification and cDNA library construction were performed with the Illumina HiSeqTM 2500 (Novogene Bioinformatics Technology Co., Ltd., Beijing, China). Three biological replicates from each treatment were used for RNA-seq.

Differentially expressed genes (DEGs) analysis

HISAT (Version: v2.1.0) was used to filter and align the reads. Then the number of reads mapped to each gene were calculated by HTSeqv0.9.1 (Fowler and Thomashow, 2002). According to the length and reads count mapped to a gene, RSEM (Version: v1.2.8) was used to calculate the number of fragments per kilobase length (FPKM) of each gene. We used DESeq R package (1.18.0) for DEGs analysis (Li and Dewey, 2011). And the statistical tests were revised for multiple testing with the Benjamina-Hochberg false discovery rate (FDR < 0.05) (Benjamini and Hochberg, 1995). The standard of statistically significant expression of genes was within a fold change ≥ 2 and an adjusted P-value <0.05.

Enrichment analysis

We analyzed GO enrichment through GOseq R Package to obtain more detailed information (Young et al., 2010). After screening the differential genes according to the purpose of the experiment, GO terms with corrected p-value less than 0.05 were considered significantly enriched by differential expressed genes.

KEGG (https://www.genome.jp/kegg/) was a database resource to identify the most important biochemical metabolic pathways and signal transduction pathways involved in differentially expressed genes through pathway significant enrichment. Statistical enrichment of DEG were found in the KEGG pathway after been tested by KOBAS software.

Metabolite extraction and metabonomic profile

UPLC-MS/MS analysis

Freeze-dried tomato and grape fruits were ground into powder, the extracts were filtered and metabolomic analyzed through UPLC (Novogene Bioinformatics Technology Co., Ltd., Beijing, China). According to the method described by Zhang et al (Zhang et al., 2020b), the chromatographic column was a Hyperil Gold (100 × 2.1 mm, 1.9 μm) and the flow rate was 0.2 mL/min. 0.1% FA dissolved in water and methanol were both chosen as the eluents in positive polarity mode. While in negative mode, 5 mM ammonium acetate (pH 9.0) and methanol were chosen as the eluents. The solvent gradient was set as follows: 2% methanol, 1.5 min; 2–100% methanol, 12.0 min; 100% methanol, 14.0 min; 100–2% methanol, 14.1 min; 2% methanol, 16 min. Polarity was in positive or negative modes, respectively.

Data analysis

We used Compound Finder 3.0 (CD 3.0, Thermo Fisher) to process the raw data files. Data of total spectral intensity normalized by the peak intensity was used to predict molecular formulas based on addition ions,fragment ions and molecular ion peaks. The mzCloud (https://www.mzcloud.org/) and ChemSpider (http://www.chemspider.com/) databases were used for accurate qualitative and relative quantitative results. Metabolites whose variable importance in projection (VIP) was ≥1 with p less than 0.05 for the model variables were defined as differentially accumulated metabolites.

Validation of RNA–Seq data by qRT-PCR

To validate the RNA-seq data, we examined the expressions of 13 candidate genes by qRT-PCR. The cDNA was synthesized using the Hifair^® Ⅱ 1st Strand cDNA Synthesis SuperMix for qPCR (11123ES60, YEASEN, China). The analysis of qRT-PCR was carried out using Hieff ^® qPCR SYBR Green Master Mix (11202ES08, YEASEN, China). The qRT-PCR cycle parameters were set at 95 ℃ for 2 min, 95 ℃ for 10 s, and annealing temperature at 60 ℃ for 40 s, which comprised a total of 40 cycles. Then the 2⁻^△△^CT method was used to calculate the relative induction ratios of treated samples compared with controls (Livak and Schmittgen, 2001). Three biological replications were used and three measurements were performed on each replicate.

ABA	Abscisic acid
ACC	1-aminocyclopropane-1-carboxylic acid
ADH	alcohol dehydrogenase
AI	acid invertase
AS	Alternative splicing
C15	cleavage of 9-cisviolaxanthin to xanthoxin
CHI	Chalcone isomerase
CHLD	encoding magnesium chelatase subunits D
ChlH	encoding magnesium-chelatase subunit H
ChlI	ending magnesium-chelatase subunit I
CHS	Chalcone synthase
CYP707A1	abscisic acid 8'-hydroxylas
DEGs	Differentially expressed genes
DFR	Dihydroflavonol 4-reductase
ETH	Ethylene
F3H	Flavanone 3-hydroxylase
FDR	False discovery rate
FLS	Flavonol synthase
FPKM	Fragments Per Kilobase of transcript per Million mapped reads
GA	Gibberellin
GC-MS	Gas chromatography-mass spectrometry
GGPP	geranylgeranyl pyrophosphate
GO	Gene Ontology
HEMB	delta-aminolevulinic acid dehydratase
HEMC	uroporphyrinogen-III synthase
HEME	uroporphyrinogen decarboxylase
HEMF	coproporphyrinogen-III oxidase 1
HEMY	protoporphyrinogen oxidase
HISAT	Hierarchical Indexing for Spliced Alignment of Transcripts
HPLC	High-performance liquid chromatographic
HPL1	fatty acid hydroperoxide lyase
Hyd1	abscisic acid 8'-hydroxylase 4
KEGG	Kyoto Encyclopedia of Genes and Genomes
Lcy	Lycopene cyclase protein
LDOX	leucoanthocyanidin dioxygenas
LOXO	lipoxygenase
MST	monosaccharide transporter
MXE	Mutually exclusive exon
NCBI	National center for biotechnology information
NCED	9-cis-epoxycarotenoid dioxygenase
NI	neutral invertase
PCA	Principal Component Analysis
PDS	15 CIS phytoene desaturase
Phys	phytochromes
POR2	protochlorophyllide reductase
PSY	phytoene synthase
QC	Quality Control
RABT	Reference Annotation Based Transcript
SAM	S-adenosyl-L-methionine
SD	standard deviations
SE	Skipped exon
SGR1	senescence -inducible chloroplast stay-green protein
SPS	sucrose phosphate synthase
SS	sucrose synthase
SUT	sugar transporter
UDP	uridine 5 '- diphosphate
UFGT	UDP-glucose: flavonoid 3-O-glucosyltransfersae
VOCs	Volatile organic compounds

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and All studies are based on these raw data [Supplementary Tables S1-S8]. Any reasonable requests are available from the corresponding authors ([email protected] and [email protected]).

Competing Interest

The authors declare no competing financial interests.

Funding

This work was supported by the national key research and development program (2019YFD1000100), the Natural Science Foundation of Jiangsu Province (BK20201176), the Natural science project of colleges and universities in Jiangsu Province (20KJD210001), Joint innovation project (CXFZ202016), National Natural Science Foundation of China (31872047) and the Fundamental Research Funds for the Central Universities (KYXJ202003). The funding bodies provided the financial support to this research, including experimental design and implementation, sampling and data analysis. No funder played the role in data collection and analysis and writing the manuscript.

Authors’ contributions

YWB conducted data analysis and drafted the manuscript. WMT treated the samples, PQQ and YK performed the research, LSY helped to revise the manuscript. GLB and ZT helped to draft the manuscript. JHF and FJG designed and coordinated this study and revised the manuscript. All authors have read and approved the manuscript.

Acknowledgements

We would like to express our gratitude to Central Laboratory of College of Horticulture, Nanjing Agricultural University.

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No competing interests reported.

TableS1.docx
Table S1-1 Key genes related to chlorophyll metabolism pathway in tomato Table S1-2 Key genes related to chlorophyll metabolism pathway in grape
TableS2.xlsx
Table S2 TW vs TR AS significant
TableS3.docx
Table S3 Key genes related to Sugar metabolism pathway in grape
TableS4.xlsx
Table S4 The annotation and quantitation results of metabolites.
TableS5.docx
Table S5-1 Key genes related to Plant hormone biosynthesis pathway in tomato Table S5-2 Key genes related to Plant hormone biosynthesis pathway in grape
TableS6.docx
Table S6 Key genes related to carotenoid metabolism pathway in tomato
TableS7.docx
Table S7 Key genes related to flavonoid metabolism in grape

Effects of Darkness On Fruit Ripening In Grape And Tomato By RNA-Seq

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Abstract

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Background

Results

Discussion

Conclusion

Methods

Abbreviations

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Supplementary Files

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