Effect of Low-Light Stress on Sugar and Acid Accumulation during Fruit Development and Ripening of Sweet Cherry

: In the production process of sweet cherry, there are unreasonable planting densities and tree shape selections. With increasing tree age, the crown of the tree continues to expand and the tree body is prone to canopy closure, which leads to the inability to efﬁciently use space and light energy. Low-light has become a major limiting factor in the quality of sweet cherry. Therefore, we analyzed the changes of various physiological indicators and the transcriptome of ‘Hongdeng’ sweet cherry under shading treatment in this study to investigate the effects of low-light stress on the photosynthetic characteristics of sweet cherry leaves and fruit physiology and biochemistry. The results showed that shading signiﬁcantly reduces the light capture capacity of leaves, damages the photosystem, reduces carbon assimilation capacity, and consumes the majority of the captured light energy as photochemical energy, thereby restricting the growth and development of leaves and reducing the accumulation of nutrients in fruits. Shading signiﬁcantly reduced fruit weight, sugar content, and vitamin C content at maturity and signiﬁcantly increased acid content. Transcriptomic data demonstrated that low-light stress produces a large number of differential genes related to carbon metabolism, organic acid metabolism, and stress resistance, thereby suggesting that low-light stress may affect the expression of these related genes and inclusions in the fruit. The results of this study will provide theoretical and technical support for the physiological response mechanism of low-light tolerance in sweet cherry, the selection and breeding of low-light tolerant sweet cherry varieties, and the cultivation of sweet cherry in facilities.


Introduction
Sweet cherry (Prunus avium L.) is a plant of the family Rosaceae and genus Prunus [1]. Sweet cherry is a significant economic fruit tree, indigenous to Europe and commonly grown in China, that presents a double S-shaped growth curve. Its development process based on developmental characteristics is divided into three main stages. When the fruit is mostly green, the first stage is dependent on cell division and elongation. The endocarp hardening stage, which results in the formation of the kernel and fruit color, is the second step. Finally, the third stage is the exponential growth period caused by cell expansion, during which drastic physiological and biochemical changes in sugar, organic acids, and color occur [2]. Sweet cherries are favored by consumers because of their early ripening, delicious taste, and strong antioxidant properties [3].
Fruit quality, which is primarily divided into internal and external qualities, plays a significant role in deciding the fruit's nutritional and commercial worth. Sweet cherries

Plant Materials and Sampling
'Hong deng' sweet cherry, used as the test material in this study, was obtained from the sweet cherry test site in Hanyuan County, Ya'an City, Sichuan Province. Six sweet cherry trees aged 10 years with the same growth conditions and growth period were randomly divided into two groups with three trees in each group. After flowering, the top of the whole tree was covered with a sunshade net. Treatment group A was shaded with a white insulated shade net (shading rate 30% ± 5%) (Meiryo, Hyogo, Japan) and the other group was left untreated and was regarded as the control (CK). Sampling started on 7 April 2021 (5 days after flowering) and was performed every 3 days after harvest by picking 20 fruits from each treatment group (60 fruits total per treatment). Fruits were divided into three stages (expansion, color change, and ripening) according to their development and color change ( Figure 1). The fruits were brought back to the laboratory immediately after sample collection for imaging and measurement of individual fruit weight and hardness. In order to prepare samples for later tests, they were quickly and uniformly cut into slices, frozen in liquid nitrogen, and kept in a refrigerator at 80 • C. and color change ( Figure 1). The fruits were brought back to the laboratory immediately after sample collection for imaging and measurement of individual fruit weight and hardness. In order to prepare samples for later tests, they were quickly and uniformly cut into slices, frozen in liquid nitrogen, and kept in a refrigerator at 80 °C. (CK indicates no shading (Control) and A indicates 30% Shading, as below). S1 means 5 days after flowering, S2 means 9 days after flowering, S3 means 13 days after flowering, S4 means 17 days after flowering, S5 means 21 days after flowering, S6 means 25 days after flowering, S7 means 29 days after flowering, S8 means 33 days after flowering, S9 means 37 days after flowering , S10 means 41 days after flowers, S11 means 45 days after flowers, S12 means 49 days after flowers.

Determination of Photosynthetic Parameters
The relative chlorophyll content was determined using a CCM-200 chlorophyll meter (OPTI-sciences, Boston, MA, USA). Gas exchange parameters, light response curves, and chlorophyll fluorescence parameters were determined using a Li-6800 portable photosynthesizer (LI-COR, Lincoln, NE, USA). The photosynthesis-light response curve [16] was fitted with the corrected right-angle hyperbola model and the apparent quantum efficiency (AQY), light compensation point (LCP), light saturation point (LSP), maximum net photosynthetic rate (Pn(max)), and dark respiration rate (Rd) were obtained.
The four bearing branch leaves of each tree's outer crown and inner circumference were randomly selected from east, south, west, and north directions. The Li-6800 portable photosynthometer was used to determine the net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular carbon dioxide concentration (Ci) during mornings of fine weather in the S9 (37 days after flowering) period. Two treatments (A and CK) were set up in this experiment, and three trees were selected for each treatment.
Chlorophyll fluorescence parameters were set for each parameter and leaf selection as above, and four leaves were measured per treatment. The leaves to be tested were wrapped with tin foil before measurement and were dark-adapted overnight. The initial and maximum fluorescence values were measured on the second day. The activation light was set according to the ambient light intensity of the shade treatment and light activation was performed for more than 50 min. The steady-state fluorescence, minimum fluorescence under light, and maximum fluorescence under light of the leaves were measured. The measured data were used to determine the electron transfer rate (ETR), photochemical quenching coefficient (qP), non-photochemical quenching coefficient (NPQ), maximum photochemical quantum yield Fv/Fm of PSII (Fv/Fm), and actual photochemical quantum yield of PSII (ΦPSII). The distribution ratio of light energy absorbed by PSII was (CK indicates no shading (Control) and A indicates 30% Shading, as below). S1 means 5 days after flowering, S2 means 9 days after flowering, S3 means 13 days after flowering, S4 means 17 days after flowering, S5 means 21 days after flowering, S6 means 25 days after flowering, S7 means 29 days after flowering, S8 means 33 days after flowering, S9 means 37 days after flowering, S10 means 41 days after flowers, S11 means 45 days after flowers, S12 means 49 days after flowers.

Determination of Photosynthetic Parameters
The relative chlorophyll content was determined using a CCM-200 chlorophyll meter (OPTI-sciences, Boston, MA, USA). Gas exchange parameters, light response curves, and chlorophyll fluorescence parameters were determined using a Li-6800 portable photosynthesizer (LI-COR, Lincoln, NE, USA). The photosynthesis-light response curve [16] was fitted with the corrected right-angle hyperbola model and the apparent quantum efficiency (AQY), light compensation point (LCP), light saturation point (LSP), maximum net photosynthetic rate (Pn (max) ), and dark respiration rate (Rd) were obtained.
The four bearing branch leaves of each tree's outer crown and inner circumference were randomly selected from east, south, west, and north directions. The Li-6800 portable photosynthometer was used to determine the net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular carbon dioxide concentration (Ci) during mornings of fine weather in the S9 (37 days after flowering) period. Two treatments (A and CK) were set up in this experiment, and three trees were selected for each treatment.
Chlorophyll fluorescence parameters were set for each parameter and leaf selection as above, and four leaves were measured per treatment. The leaves to be tested were wrapped with tin foil before measurement and were dark-adapted overnight. The initial and maximum fluorescence values were measured on the second day. The activation light was set according to the ambient light intensity of the shade treatment and light activation was performed for more than 50 min. The steady-state fluorescence, minimum fluorescence under light, and maximum fluorescence under light of the leaves were measured. The measured data were used to determine the electron transfer rate (ETR), photochemical quenching coefficient (qP), non-photochemical quenching coefficient (NPQ), maximum photochemical quantum yield Fv/Fm of PSII (Fv/Fm), and actual photochemical quantum yield of PSII (ΦPSII). The distribution ratio of light energy absorbed by PSII was obtained according to the method proposed by Demmig-Adams et al. [17] for photochemical energy dissipation, antenna thermal energy dissipation, and non-photochemical energy.

Determination of Fruit Weight and Shape Index
Ten fruits were selected from each sampling period to measure the fruit weight and calculate the shape index. Fruit hardness was measured using a GY-1 hardness meter. A MASTER-M handheld sugar meter was used to calculate the soluble solid concentration (TSS). The Vc content was determined using the 2, 6-dichloroindophenol titrimetric method (AOAC Official Method 967.21). A method involving 1% hydrochloric acid and methanol was used to measure the anthocyanin content [18]. Three replicates were determined for each data sample. Fruit color was determined using a CM-2600d spectrophotometer (Konica Minolta, Tokyo, Japan). At each sampling step, ten fruits were chosen at random and measurements were taken at four locations around the equator. A micro-method kit (Solarbio, Beijing, China) was used to analyze the amount of cellulose and trehalose in accordance with the manufacturer's directions.

Determination of Glycolic Acid Fractions and Content
High-performance liquid chromatography (HPLC) was used with an Agilent 1260 II high-performance liquid chromatography system to measure the contents of soluble sugars and titratable acid fractions (Agilent Technologies, Santa Clara, CA, USA). Refer to Chen et al.'s [18] paper for specific methods.

RNA Extraction and Transcriptome Sequencing
Transcriptome data of sweet cherry fruit treated by A and CK during S9 were studied using the RNA-seq technique.
The total RNA kit was used to recover total RNA (Tiangen Biotechnology Co., Ltd., Beijing, China). In order to check the integrity of the RNA samples, RNA was extracted using an Agilent 2100 Bioanalyzer and a 2100 RNA Nano 6000 assay kit (Agilent Technologies, Inc., Santa Clara, CA, USA). The concentration and purity of the RNA samples were verified with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Transcriptome sequencing was performed by San ni Biosciences (Nantong, China). Genes or transcripts with computed expression fold changes fulfilling |log2 (fold change)| > 1 analysis and a sum of mapping reads 10 in the two samples were selected. A hierarchical clustering heat map between the two treatments was generated using the FPKM (Fragments Per Kilobase of exon model per Million mapped fragments) values as expression levels.

Data Processing and Analysis
The raw data were filtered using fastp software and the clean data were mapped against the reference genome using hisat2 to obtain information on the position of the reads on the reference genome (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA395588 accessed on 20 October 2022), as well as information on the characteristics of the sequenced samples. Differential expression at the transcript and gene levels was analyzed using DEseq2 or edgeR. Gene ontology (GO) enrichment analysis was performed using the topGO R package, and the categories of biological process (BP), cellular component (CC), and molecular function (MF) analyses made up the functional classification annotations. The graphic only displays the top 10 GO keywords' names. The Kyoto Encyclopedia of Genes and Genomes (KEGG) using the clusterProfiler package was used to elucidate the signaling pathways involved in differential genes.

Quantitative Real-Time PCR Analysis
We performed real-time quantitative PCR on nine important differential genes that have been screened for data accuracy. qRT PCR analysis was performed using the Bio-Rad CFX96TM Real-Time PCR System (Bio-Rad, Hercules, CA, USA) and 2× TSINGKE ® Master qRT PCR Mix (SYBR Green I) (TSINGKE, Beijing, China). The amplification procedure was: pre-denaturation at 95 • C for 30 s, denaturation at 95 • C for 5 s, annealing at 59 • C for 30 s. The number of amplification cycles was 39 and each sample was repeated three times. Each 20 L PCR reaction solution contained 2.0 µL diluted cDNA, 0.8 µL of each primer (10 mM), 10 µL SYBR Green I mix, and 6.4 µL dd H 2 O. Finally, gene specific primers were designed using Primer Premier 6 and gene expression was calculated using the 2 −∆∆Ct method [19].
See specific primer information Table S2.

Data Processing and Analysis
The average value was taken after three repetitions for the determination of all indicators. The data were sorted, checked, and plotted using Excel, SPSS 20.0, and Graphpad Prism 8. Figure 1a depicts the leaf phenotype during photosynthesis measurements. Figure 1b depicts several fruit phenotypes that occurred during the growth and ripening of the sweet cherry fruit. The fruit underwent a gradual change from small to large throughout the developmental stage, and the fruit color changed gradually from green to light yellow and finally to dark red. As clearly shown in Figure 1, sweet cherry fruit coloration was affected by the use of shade net treatment. Compared with the control group, shading of the treatment group reduced the fruit coloration.

Leaf Photosynthetic Properties
The parameters governing the gas exchange in sweet cherry leaves were significantly influenced by low-light stress. The net photosynthetic rate of 'Hong deng' sweet cherry leaves under shading decreased by 8.44%, transpiration rate and stomatal conductance were significantly lower than those of the control, and differences in intercellular CO 2 were insignificant (Table 1). These results indicated that the decreased photosynthesis of leaves after shading results in low dry matter accumulation and a reduced proportion of distribution to the fruit. As can be seen in Table 2, the shade group's Fv/Fm, NPQ, and ERT values were significantly lower than those of the control group, although the shade group's PSII and qP values were significantly greater. Low NPQ of the shade group indicated that the proportion of absorbed light energy for non-photochemical dissipation is reduced and additional absorbed light energy is used for photochemical reactions, increasing PSII's ability to use the light energy it has absorbed. As shown in Table 3, the energy consumption of photochemical reactions in the shade group was significantly higher than that in the control group and the antenna heat and non-photochemical energy consumption values were significantly lower than those in the control group. The significant decrease in leaf chlorophyll SPAD values under low-light stress could be attributed to the reduced content of light-catching pigments, such as chlorophyll, located in the cystoid membrane; hence, the light-catching capacity of leaves was reduced ( Figure 2a). Pn is favorably connected with Tr (p < 0.05) and Gs is positively correlated with Tr (p < 0.01), according to an additional correlation study of Pn, Tr, Gs, and Ci ( Figure 2b).  Table 3, the energy consumption of photochemical reaction group was significantly higher than that in the control group and the anten non-photochemical energy consumption values were significantly lower than control group. The significant decrease in leaf chlorophyll SPAD values under low-ligh be attributed to the reduced content of light-catching pigments, such as ch cated in the cystoid membrane; hence, the light-catching capacity of leaves ( Figure 2a). Pn is favorably connected with Tr (p < 0.05) and Gs is positive with Tr (p < 0.01), according to an additional correlation study of Pn, Tr, Gs, a 2b).

Changes in General Fruit Characteristics and Quality
The single-fruit weight of sweet cherry increased continuously during d with the fastest increase from 2.06 g to 7.09 g in S6-S11 in treatment A and f 8.

Changes in General Fruit Characteristics and Quality
The single-fruit weight of sweet cherry increased continuously during development, with the fastest increase from 2.06 g to 7.09 g in S6-S11 in treatment A and from 2.79 g to 8.21 g in CK (Figure 3a). Shading significantly reduced fruit weight, especially during ripening, by 1.03 g (Figure 3a). The longitudinal ( Figure 3b) and transverse ( Figure 3c) diameters of sweet cherries gradually increased during fruit development. The shape of fruit in treatment A was within 0.86-0.89 and the fruit shape index of CK at the ripening stage was within 0.78-0.86 ( Figure 3d). This finding indicated that shading can effectively improve the fruit shape index of the sweet cherry fruit. in treatment A was within 0.86-0.89 and the fruit shape index of CK at the ripening stage was within 0.78-0.86 ( Figure 3d). This finding indicated that shading can effectively improve the fruit shape index of the sweet cherry fruit.

Effect of Shading Treatment on Fruit Hardness, TSS, Anthocyanin, Vitamin C and Trehalose.
The analysis of hardness, TSS, anthocyanin, Vc, and trehalose is shown in Figure 4. The shading treatments affected fruit hardness, with differences starting from the S7 period and CK presenting significantly lower hardness than treatment group A. The hardness of treatment A at maturity was 6.40 Kg/cm 2 , which was significantly higher than that of CK (4.57 Kg/cm 2 ) (Figure 4a). The TSS increased slowly and then rapidly from S6 to S10 in the growth and development period, with significant differences between the two treatments ( Figure 4b). The TSS of treatment group A at maturity decreased by 8.87% compared with the control.

Effect of Shading Treatment on Fruit Hardness, TSS, Anthocyanin, Vitamin C and Trehalose
The analysis of hardness, TSS, anthocyanin, Vc, and trehalose is shown in Figure 4. The shading treatments affected fruit hardness, with differences starting from the S7 period and CK presenting significantly lower hardness than treatment group A. The hardness of treatment A at maturity was 6.40 Kg/cm 2 , which was significantly higher than that of CK (4.57 Kg/cm 2 ) (Figure 4a). The TSS increased slowly and then rapidly from S6 to S10 in the growth and development period, with significant differences between the two treatments ( Figure 4b). The TSS of treatment group A at maturity decreased by 8.87% compared with the control.  The anthocyanin concentration was minimal from S1 to S8 but increased rapidly from S9 until harvest and was significantly higher in CK than that in treatment A (Figure 4c). The Vc concentration gradually increased and peaked at S12 at 12.7 and 13.9 mg/100 g in treatments A and CK, respectively. Significant differences were observed in the Vc concentration between treatments throughout the maturation period (Figure 4d). The trehalose concentration of the shade group was significantly higher than that of the control group in all periods (Figure 4e). The anthocyanin concentration was minimal from S1 to S8 but increased rapidly from S9 until harvest and was significantly higher in CK than that in treatment A (Figure 4c). The Vc concentration gradually increased and peaked at S12 at 12.7 and 13.9 mg/100 g in treatments A and CK, respectively. Significant differences were observed in the Vc concentration between treatments throughout the maturation period (Figure 4d). The trehalose concentration of the shade group was significantly higher than that of the control group in all periods (Figure 4e).

Effect of Shading Treatment on Fruit Soluble Sugar and Titratable Acid Fractions and Concentrations
The overall trend of soluble sugar concentration increased slowly from S1 to S5 and then rapidly after S6 until harvest. The sugar concentration was significantly lower than the control for most periods of shading (Figure 5a). Glucose and fructose were the most abundant components of soluble sugars in the sweet cherry fruit (Figure 5c,d). The titratable acid concentration showed an overall trend of gradual increase (Figure 5b). Malic acid was the most abundant component of titratable acid (Figure 5f). The glucose concentration of the control group was significantly higher than that of the shade group during the ripening period (Figure 5c). The fructose concentration gradually increased and the glucose concentration of the control group was significantly higher than that of the shade group after period S6 (Figure 5d). The trend of sucrose concentration was insignificant during the growth and development period, and no significant difference was observed in the trend of the two treatments (Figure 5e).
The malic acid concentration of sweet cheery decreased and then gradually increased to maturity; meanwhile, the malic acid concentration of the shade group was significantly higher than that of the control group during the maturity period (Figure 5f). The citric The glucose concentration of the control group was significantly higher than that of the shade group during the ripening period (Figure 5c). The fructose concentration gradually increased and the glucose concentration of the control group was significantly higher than that of the shade group after period S6 (Figure 5d). The trend of sucrose concentration was insignificant during the growth and development period, and no significant difference was observed in the trend of the two treatments (Figure 5e).
The malic acid concentration of sweet cheery decreased and then gradually increased to maturity; meanwhile, the malic acid concentration of the shade group was significantly higher than that of the control group during the maturity period (Figure 5f). The citric acid concentration increased and then decreased to a stable level, and the change between the two treatments demonstrated no significant difference (Figure 5g). The quinic acid concentration presented an overall decrease and no difference between the two treatments was observed during the maturity period (Figure 5h).

Effect of Shading Treatment on the Activity of Enzymes Related to Sugar and Acid Metabolism in Fruits
The activities of sucrose acid invertase (AI), sucrose neutral or alkalineinvertase (NI), sucrose phosphate synthase (SPS), decomposition direction of sucrose synthase (SS-I), synthetic direction of sucrose synthase (SS), phosphoenolpyruvate carboxylase (PEPC), malate synthase (NADP-ME), and malate dehydrogenase (NAD-MDH) during the development and ripening of sweet cherry fruit were studied. The enzyme activities of SPS and SS showed an increasing trend during the growth and development period and then decreased to a stable level; meanwhile, the difference between the control and shade groups in the middle and late development periods was insignificant (Figure 6c,d). The enzyme activities of SS-I showed a decreasing trend during the growth and development period and then increased. Notably, the enzyme activities of the control group were significantly higher than those of the shade group in the period after S5 (Figure 6e). malate synthase (NADP-ME), and malate dehydrogenase (NAD-MDH) during the development and ripening of sweet cherry fruit were studied. The enzyme activities of SPS and SS showed an increasing trend during the growth and development period and then decreased to a stable level; meanwhile, the difference between the control and shade groups in the middle and late development periods was insignificant (Figure 6c,d). The enzyme activities of SS-I showed a decreasing trend during the growth and development period and then increased. Notably, the enzyme activities of the control group were significantly higher than those of the shade group in the period after S5 (Figure 6e). The enzyme activity of PEPC presented a decreasing trend during the growth and development period (Figure 6f). The enzyme activity of the control group was significantly higher than that of the shade group in the early stage of fruit development. The enzyme activities of NADP-ME and NAD-MDH demonstrated a decreasing trend and then increased in the overall development period. The enzyme activity of NADP-ME in the control group was lower than that of the shade group in the early stage of growth and The enzyme activity of PEPC presented a decreasing trend during the growth and development period (Figure 6f). The enzyme activity of the control group was significantly higher than that of the shade group in the early stage of fruit development. The enzyme activities of NADP-ME and NAD-MDH demonstrated a decreasing trend and then increased in the overall development period. The enzyme activity of NADP-ME in the control group was lower than that of the shade group in the early stage of growth and development (Figure 6g). Note that the enzyme activities of the control group were significantly lower than those of the shade group in S3, S4, and S6. The differences in NAD-MDH enzyme activities between the two treatments were insignificant (Figure 6h). Figure 7 displays the relationships between enzyme activities and sugar-acid concentration. The total sugar content was highly significantly positively correlated with AI, NI, and SS-I and significantly negatively correlated with SPS, whereas the organic acid content of both treatments was highly significantly negatively correlated with the PEPC.  (Figure 6g). Note that the enzyme activities of the control group were significantly lower than those of the shade group in S3, S4, and S6. The differences in NAD-MDH enzyme activities between the two treatments were insignificant (Figure 6h). Figure 7 displays the relationships between enzyme activities and sugar-acid concentration. The total sugar content was highly significantly positively correlated with AI, NI, and SS-I and significantly negatively correlated with SPS, whereas the organic acid content of both treatments was highly significantly negatively correlated with the PEPC. Correlation between sugar-acid content and enzyme activities related to sugar-acid metabolism: (a) Correlation between total sugar content and enzyme activities related to sugar metabolism in A treatment. (b) Correlation between total sugar content and enzyme activities related to sugar metabolism in CK treatment. (c) Correlation between organic acid content and enzyme activities related to acid metabolism in A treatment. (d) Correlation between organic acid content and enzyme activities related to acid metabolism in CK treatment. * indicates significant correlation at the 0.05 level and ** indicates highly significant correlation at the 0.01 level. ns indicates that the difference is not significant.

Sequencing Quality Analysis
Significant physiological and biochemical changes in sugars, organic acids, soluble solids, vitamin C, and color began to occur in the S9 period. RNA-seq technology was applied to examine the transcriptome data between sweet cherry fruit treatments during this period. For details of transcription sequencing, see Table S5. After removing the splice sequences, uncertain reads, and low-quality reads, a total of 279,674,870 high-quality clean reads were recovered from these two treatments, with an average of 93.24% of clean reads localizing to the sweet cherry genome (see Table S2 for detailed results).
Gene expression correlations among samples are shown in Figure 8b. High correlations were observed among the same treatment and low correlations were revealed among different treatments. This finding indicated that the shade treatment affects the expression of sweet cherry genes. Samples were subjected to PCA analysis and the findings are shown in Figure 8a. On the score map, the duplicates were concentrated and the samples from Correlation between sugar-acid content and enzyme activities related to sugar-acid metabolism: (a) Correlation between total sugar content and enzyme activities related to sugar metabolism in A treatment. (b) Correlation between total sugar content and enzyme activities related to sugar metabolism in CK treatment. (c) Correlation between organic acid content and enzyme activities related to acid metabolism in A treatment. (d) Correlation between organic acid content and enzyme activities related to acid metabolism in CK treatment. * indicates significant correlation at the 0.05 level and ** indicates highly significant correlation at the 0.01 level. ns indicates that the difference is not significant.

Sequencing Quality Analysis
Significant physiological and biochemical changes in sugars, organic acids, soluble solids, vitamin C, and color began to occur in the S9 period. RNA-seq technology was applied to examine the transcriptome data between sweet cherry fruit treatments during this period. For details of transcription sequencing, see Table S5. After removing the splice sequences, uncertain reads, and low-quality reads, a total of 279,674,870 high-quality clean reads were recovered from these two treatments, with an average of 93.24% of clean reads localizing to the sweet cherry genome (see Table S2 for detailed results).
Gene expression correlations among samples are shown in Figure 8b. High correlations were observed among the same treatment and low correlations were revealed among different treatments. This finding indicated that the shade treatment affects the expression of sweet cherry genes. Samples were subjected to PCA analysis and the findings are shown in Figure 8a. On the score map, the duplicates were concentrated and the samples from the two treatments were easily distinguishable. Hence, sweet cherry demonstrated differing gene expression levels between treatments. PC 1 and PC 2 respectively explained 87.3% and 10.4% of the features in the original dataset. A distinction between the shade therapy and no treatment could be seen in PC 1 and PC 2. There was a strong correlation between the samples within the group and a large difference between the groups, which further indicated that the samples changed at the transcription level after treatment (Figure 8b).

Identification of Differentially Expressed Genes
Between the treatment and control groups, 1910 differentially expressed genes were observed. A total of 1258 genes presented significantly higher expression levels and 652 genes demonstrated significantly lower expression levels in the treatment group relative to the control group (Figure 8c,d).
The results of the hierarchical clustering heat map are shown in Figure 8e. The satisfactory intra-group reproducibility and large inter-group differences further indicated that the shading treatment exerts an effect on the sweet cherry gene expression and most genes were downregulated.

GO and KEGG Enrichment Analyses
The majority of DEGs had high CC and BP enrichments and the BP category had much greater enrichments in both treatments, indicating that these pathways may be crucial in low-light stress (Figure 9a, the significantly enriched GO path information in the figure is shown in Table S3). Focusing on the biological process analysis, the results showed that differential genes in treatment groups are enriched mainly in terms of carbon metabolism, organic matter metabolism, and other pathways after shading, relative to the control group.

GO and KEGG Enrichment Analyses
The majority of DEGs had high CC and BP enrichments and the BP category had much greater enrichments in both treatments, indicating that these pathways may be crucial in low-light stress (Figure 9a, the significantly enriched GO path information in the figure is shown in Table S3). Focusing on the biological process analysis, the results showed that differential genes in treatment groups are enriched mainly in terms of carbon metabolism, organic matter metabolism, and other pathways after shading, relative to the control group. We subjected the differential genes to KEGG enrichment analysis to understand the metabolic pathways and functions where DEGs were located between treatment groups (Figure 9b, the significantly enriched KEGG path information in the figure is shown in Table S4). The KEGG enrichment bubble plots illustrated that the differential genes are mainly enriched in some photosynthetic and organic acid metabolic pathways. We subjected the differential genes to KEGG enrichment analysis to understand the metabolic pathways and functions where DEGs were located between treatment groups ( Figure 9b, the significantly enriched KEGG path information in the figure is shown in Table S4). The KEGG enrichment bubble plots illustrated that the differential genes are mainly enriched in some photosynthetic and organic acid metabolic pathways.
The results of GO and KEGG enrichment analyses demonstrated that the organic acid metabolism of sweet cherry fruits is produced differently depending on the shading treatment. In addition, the enrichment of carbon metabolism and photosynthetic metabolism pathways also indicated that shading might further influence the distribution of material metabolism by affecting plant photosynthesis and finally lead to changes in fruit quality.

Differential Gene Screening and Validation
Previous studies revealed that the content of glycolic acid in sweet cherry fruits changes significantly after the use of shade treatment (Figure 10a, The information of all genes in the figure is shown in Table S1.). Therefore, we focused on the changes of glycolic acid-related pathways and observed 25 differential genes in four pathways, namely, fructose and mannose metabolism, starch and sucrose metabolism, pyruvate metabolism, and glycolysis/gluconeogenesis. The results showed that the expression of most genes is suppressed, especially genes directly related to sugar synthesis conversion such as SORD and INV, after the shading treatment. These results are consistent with the accumulation of fruit sugars. pathways also indicated that shading might further influence the distribution of material metabolism by affecting plant photosynthesis and finally lead to changes in fruit quality.

Differential Gene Screening and Validation
Previous studies revealed that the content of glycolic acid in sweet cherry fruits changes significantly after the use of shade treatment (Figure 10a, The information of all genes in the figure is shown in Table S1.). Therefore, we focused on the changes of glycolic acid-related pathways and observed 25 differential genes in four pathways, namely, fructose and mannose metabolism, starch and sucrose metabolism, pyruvate metabolism, and glycolysis/gluconeogenesis. The results showed that the expression of most genes is suppressed, especially genes directly related to sugar synthesis conversion such as SORD and INV, after the shading treatment. These results are consistent with the accumulation of fruit sugars. Real-time quantitative PCR showed that the trends of the transcriptome and RT-qPCR data are basically the same, thereby indicating that the transcriptome data are accurate and reliable (Figure 10b).

Discussion
The energy needed for photosynthesis is provided by light that facilitates assimilation, promotes stomatal opening, activates RuBisCo, and influences the development of the photosynthetic system. Studies have shown that leaves are organs that perceive environmental changes and can change the structure and function of photosynthetic organs with changes in light intensity; the photosynthetic performance of sweet cherry leaves with reduced light intensity will be greatly inhibited [20][21][22][23]. In the results of this experiment, Pn, Tr, and Gs were significantly lower in the shade group than in the control group, which was similar to previous results.
The chlorophyll fluorescence technique explores photosynthesis in plants. Compared with gas exchange parameters, chlorophyll fluorescence parameters can reflect the absorption, transfer, dissipation, and distribution of light energy by the photosystem [24]; moreover, the chlorophyll fluorescence technique can truly and accurately reveal the mechanism of the effect of shading on Pn in plant leaves [25]. The three destinations of light energy absorbed by plant leaves are (1) energy dissipated by antenna pigments in the form of heat energy (D), (2) energy involved in photochemical reactions (P), and (3) Real-time quantitative PCR showed that the trends of the transcriptome and RT-qPCR data are basically the same, thereby indicating that the transcriptome data are accurate and reliable (Figure 10b).

Discussion
The energy needed for photosynthesis is provided by light that facilitates assimilation, promotes stomatal opening, activates RuBisCo, and influences the development of the photosynthetic system. Studies have shown that leaves are organs that perceive environmental changes and can change the structure and function of photosynthetic organs with changes in light intensity; the photosynthetic performance of sweet cherry leaves with reduced light intensity will be greatly inhibited [20][21][22][23]. In the results of this experiment, Pn, Tr, and Gs were significantly lower in the shade group than in the control group, which was similar to previous results.
The chlorophyll fluorescence technique explores photosynthesis in plants. Compared with gas exchange parameters, chlorophyll fluorescence parameters can reflect the absorption, transfer, dissipation, and distribution of light energy by the photosystem [24]; moreover, the chlorophyll fluorescence technique can truly and accurately reveal the mechanism of the effect of shading on Pn in plant leaves [25]. The three destinations of light energy absorbed by plant leaves are (1) energy dissipated by antenna pigments in the form of heat energy (D), (2) energy involved in photochemical reactions (P), and (3) nonchemical reaction dissipation (Ex) is neither dissipated as thermal energy nor involved in photochemical reactions but can only be achieved with non-photochemical reactions such as photorespiration, the Mehler reaction, or electron transfer to oxygen to form singlet oxygen [26,27]. It was shown that Fv/Fm reflected the intrinsic light energy conversion efficiency of the PSII reaction center, and the variation of this parameter was minimal under non-stress conditions and was not affected by species and growth conditions, while it decreased significantly under stress conditions [28,29]. Fv/Fm reflects the inherent light energy conversion efficiency of PSII reaction centers and was significantly lower in the shaded group than that in the control group in this experiment. Therefore, the photoinhibition phenomenon may exceed the reversible deactivation range of the PSII reaction center and cause substantial damage to leaves, thereby weakening the normal photosynthesis of plants. Meanwhile, the shade treatment changed the distribution of absorbed light energy in sweet cherry leaves. The portion of absorbed light energy allocated to photochemical reactions in the shade group increased significantly, while that of antenna heat dissipation decreased significantly. This finding indicated that the shade treatment of sweet cherry leaves mainly allows additional light energy to be used for photochemical reactions by reducing the level of antenna heat dissipation and improves light energy utilization efficiency under low light to enhance the adaption to low light environment. In addition, antenna thermal dissipation, the second energy dissipation mechanism in sweet cherry leaves, is a regulatory energy dissipation mechanism compared with energy dissipation through non-photochemical reactions. This mechanism can mitigate the excessive reduction of PSII and electron transport chain as well as the damage of photosynthetic structure by non-chemical dissipation. Thus, the excess excitation energy in the reaction center is weakened and the degree of photoinhibition is reduced. The extent of photoinhibition is reduced by weakening the excess excitation energy in the reaction center. Note that shading significantly affects photosynthesis, and it serves as the building block for the production of carbohydrates in fruit trees. Carbohydrates also have an immediate impact on the growth, development, and flowering of fruit trees.
The process of fruit development and ripening involves a series of physiological and biochemical changes, including pigment accumulation, fruit softening, aroma and flavor substance formation, etc., which is also the process of fruit quality formation [30]. The ripening process is one of the important stages in the formation of commercial value, and changes in this stage include changes in fruit size, color, and intrinsic quality. The development of drupe fruits such as dates, plums, and sweet cherries follows a double S-shaped growth pattern [2]. Light is an indispensable environmental factor for plant growth and development; however, inadequate light conditions of plants during growth present a number of severe effects on plant physiology, metabolism, and development. Light affects the accumulation of pigments and consumers prefer fruits with attractive colors, with red being the most attractive color [31]. The results of the study showed that the single fruit weight, longitudinal and longitudinal warp, TSS, anthocyanin, and Vc of sweet cherry fruit increased continuously with fruit development, and their changing stages occurred mainly after the color transition period [18], while the results of the present study were consistent with the previous research results.
The type, concentration, and dynamics of sugars and acids in fruits are the important basis of fruit quality formation [32,33]. The results of this study showed that the low light environment may affect the microenvironment of fruit growth, resulting in changes in sugar and organic acid concentration. The results of the shading of grape fruit showed that an appropriate reduction in light intensity (80% light transmission) did not significantly affect soluble solids (TSS) and titratable acids (TA) in the fruit [34], while the study on the fruit of sweet cherry plants that had been grown in the environment of rain-sheltered cultivation facilities found that TSS could increase or decrease depending on the plant variety or the type of rain-sheltered facility [35,36]. In the present study, TSS, anthocyanin, and Vc decreased significantly during the ripening period, which was consistent with previous results. Throughout sweet cherry fruit development, glucose concentration was highest and sucrose concentration was minimal and relatively insignificantly varied. The total sugar, glucose, and fructose concentrations of the control fruit were higher than those of the shade group during the ripening period. The organic acid concentration of sweet cherry fruit was mainly malic acid, which accounted for 93.65% of the total acid concentration at maturity, while the concentration of other organic acids was very low, which showed that the main organic acid determining the flavor of sweet cherry fruit was malic acid; during the fruit development period, malic acid concentration was the highest and showed an overall increasing trend, while the concentration of other acids was very little and the changes were relatively insignificant. The malic and total acid concentrations of the control fruit were lower than those of the shade group during the ripening period, and the higher sugar concentration and lower organic acid concentration determined the flavor advantage of the control group compared with the shade group.
Sugar is a very important carbohydrate in plants and is typically synthesized in the form of sucrose in source leaves, transported to depot tissues, and converted into sucrose, glucose, and fructose through the action of sucrose-metabolizing enzymes for the regulation of material and energy metabolism in cells and continued metabolism and growth [37]. Although the sucrose concentration in sweet cherry is very low, sucrose metabolism plays an important role in sugar metabolism and sucrose metabolism-related enzymes regulate the accumulation of sucrose. Sucrose metabolism-related enzymes are divided into two major groups: sucrose synthases (including SS and SPS), which regulate sucrose synthesis, and sucrose catabolic enzymes (including SS-I, AI, and NI), which regulate reducing sugar synthesis [38]. Changes in reducing sugar concentration were unclear in the early stage of sweet cherry fruit development (S1-S4) when the activities of sucrose synthesis enzymes (SS and SPS) gradually increased, during which reducing sugar may be synthesized into sucrose to participate in the vital metabolic process. Activities of sweet cherry sucrose catabolic enzymes (SS-I, AI, and NI) began to increase from the S5 period, and reducing sugar accumulated rapidly in the fruit while the activity of SS and SPS gradually decreased. The flesh tissue grew rapidly, the fruit expanded, and metabolism accelerated after the fruit entered the color-change stage. The fruit needed other carbon sources for growth and development, and the highly active acidic translocase could provide additional hexose as energy to promote fruit development in this stage. The results showed that the activity of sps enzymes in shaded apple fruit was only half of that in light conditions and shading also had significant effects on other enzymes [39]. In this study, the activities of sucrose catabolic enzymes (SS-I, AI and NI) were significantly higher in the control group than in the shade group during the ripening period, and the activities of sucrose synthase enzymes (SS and SPS) did not differ significantly between the two treatments during the ripening period, which is inconsistent with the above findings, probably due to the different concentrations of sugar components in the fruits of different varieties, resulting in inconsistent changes in enzyme activities during sugar accumulation. The activities of sucrose catabolic enzymes were higher in the control group than in the shade group in this study, so they promoted the accumulation of fructose and glucose in the control group, which is consistent with the significantly higher glucose and fructose concentration in the control group than in the shade group.
The accumulation of sugar and acid concentration during fruit development determines the flavor of the fruit. The organic acid concentration is significantly correlated with fruit acidity and is important not only in balancing fruit flavor but also for fruit photosynthesis, respiration, and other vital metabolic processes [40]. Although high organic acid concentration results in poor fruit flavor, it is crucial for the growth and development of fruits. Moreover, enzymes involved in the metabolism of organic acids control the buildup of organic acids. Generally speaking, malate dehydrogenase (NAD-MDH), malic enzyme (NADP-ME), and phosphoenolpyruvate carboxylase are the enzymes that control malic acid metabolism (PEPC). All three together regulate the synthesis of malic acid. In this study, the variation trend of NAD-MDH, NADP-ME, and malic acid concentration is approximately the same, and the difference in malic acid accumulation in sweet cherry is mainly related to the level of the two enzyme activities. The gradual decrease in PEPC activity may be the reason for the slow accumulation of malic acid in the later stage. The increase in malic acid concentration of sweet cherry fruit after entering the color transition period is related to the rapid increase in NAD-MDH activity. The increase in NADP-ME activity causes malic acid to begin to decompose, resulting in a slow increase in malic acid concentration. The enzyme activities of malic acid synthesis in the control group, NADP-ME, and PEPC, are lower than those in the shading group, while the enzyme activities of decomposition, NADP-ME, are higher than those in the shading group, which may lead to a lower accumulation of malic acid in the control group than in the shading group. The results are consistent with the results of NAD-MDH and PEPC regulating malic acid synthesis and NADP-ME regulating malic acid decomposition in peach fruit [41]. During the different stages of sweet cherry fruit development, the accumulation of organic acids may be the result of the interaction of various acid metabolism enzymes and, by affecting the accumulation of organic acids in the fruit, thereby affect the flavor of the fruit and determining the quality of the fruit.
The regulation of sugar and acid accumulation in sweet cherry is associated not only with the aforementioned enzymes but also related enzyme genes. The regulation of enzyme activity by key enzyme genes affects the flavor of the fruit. Among them, the SORD gene of the fructose and mannose metabolism pathway mainly acts on the interconversion of D-fructose and sorbitol and is inhibited by shading, thereby reducing the interconversion of sugars and negatively affecting the fruit sugar content. The ostB2 gene of the starch and sucrose metabolism pathway promoted the conversion of alglucose-6p to alglucan, thereby advancing the synthesis of glucose; meanwhile, the promotion of the expression of this gene by shading promoted the synthesis of alglucan and increased fruit stress tolerance. The E3.2.1.21 gene acts as the last key step in glucose synthesis, and shading reduced the expression of this gene and inhibited glucose synthesis. In addition, the expression of four INV genes inhibited by shade treatment suppressed sucrose-to-glucose and fructose conversion pathways and reduced the glucose and fructose content.

Conclusions
Shading significantly reduced the quality of sweet cherry fruit and reduced the accumulation of nutrients in the fruit by directly affecting the growth and development of leaves. Shading significantly reduced the fruit weight, sugar content, and vitamin C content at maturity and significantly increased the acid content. Low light stress produces a large number of differential genes related to carbon metabolism, organic acid metabolism, and stress resistance, thereby suggesting that low light stress may affect the expression of these related genes and inclusions in the fruit. This study illustrated that fruit physiological quality is damaged to different degrees under 30% shade stress; therefore, moderate shade treatment (shade rate less than 30%) is recommended in sweet cherry cultivation and management practices to produce excellent fruit. Transcriptome data provide theoretical and technical support for the mechanism of the low-light-tolerant physiological response of sweet cherry and the selection and breeding of low-light-tolerant sweet cherry varieties.
Supplementary Materials: The following supporting information can be downloaded at: https://www. mdpi.com/article/10.3390/horticulturae9060654/s1, Table S1: Genetic information; Table S2: qPCR sequence of differential genes in sweet cherry fruit; Table S3: Significantly enriched GO pathway information; Table S4: Summary of significantly enriched KEGG pathway information; Table S5: Summary of transcriptome sequencing.